Phoenix Neighborhoods Data

# Load libraries

library(knitr, quietly=TRUE)
library(dplyr, quietly=TRUE)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
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library(pander, quietly=TRUE)
library(devtools, quietly=TRUE)
library(censusapi, quietly=TRUE)

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## Attaching package: 'censusapi'

## The following object is masked from 'package:methods':
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library(maptools, quietly=TRUE)

## Checking rgeos availability: TRUE

library(rgdal, quietly=TRUE)

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##  Loaded GDAL runtime: GDAL 2.1.3, released 2017/20/01
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library(geojsonio, quietly=TRUE)

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library(rmapshaper, quietly=TRUE)
library(sf, quietly=TRUE)

## Linking to GEOS 3.6.1, GDAL 2.1.3, PROJ 4.9.3

library(ggplot2, quietly=TRUE)
library(tidyr, quietly=TRUE)
library(viridis, quietly=TRUE)
library(gridExtra, quietly=TRUE)

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## Attaching package: 'gridExtra'

## The following object is masked from 'package:dplyr':
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library(rmapshaper, quietly=TRUE)
library( sp, quietly=TRUE)
library(rgeos, quietly=TRUE)

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##  GEOS runtime version: 3.6.1-CAPI-1.10.1 
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##  Polygon checking: TRUE

library(mapproj, quietly=TRUE)
library(ggmap, quietly=TRUE)

## Google's Terms of Service: https://cloud.google.com/maps-platform/terms/.

## Please cite ggmap if you use it! See citation("ggmap") for details.

library(scales, quietly=TRUE)

## 
## Attaching package: 'scales'

## The following object is masked from 'package:viridis':
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library(RColorBrewer, quietly=TRUE)

#Load in census key
##Census Key
censuskey <- "20f2773e863a33466e0fbace2116919a1c67e4a5"

setwd("../data")

# Load Meta data

## Read csv file with all filtered variables. 
Metadata_2010_ACS5 <- read.csv("./raw/2010ACS5DataDictionary.csv")
Metadata_2015_ACS5 <- read.csv("./raw/2015ACS5DataDictionary.csv")

#Load time series tables
NHGIS_data <- read.csv("./raw/NHGIS_geog_data.csv")

#Manipulate NHGIS data to rename and create percentages



NHGIS_data <- rename(NHGIS_data, NotHispanic.Latino_1990=CP4AA1990, NotHispanic.Latino_2000=CP4AA2000, NotHispanic.Latino_2010=CP4AA2010, Hispanic.Latino1990=CP4AB1990, Hispanic.Latino2000=CP4AB2000, Hispanic.Latino2010=CP4AB2010)

# Rename Racial Variables


NHGIS_data <- rename(NHGIS_data, White_1990=CM1AA1990, White_2000=CM1AA2000, White_2010=CM1AA2010, Black_AA_1990=CM1AB1990, Black_AA_2000=CM1AB2000, Black_AA_2010=CM1AB2010, NativeAm_Alaskan1990=CM1AC1990, NativeAm_Alaskan2000=CM1AC2000,NativeAm_Alaskan2010=CM1AC2010, Asian_1990=CM1AD1990,Asian_2000=CM1AD2000, Asian_2010=CM1AD2010, NativeHawaiian.PacificIslander_1990=CM1AE1990,NativeHawaiian.PacificIslander_2000=CM1AE2000, NativeHawaiian.PacificIslander_2010=CM1AE2010, SomeOther_1990=CM1AF1990, SomeOther_2000=CM1AF2000, SomeOther_2010=CM1AF2010, Two.OrMore_1990=CM1AG1990, Two.OrMore_2000=CM1AG2000, Two.OrMore_2010=CM1AG2010 )

# Rename Number of Units Variables

NHGIS_data <- rename(NHGIS_data, HousingUnits_1990=CM7AA1990, HousingUnits_2000=CM7AA2000, HousingUnits_2010=CM7AA2010)

# Rename Occupancy Variable 

NHGIS_data <- rename(NHGIS_data, HousingUnits_Occupied_1990=CM9AA1990, HousingUnits_Occupied_2000=CM9AA2000, HousingUnits_Occupied_2010=CM9AA2010, HousingUnits_Vacant_1990=CM9AB1990, HousingUnits_Vacant_2000=CM9AB2000, HousingUnits_Vacant_2010=CM9AB2010)

# Rename Vacancy Status Variables 

NHGIS_data <- rename(NHGIS_data, Vacant_ForRent_1990=CN0AA1990, Vacant_ForRent_2000=CN0AA2000, Vacant_ForRent_2010=CN0AA2010, Vacant_ForSale_1990=CN0AB1990, Vacant_ForSale_2000=CN0AB2000, Vacant_ForSale_2010=CN0AB2010, Vacant_RentedOrSold_1990=CN0AC1990, Vacant_RentedOrSold_2000=CN0AC2000, Vacant_RentedOrSold_2010=CN0AC2010, Vacant_OccasionalUse_1990=CN0AD1990, Vacant_OccasionalUse_2000=CN0AD2000, Vacant_OccasionalUse_2010=CN0AD2010, Vacant_MigrantWorkers_1990=CN0AE1990, Vacant_MigrantWorkers_2000=CN0AE2000, Vacant_MigrantWorkers_2010=CN0AE2010, Vacant_Other_1990=CN0AF1990, Vacant_Other_2000=CN0AF2000, Vacant_Other_2010=CN0AF2010)

# Rename Sex Variables 

NHGIS_data <- rename(NHGIS_data, Male_1990=CM0AA1990, 
Male_2000=CM0AA2000,
Male_2010=CM0AA2010, 
Female_1990=CM0AB1990,
Female_2000=CM0AB2000,
Female_2010=CM0AB2010)

# Rename Age Variables 

NHGIS_data <- rename(NHGIS_data, Under5years_1990=CW3AA1990, 
Under5years_2000=CW3AA2000,
Under5years_2010=CW3AA2010, 
Ages5to9_1990=CW3AB1990,
Ages5to9_2000=CW3AB2000,
Ages5to9_2010=CW3AB2010,
Ages10to14_1990=CW3AC1990,
Ages10to14_2000=CW3AC2000,
Ages10to14_2010=CW3AC2010,
Ages15to17_1990=CW3AD1990,
Ages15to17_2000=CW3AD2000,
Ages15to17_2010=CW3AD2010,
Ages25to29_1990=CW3AI1990,
Ages25to29_2000=CW3AI2000,
Ages25to29_2010=CW3AI2010)

# Combine ages 18&19, 20, 21, 22-24. Rename "College Age"
NHGIS_data <- NHGIS_data %>%
  mutate(CollegeAge_1990 = coalesce(CW3AE1990 + CW3AF1990 + CW3AG1990 + CW3AH1990))

NHGIS_data <- NHGIS_data %>%
  mutate(CollegeAge_2000 = coalesce(CW3AE2000 + CW3AF2000 + CW3AG2000 + CW3AH2000))

NHGIS_data <- NHGIS_data %>%
  mutate(CollegeAge_2010 = coalesce(CW3AE2010 + CW3AF2010 + CW3AG2010 + CW3AH2010))

#Combine 30s, rename Age30s
NHGIS_data <- NHGIS_data %>%
  mutate(Age30s_1990 = coalesce(CW3AJ1990 + CW3AK1990))

NHGIS_data <- NHGIS_data %>%
  mutate(Age30s_2000 = coalesce(CW3AJ2000 + CW3AK2000))

NHGIS_data <- NHGIS_data %>%
  mutate(Age30s_2010 = coalesce(CW3AJ2010 + CW3AK2010))

#Combine 40s, rename Age40s
NHGIS_data <- NHGIS_data %>%
  mutate(Age40s_1990 = coalesce(CW3AL1990 + CW3AM1990))

NHGIS_data <- NHGIS_data %>%
  mutate(Age40s_2000 = coalesce(CW3AL2000 + CW3AM2000))

NHGIS_data <- NHGIS_data %>%
  mutate(Age40s_2010 = coalesce(CW3AL2010 + CW3AM2010))

#Combine 50s, rename Age50s
NHGIS_data <- NHGIS_data %>%
  mutate(Age50s_1990 = coalesce(CW3AN1990 + CW3AO1990))

NHGIS_data <- NHGIS_data %>%
  mutate(Age50s_2000 = coalesce(CW3AN2000 + CW3AO2000))

NHGIS_data <- NHGIS_data %>%
  mutate(Age50s_2010 = coalesce(CW3AN2010 + CW3AO2010))

#Combine 60s, rename Age60s
NHGIS_data <- NHGIS_data %>%
  mutate(Age60s_1990 = coalesce(CW3AP1990 + CW3AQ1990 + CW3AR1990))

NHGIS_data <- NHGIS_data %>%
  mutate(Age60s_2000 = coalesce(CW3AP2000 + CW3AQ2000 + CW3AR2000))

NHGIS_data <- NHGIS_data %>%
  mutate(Age60s_2010 = coalesce(CW3AP2010 + CW3AQ2010 + CW3AR2010))

#Combine 70s, rename Age70s
NHGIS_data <- NHGIS_data %>%
  mutate(Age70s_1990 = coalesce(CW3AS1990 + CW3AT1990))

NHGIS_data <- NHGIS_data %>%
  mutate(Age70s_2000 = coalesce(CW3AS2000 + CW3AT2000))

NHGIS_data <- NHGIS_data %>%
  mutate(Age70s_2010 = coalesce(CW3AS2010 + CW3AT2010))

#Combine 80s, rename Age80andOver
NHGIS_data <- NHGIS_data %>%
  mutate(Age80sandOver_1990 = coalesce(CW3AU1990 + CW3AV1990))

NHGIS_data <- NHGIS_data %>%
  mutate(Age80sandOver_2000 = coalesce(CW3AU2000 + CW3AV2000))

NHGIS_data <- NHGIS_data %>%
  mutate(Age80sandOver_2010 = coalesce(CW3AU2010 + CW3AV2010))

# Occupancy and Vacancy 
# Create percentage variables of each Occupancy category

NHGIS_data <- NHGIS_data %>% group_by(TRACTA) %>% 
  mutate((OccupiedHousingUnits_Percent_1990 = HousingUnits_Occupied_1990
 / HousingUnits_1990) * 100) %>%
  mutate(( OccupiedHousingUnits_Percent_2000 = HousingUnits_Occupied_2000
 / HousingUnits_2000) * 100) %>%
mutate(( OccupiedHousingUnits_Percent_2010 = HousingUnits_Occupied_2010
 / HousingUnits_2010) * 100) %>% 
mutate(( VacantHousingUnits_Percent_1990 = HousingUnits_Vacant_1990
 / HousingUnits_1990 ) * 100) %>%
mutate(( VacantHousingUnits_Percent_2000 = HousingUnits_Vacant_2000
 / HousingUnits_2000 ) * 100) %>%
mutate(( VacantHousingUnits_Percent_2010 = HousingUnits_Vacant_2010
 / HousingUnits_2010 ) * 100) %>%
  mutate((forsale_percent_1990 = Vacant_ForSale_1990 / HousingUnits_1990 )* 100 ) %>%
  mutate((forsale_percent_2000 = Vacant_ForSale_2000 / HousingUnits_2000 ) * 100) %>%
  mutate((forsale_percent_2010 = Vacant_ForSale_2010 / HousingUnits_2010 ) * 100)

# Ethnicity 
#Combine Hispanic and Not Hispanic to get an Ethnicity population count

NHGIS_data <- NHGIS_data %>%
  mutate(TotalEthnicityCount_1990 = coalesce(NotHispanic.Latino_1990 + Hispanic.Latino1990))

NHGIS_data <- NHGIS_data %>%
  mutate(TotalEthnicityCount_2000 = coalesce(NotHispanic.Latino_2000 + Hispanic.Latino2000))

NHGIS_data <- NHGIS_data %>%
  mutate(TotalEthnicityCount_2010 = coalesce(NotHispanic.Latino_2010 + Hispanic.Latino2010))

# Create percentage variables of Ethnicity category

NHGIS_data <- NHGIS_data %>% group_by(TRACTA) %>% 
  mutate((Hispanic.Latino_Percent_1990 = Hispanic.Latino1990
 / TotalEthnicityCount_1990) * 100) %>%
  mutate(( NotHispanic.Latino_Percent_1990 = NotHispanic.Latino_1990
 / TotalEthnicityCount_1990) * 100) %>%
mutate(( Hispanic.Latino_Percent_2000 = Hispanic.Latino2000 
 / TotalEthnicityCount_2000) * 100) %>% 
mutate(( NotHispanic.Latino_Percent_2000 = NotHispanic.Latino_2000
 / TotalEthnicityCount_2000 ) * 100) %>%
mutate(( Hispanic.Latino_Percent_2010 = Hispanic.Latino2010 
 / TotalEthnicityCount_2010 ) * 100) %>%
mutate(( NotHispanic.Latino_Percent_2010 = NotHispanic.Latino_2010 
 / TotalEthnicityCount_2010 ) * 100)

# Sex
#Combine Male and Female to get a population count

NHGIS_data <- NHGIS_data %>%
  mutate(TotalSexPopulation_1990 = coalesce(Male_1990 + Female_1990))

NHGIS_data <- NHGIS_data %>%
  mutate(TotalSexPopulation_2000 = coalesce(Male_2000 + Female_2000))

NHGIS_data <- NHGIS_data %>%
  mutate(TotalSexPopulation_2010 = coalesce(Male_2010 + Female_2010))

# Create percentage variables of Sex category

NHGIS_data <- NHGIS_data %>% group_by(TRACTA) %>% 
  mutate((Male_Percent_1990 = Male_1990
 / TotalSexPopulation_1990) * 100) %>%
  mutate(( Female_Percent_1990 = Female_1990 / TotalSexPopulation_1990) * 100) %>%
mutate(( Male_Percent_2000 = Male_2000 / TotalSexPopulation_2000) * 100) %>% 
mutate(( Female_Percent_2000 = Female_2000 / TotalSexPopulation_2000 ) * 100) %>%
mutate(( Male_Percent_2010 = Male_2010 
 / TotalSexPopulation_2010 ) * 100) %>%
mutate(( Female_Percent_2010 = Female_2010 / TotalSexPopulation_2010 ) * 100)

# Write new CSV File
write.csv( NHGIS_data, "NHGIS_data_rename.csv", row.names=F)

Manipulate ACS data

##2015

## Variable list

race_2015_vars <- read.csv("variable_lists/race_2015_ACS5.csv")

## Download data
### Create Variable list based off variables in the first column
var.list.race.2015 <- race_2015_vars$name

### Pull Data using variable list only. Make sure the censusapi package is loaded.
race.pop.2015 <- getCensus( name = "acs/acs5", vintage = 2015,
                            key=censuskey,
                               vars = var.list.race.2015,
                               region="tract:*",
                            regionin="state:04&county:013" )

## Rename variables
### Rename data
race.pop.2015 <- rename(race.pop.2015, 
                        Total_2015=B25006_001E, 
                        White_2015=B02001_002E, 
                        Black_2015=B02001_003E,
                        American_Indian_2015=B02001_004E,
                        Asian_2015=B02001_005E ,
                        Pacific_Islander_2015=B02001_006E,
                        Two_plus_races_2015= B02001_008E,
                        Other_Race_2015=B02001_007E,
                         Not_hispanic_2015= B03003_002E,
                         Hispanic_2015= B03003_003E)

### Add Percentages

race.pop.2015 <- race.pop.2015 %>% group_by(tract) %>% 
  mutate(( White_Percent_2015 = White_2015 / Total_2015) * 100) %>%
mutate(( Black_Percent_2015 = Black_2015 / Total_2015) * 100) %>% 
mutate(( Indian_Percent_2015 = American_Indian_2015 / Total_2015 ) * 100) %>%
mutate(( Asian_Percent_2015 = Asian_2015 / Total_2015 ) * 100) %>%
mutate(( Pacific_Islander_Percent_2015 = Pacific_Islander_2015 / Total_2015 ) * 100) %>%
mutate(( Two_plus_racesPercent_2015 = Two_plus_races_2015 / Total_2015 ) * 100) %>%
mutate(( Other_Percent_2015 = Other_Race_2015 / Total_2015 ) * 100) %>%
  mutate(( Hispanic_percent_2015 = Hispanic_2015 / Total_2015) * 100 ) %>%
  mutate((Not_hispanic_percent_2015 = Not_hispanic_2015 / Total_2015) * 100)

##Geoid
###Create GEOID of FIPS Code elements
race_geoid_2015 <- paste0( race.pop.2015$state, race.pop.2015$county, race.pop.2015$tract)

race.pop.2015$geoid <- race_geoid_2015

# Sex

##1990, 2000, and 2010


##2015
###Read csv file with only age variables. I created this by selecting variables from the Metadata and putting them into a separate csv file. Unfortunately, there was no "Sex" alone variables, so I selected Total sex estimates from a different concept.

sex_vars_2015 <- read.csv("variable_lists/sex_vars_2015.csv")

## Warning in read.table(file = file, header = header, sep = sep, quote =
## quote, : incomplete final line found by readTableHeader on 'variable_lists/
## sex_vars_2015.csv'

### Create Variable list based off variables in the first column
sex.list.2015 <- sex_vars_2015$name
sex.pop.2015 <- getCensus( name = "acs/acs5", vintage = 2015,
                           key=censuskey,
                               vars = sex.list.2015,
                               region="tract:*",
                           regionin="state:04&county:013" )

#Rename the variables
sex.pop.2015 <- rename(sex.pop.2015,
                       Total_sex_2015= B01001_001E,
                         Male_2015= B01001_002E,
                         Female_2015= B01001_026E)
###Create GEOID of FIPS Code elements
sex_geoid_2015 <- paste0( sex.pop.2015$state, sex.pop.2015$county, sex.pop.2015$tract)

sex.pop.2015$geoid <- sex_geoid_2015

# Education

##2010 and 2015

###Read csv file with only race variables. I manually created this by cutting and pasting the rows I wanted from the previous spreadsheet. 
educ_2010_vars <- read.csv("variable_lists/educ_2010_vars.csv")

### Create Variable list based off variables in the first column
var.list.educ.2010 <- educ_2010_vars$name

educ.pop.2010 <- getCensus( name = "acs/acs5", vintage = 2010,
                            key=censuskey,
                               vars = var.list.educ.2010,
                               region="tract:*",
                            regionin="state:04&county:013" )


educ.pop.2010 <- rename(educ.pop.2010, Total_2010=B15002_001E,
                        No_school_2010_M=B15002_003E,
                        Fourth_2010_M=B15002_004E,
                         Sixth_2010_M=B15002_005E,
                        Eighth_2010_M=B15002_006E, 
                        Ninth_2010_M=B15002_007E,
                        Tenth_2010_M= B15002_008E,
                       Eleventh_2010_M=B15002_009E,
                       Twelfth_NO_2010_M=B15002_010E,
                       HSD_GED_2010_M=B15002_011E,
                       SomeCollege_0yr_2010_M=B15002_012E,
                       SomeCollege_1yr_2010_M=B15002_013E,
                       AA_2010_M=B15002_014E,
                       BA_2010_M=B15002_015E,
                       Masters_2010_M=B15002_016E,
                       ProfSchool_2010_M=B15002_017E,
                       Doctoral_2010_M=B15002_018E,
                        No_school_2010_F=B15002_020E,
                       Fourth_2010_F=B15002_021E,
                        Sixth_2010_F=B15002_022E,
                       Eighth_2010_F=B15002_023E, 
                        Ninth_2010_F=B15002_024E,
                       Tenth_2010_F=B15002_025E,
                       Eleventh_2010_F=B15002_026E,
                       Twelfth_NO_2010_F=B15002_027E,
                       HSD_GED_2010_F=B15002_028E,
                       SomeCollege_0yr_2010_F=B15002_029E,
                       SomeCollege_1yr_2010_F=B15002_030E,
                       AA_2010_F=B15002_031E,
                       BA_2010_F=B15002_032E,
                       Masters_2010_F=B15002_033E,
                       ProfSchool_2010_F=B15002_034E,
                       Doctoral_2010_F=B15002_035E)


###Combine variable categories as necessary, including combining Male and Female to get a population count.

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(LessThanNinth_2010 = coalesce(Fourth_2010_M + Fourth_2010_F + Sixth_2010_M + Sixth_2010_F + Eighth_2010_M +  Eighth_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(NoSchool_2010 = coalesce(No_school_2010_F + No_school_2010_M))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(Ninthgrade_2010 = coalesce(Ninth_2010_M + Ninth_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(Tenthgrade_2010 = coalesce(Tenth_2010_M+ Tenth_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(Eleventhgrade_2010 = coalesce(Eleventh_2010_M + Eleventh_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(Twelfthgrade_2010 = coalesce(Twelfth_NO_2010_M + Twelfth_NO_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(HSDiploma_GED_2010 = coalesce(HSD_GED_2010_M + HSD_GED_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(SomeCollege_2010 = coalesce(SomeCollege_0yr_2010_M +
                                       SomeCollege_1yr_2010_M +
                                       SomeCollege_0yr_2010_F +
                                       SomeCollege_1yr_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(AA_2010 = coalesce(AA_2010_M + AA_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(BA_2010 = coalesce(BA_2010_M + BA_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(Masters_2010 = coalesce(Masters_2010_M + Masters_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(ProfSchool_2010 = coalesce(ProfSchool_2010_M + ProfSchool_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(Doctoral_2010 = coalesce(Doctoral_2010_M + Doctoral_2010_F))

educ.pop.2010 <- educ.pop.2010 %>%
  mutate(hs_above_2010 = coalesce(HSD_GED_2010_M + HSD_GED_2010_F +  SomeCollege_0yr_2010_M + SomeCollege_0yr_2010_F + SomeCollege_1yr_2010_M + AA_2010_M +  AA_2010_F + BA_2010_M + BA_2010_F +  Masters_2010_M + Masters_2010_F + ProfSchool_2010_M + ProfSchool_2010_F + Doctoral_2010_M + Doctoral_2010_F))


###Create percentage variables of each educational category

educ.pop.2010 <- educ.pop.2010 %>% group_by(tract) %>% 
  mutate((No_school_Percent_2010 = NoSchool_2010 / Total_2010) * 100) %>%
  mutate(( LessThanNinth_Percent_2010 = LessThanNinth_2010 / Total_2010) * 100) %>%
mutate(( Ninthgrade_Percent_2010 = Ninthgrade_2010 / Total_2010) * 100) %>% 
mutate(( Tenthgrade_Percent_2010 = Tenthgrade_2010 / Total_2010 ) * 100) %>%
mutate(( Eleventhgrade_Percent_2010 = Eleventhgrade_2010 / Total_2010 ) * 100) %>%
mutate(( Twelfthgrade_Percent_2010 = Twelfthgrade_2010 / Total_2010 ) * 100) %>%
mutate(( HSD_GED_Percent_2010 = HSDiploma_GED_2010 / Total_2010 ) * 100) %>%
mutate(( SomeCollege_Percent_2010 = SomeCollege_2010  / Total_2010 ) * 100) %>%
mutate(( AA_Percent_2010 = AA_2010 / Total_2010 ) * 100) %>%
mutate(( BA_Percent_2010 = BA_2010 / Total_2010 ) * 100) %>%
mutate(( Masters_Percent_2010 = Masters_2010 / Total_2010 ) * 100) %>%
mutate(( ProfSchool_Percent_2010 = ProfSchool_2010 / Total_2010 ) * 100) %>%
mutate(( Doctoral_Percent_2010 = Doctoral_2010 / Total_2010 ) * 100) %>%
  mutate(( hs_above_Percent_2010 = hs_above_2010 / Total_2010) * 100)

### Geoid

#Create GEOID of FIPS Code elements
educ_geoid_2010 <- paste0( educ.pop.2010$state, educ.pop.2010$county, educ.pop.2010$tract)

educ.pop.2010$geoid <- educ_geoid_2010

###Read csv file with only race variables. I manually created this by cutting and pasting the rows I wanted from the previous spreadsheet. 
educ_2015_vars <- read.csv("variable_lists/educ_2015_vars.csv")

### Create Variable list based off variables in the first column
var.list.educ.2015 <- educ_2015_vars$name


### Pull Data using variable list only. 
educ.pop.2015 <- getCensus( name = "acs/acs5", vintage = 2015,
                            key=censuskey,
                               vars = var.list.educ.2015,
                               region="tract:*",
                            regionin="state:04&county:013" )

### Rename data
educ.pop.2015 <- rename(educ.pop.2015, Total_2015=B15003_001E,
                        No_school_2015=B15003_002E,
                        Prek_2015=B15003_003E,
                        Kinder_2015=B15003_004E,
                        Firstgrade_2015=B15003_005E, 
                        Secondgrade_2015=B15003_006E, 
                        Thirdgrade_2015= B15003_007E,
                       Fourthgrade_2015=B15003_008E,
                       Fifthgrade_2015=B15003_009E,
                       Sixthgrade_2015=B15003_010E,
                       Seventhgrade_2015=B15003_011E,
                       Eighthgrade_2015=B15003_012E,
                       Ninthgrade_2015=B15003_013E,
                       Tenthgrade_2015=B15003_014E,
                       Eleventhgrade_2015=B15003_015E,
                       Twelfthgrade_2015=B15003_016E,
                       HSdiploma_2015=B15003_017E,
                       GED_2015=B15003_018E,
                       Somecollege_0yr_2015=B15003_019E,
                       Somecollege_1yr_2015=B15003_020E,
                       AA_2015=B15003_021E,
                       Bachelors_2015=B15003_022E,
                       Masters_2015=B15003_023E,
                       ProfSchool_2015=B15003_024E,
                       Doctoral_2015=B15003_025E)


### Combine Categories as necessary to make meaningful categories

educ.pop.2015 <- educ.pop.2015 %>%
  mutate(LessThanNinth_2015 = coalesce(Prek_2015 + Kinder_2015 + Firstgrade_2015 + Secondgrade_2015 + Thirdgrade_2015 +  Fourthgrade_2015 + Fifthgrade_2015 + Sixthgrade_2015 + Seventhgrade_2015 + Eighthgrade_2015))

educ.pop.2015 <- educ.pop.2015 %>% 
  mutate(SomeCollege_2015 = coalesce(Somecollege_0yr_2015 + Somecollege_1yr_2015))

educ.pop.2015 <- educ.pop.2015 %>%
  mutate(hs_above_2015 = coalesce(HSdiploma_2015 + GED_2015 + Somecollege_0yr_2015 + Somecollege_1yr_2015 + AA_2015 +  Bachelors_2015 + Masters_2015 + ProfSchool_2015 + Doctoral_2015))

### Add Percentages

educ.pop.2015 <- educ.pop.2015 %>% group_by(tract) %>% 
  mutate((No_school_Percent_2015 = No_school_2015 / Total_2015) * 100) %>%
  mutate(( LessThanNinth_Percent_2015 = LessThanNinth_2015 / Total_2015) * 100) %>%
mutate(( Ninthgrade_Percent_2015 = Ninthgrade_2015 / Total_2015) * 100) %>% 
mutate(( Tenthgrade_Percent_2015 = Tenthgrade_2015 / Total_2015 ) * 100) %>%
mutate(( Eleventhgrade_Percent_2015 = Eleventhgrade_2015 / Total_2015 ) * 100) %>%
mutate(( Twelfthgrade_Percent_2015 = Twelfthgrade_2015 / Total_2015 ) * 100) %>%
mutate(( HSDiploma_Percent_2015 = HSdiploma_2015 / Total_2015 ) * 100) %>%
mutate(( GED_Percent_2015 = GED_2015 / Total_2015 ) * 100) %>%
mutate(( SomeCollege_Percent_2015 = SomeCollege_2015  / Total_2015 ) * 100) %>%
mutate(( AA_Percent_2015 = AA_2015 / Total_2015 ) * 100) %>%
mutate(( Bachelors_Percent_2015 = Bachelors_2015 / Total_2015 ) * 100) %>%
mutate(( Masters_Percent_2015 = Masters_2015 / Total_2015 ) * 100) %>%
mutate(( ProfSchool_Percent_2015 = ProfSchool_2015 / Total_2015 ) * 100) %>%
mutate(( Doctoral_Percent_2015 = Doctoral_2015 / Total_2015 ) * 100) %>%
mutate(( hs_above_percent_2015 = hs_above_2015 / Total_2015) * 100)

###Geo id
#Create GEOID of FIPS Code elements
educ_geoid_2015 <- paste0( educ.pop.2015$state, educ.pop.2015$county, educ.pop.2015$tract)

educ.pop.2015$geoid <- educ_geoid_2015

# Income

##2010 and 2015

### Read csv file with only race variables. 
income_2010_vars <- read.csv("variable_lists/income_2010_vars.csv")

### Create Variable list based off variables in the first column
var.list.income.2010 <- income_2010_vars$name

###Download the data
income.pop.2010 <- getCensus( name = "acs/acs5", vintage = 2010,
                              key=censuskey,
                               vars = var.list.income.2010,
                               region="tract:*",
                              regionin="state:04&county:013" )

##Rename the variables
income.pop.2010 <- rename(income.pop.2010, Total_income_2010=B19001_001E,
                        Lessthan10k_income_2010=B19001_002E, 
                        TenkTo14k_income_2010=B19001_003E,
                        Fifteenkto20k_income_2010=B19001_004E,
                        TwentykTo25k_income_2010=B19001_005E, 
                        TwentyfivekTo30k_income_2010=B19001_006E, 
                        ThirtykTo35k_income_2010= B19001_007E,
                       ThirtyfivekTo40k_income_2010=B19001_008E,
                       FortykTo45k_income_2010=B19001_009E,
                       FortyfivekTo50k_income_2010=B19001_010E,
                       FiftykTo60k_income_2010=B19001_011E,
                       SixtykTo75k_income_2010=B19001_012E, 
                       SeventyfivekTo100k_income_2010=B19001_013E,
                       OnehundredkTo125k_income_2010=B19001_014E, 
                       OnetwentyfivekTo150k_income_2010=B19001_015E,
                       OnefiftykTo200k_income_2010=B19001_016E, 
                       TwohundredkPlus_income_2010=B19001_017E)

###Combine variable categories as necessary.
income.pop.2010 <- income.pop.2010 %>%
  mutate(OnetwentyfivekPlus_income_2010 = coalesce(OnehundredkTo125k_income_2010 + OnefiftykTo200k_income_2010 + TwohundredkPlus_income_2010))


income.pop.2010 <- income.pop.2010 %>%
  mutate(belowpoverty_2010 = coalesce(Lessthan10k_income_2010 + TenkTo14k_income_2010 + Fifteenkto20k_income_2010))

###Create percentage variables of each educational category
income.pop.2010 <- income.pop.2010 %>% group_by(tract) %>% 
  mutate((Lessthan10k_Percent_2010 = Lessthan10k_income_2010 / Total_income_2010) * 100) %>%
  mutate(( TenkTo14k_Percent_2010 = TenkTo14k_income_2010 / Total_income_2010) * 100) %>%
mutate(( TenkTo14k_Percent_2010 = TenkTo14k_income_2010 / Total_income_2010) * 100) %>% 
mutate(( Fifteenkto20k_Percent_2010 = Fifteenkto20k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( TwentykTo25k_Percent_2010 = TwentykTo25k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( TwentyfivekTo30k_Percent_2010 = TwentyfivekTo30k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( ThirtykTo35k_2010 = ThirtykTo35k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( ThirtyfivekTo40k_Percent_2010 = ThirtyfivekTo40k_income_2010  / Total_income_2010 ) * 100) %>%
mutate(( FortykTo45k_Percent_2010 = FortykTo45k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( FortyfivekTo50k_Percent_2010 = FortyfivekTo50k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( FiftykTo60k_Percent_2010 = FiftykTo60k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( SixtykTo75k_Percent_2010 = SixtykTo75k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( SeventyfivekTo100k_Percent_2010 = SeventyfivekTo100k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( OnehundredkTo125k_Percent_2010 = OnehundredkTo125k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( OnetwentyfivekTo150k_Percent_2010 = OnetwentyfivekTo150k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( OnefiftykTo200k_Percent_2010 = OnefiftykTo200k_income_2010 / Total_income_2010 ) * 100) %>%
mutate(( TwohundredkPlus_Percent_2010 = TwohundredkPlus_income_2010 / Total_income_2010 ) * 100)%>%
  mutate(( belowpoverty_percent_2010 = belowpoverty_2010 / Total_income_2010 ) * 100)

###Create GEOID of FIPS Code elements
income_geoid_2010 <- paste0( income.pop.2010$state, income.pop.2010$county, income.pop.2010$tract)
income.pop.2010$geoid <- income_geoid_2010

###Read csv file with only income variables for 2015. 
income_2015_vars <- read.csv("variable_lists/income_2015_vars.csv")

### Create Variable list based off variables in the first column
var.list.income.2015 <- income_2015_vars$name

### Pull Data using variable list only. Make sure the censusapi package is loaded.
income.pop.2015 <- getCensus( name = "acs/acs5", vintage = 2015,
                              key=censuskey,
                               vars = var.list.income.2015,
                               region="tract:*",
                              regionin="state:04&county:013" )
### Rename data
income.pop.2015 <- rename(income.pop.2015,
                      Total_income_2015=B19001_001E,
                        Lessthan10k_income_2015=B19001_002E, 
                        TenkTo14k_income_2015=B19001_003E,
                        Fifteenkto20k_income_2015=B19001_004E,
                        TwentykTo25k_income_2015=B19001_005E, 
                        TwentyfivekTo30k_income_2015=B19001_006E, 
                        ThirtykTo35k_income_2015= B19001_007E,
                       ThirtyfivekTo40k_income_2015=B19001_008E,
                       FortykTo45k_income_2015=B19001_009E,
                       FortyfivekTo50k_income_2015=B19001_010E,
                       FiftykTo60k_income_2015=B19001_011E,
                       SixtykTo75k_income_2015=B19001_012E, 
                       SeventyfivekTo100k_income_2015=B19001_013E,
                       OnehundredkTo125k_income_2015=B19001_014E, 
                       OnetwentyfivekTo150k_income_2015=B19001_015E,
                       OnefiftykTo200k_income_2015=B19001_016E, 
                       TwohundredkPlus_income_2015=B19001_017E)

###Combine Categories
income.pop.2015 <- income.pop.2015 %>%
  mutate(OnetwentyfivekPlus_income_2015 = coalesce(OnehundredkTo125k_income_2015 + OnefiftykTo200k_income_2015 + TwohundredkPlus_income_2015))

income.pop.2015 <- income.pop.2015 %>%
  mutate(belowpoverty_2015 = coalesce(Lessthan10k_income_2015 + TenkTo14k_income_2015 + Fifteenkto20k_income_2015))

### Add Percentages
income.pop.2015 <- income.pop.2015 %>% group_by(tract) %>% 
  mutate((Lessthan10k_Percent_2015 = Lessthan10k_income_2015 / Total_income_2015) * 100) %>%
  mutate(( TenkTo14k_Percent_2015 = TenkTo14k_income_2015 / Total_income_2015) * 100) %>%
mutate(( TenkTo14k_Percent_2015 = TenkTo14k_income_2015 / Total_income_2015) * 100) %>% 
mutate(( Fifteenkto20k_Percent_2015 = Fifteenkto20k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( TwentykTo25k_Percent_2015 = TwentykTo25k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( TwentyfivekTo30k_Percent_2015 = TwentyfivekTo30k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( ThirtykTo35k_Percent_2015 = ThirtykTo35k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( ThirtyfivekTo40k_Percent_2015 = ThirtyfivekTo40k_income_2015  / Total_income_2015 ) * 100) %>%
mutate(( FortykTo45k_Percent_2015 = FortykTo45k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( FortyfivekTo50k_Percent_2015 = FortyfivekTo50k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( FiftykTo60k_Percent_2015 = FiftykTo60k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( SixtykTo75k_Percent_2015 = SixtykTo75k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( SeventyfivekTo100k_Percent_2015 = SeventyfivekTo100k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( OnehundredkTo125k_Percent_2015 = OnehundredkTo125k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( OnetwentyfivekTo150k_Percent_2015 = OnetwentyfivekTo150k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( OnefiftykTo200k_Percent_2015 = OnefiftykTo200k_income_2015 / Total_income_2015 ) * 100) %>%
mutate(( TwohundredkPlus_Percent_2015 = TwohundredkPlus_income_2015 / Total_income_2015 ) * 100) %>%
  mutate(( belowpoverty_percent_2015 = belowpoverty_2015 / Total_income_2015 ) * 100)

###Create GEOID of FIPS Code elements
income_geoid_2015 <- paste0( income.pop.2015$state, income.pop.2015$county, income.pop.2015$tract)

income.pop.2015$geoid <- income_geoid_2015


# Value

##2010 and 2015

###Read csv file with only race variables. I manually created this by cutting and pasting the rows I wanted from the previous spreadsheet. 
value_2010_vars <- read.csv("variable_lists/value_vars_2010.csv")


### Create Variable list based off variables in the first column
var.list.value.2010 <- value_2010_vars$name

##Download the data
value.pop.2010 <- getCensus( name = "acs/acs5", vintage = 2010,
                             key=censuskey,
                               vars = var.list.value.2010,
                               region="tract:*",
                             regionin="state:04&county:013" )

##Rename variables
value.pop.2010 <- rename(value.pop.2010,
                         Total_value_2010=B25075_001E,
                        Lessthan10k_value_2010=B25075_002E, 
                        TenkTo14k_value_2010=B25075_003E,
                        Fifteenkto20k_value_2010=B25075_004E,
                        TwentykTo25k_value_2010=B25075_005E, 
                        TwentyfivekTo30k_value_2010=B25075_006E, 
                        ThirtykTo35k_value_2010= B25075_007E,
                       ThirtyfivekTo40k_value_2010=B25075_008E,
                       FortykTo50k_value_2010=B25075_009E,
                       FiftykTo60k_value_2010=B25075_010E,
                       SixtykTo70k_value_2010=B25075_011E, 
                       SeventykTo80k_value_2010=B25075_012E,
                       Eightykto90k_value_2010=B25075_013E,
                       Ninetykto100k_value_2010=B25075_014E,
                       OnehundredkTo125k_value_2010=B25075_015E, 
                       OnetwentyfivekTo150k_value_2010=B25075_016E,
                       OnefiftykTo175k_value_2010=B25075_017E, 
                       One75kTo200k_value_2010=B25075_018E, 
                       Twohundredkto250k_value_2010=B25075_019E, 
                       Twofiftykto300k_value_2010=B25075_020E, 
                       Threehundredkto400k_value_2010=B25075_021E, 
                       Fourhundredkto500k_value_2010=B25075_022E, 
                       Fivehundredkto750k_value_2010=B25075_023E, 
                       Sevenfiftykto1mil_value_2010=B25075_024E, 
                       OnemilPlus_value_2010=B25075_025E)

###Create percentage variables of each educational category
value.pop.2010 <- value.pop.2010 %>% group_by(tract) %>% 
  mutate((Lessthan10k_Percent_2010 = Lessthan10k_value_2010 / Total_value_2010) * 100) %>%
  mutate(( TenkTo14k_Percent_2010 = TenkTo14k_value_2010 / Total_value_2010) * 100) %>%
mutate(( TenkTo14k_Percent_2010 = TenkTo14k_value_2010 / Total_value_2010) * 100) %>% 
mutate(( Fifteenkto20k_Percent_2010 = Fifteenkto20k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( TwentykTo25k_Percent_2010 = TwentykTo25k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( TwentyfivekTo30k_Percent_2010 = TwentyfivekTo30k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( ThirtykTo35k_2010 = ThirtykTo35k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( ThirtyfivekTo40k_Percent_2010 = ThirtyfivekTo40k_value_2010  / Total_value_2010 ) * 100) %>%
mutate(( FortykTo50k_Percent_2010 = FortykTo50k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( FiftykTo60k_Percent_2010 = FiftykTo60k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( SixtykTo70k_Percent_2010 = SixtykTo70k_value_2010 / Total_value_2010 ) * 100) %>%
mutate((  Eightykto90k_Percent_2010 =  Eightykto90k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( Ninetykto100k_Percent_2010 = Ninetykto100k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( OnehundredkTo125k_Percent_2010 = OnehundredkTo125k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( OnetwentyfivekTo150k_Percent_2010 = OnetwentyfivekTo150k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( OnefiftykTo175k_Percent_2010 = OnefiftykTo175k_value_2010 / Total_value_2010 ) * 100) %>%
mutate((  One75kTo200k_Percent_2010 =  One75kTo200k_value_2010 / Total_value_2010 ) * 100) %>%
mutate(( Twohundredkto250k_Percent_2010 = Twohundredkto250k_value_2010 / Total_value_2010 ) * 100) %>%
  mutate(( Twofiftykto300k_Percent_2010 = Twofiftykto300k_value_2010 / Total_value_2010 ) * 100) %>%
  mutate(( Threehundredkto400k_Percent_2010 = Threehundredkto400k_value_2010 / Total_value_2010 ) * 100) %>%
  mutate(( Fourhundredkto500k_Percent_2010 = Fourhundredkto500k_value_2010 / Total_value_2010 ) * 100) %>%
  mutate(( Fivehundredkto750k_Percent_2010 = Fivehundredkto750k_value_2010 / Total_value_2010 ) * 100) %>%
  mutate(( Sevenfiftykto1mil_Percent_2010 = Sevenfiftykto1mil_value_2010 / Total_value_2010 ) * 100) %>%
  mutate(( OnemilPlus_Percent_2010 = OnemilPlus_value_2010 / Total_value_2010 ) * 100)

### Create GEOID of FIPS Code elements
value_geoid_2010 <- paste0( value.pop.2010$state, value.pop.2010$county, value.pop.2010$tract)
value.pop.2010$geoid <- value_geoid_2010

### Read csv file with only race variables. I manually created this by cutting and pasting the rows I wanted from the previous spreadsheet. 
value_2015_vars <- read.csv("variable_lists/value_vars_2015.csv")

### Create Variable list based off variables in the first column
var.list.value.2015 <- value_2015_vars$name

###Download data
value.pop.2015 <- getCensus( name = "acs/acs5", vintage = 2015,
                             key=censuskey,
                               vars = var.list.value.2015,
                               region="tract:*",
                             regionin="state:04&county:013" )

### Rename variables
value.pop.2015 <- rename(value.pop.2015,
                         Total_value_2015=B25075_001E,
                        Lessthan10k_value_2015=B25075_002E, 
                        TenkTo14k_value_2015=B25075_003E,
                        Fifteenkto20k_value_2015=B25075_004E,
                        TwentykTo25k_value_2015=B25075_005E, 
                        TwentyfivekTo30k_value_2015=B25075_006E, 
                        ThirtykTo35k_value_2015= B25075_007E,
                       ThirtyfivekTo40k_value_2015=B25075_008E,
                       FortykTo50k_value_2015=B25075_009E,
                       FiftykTo60k_value_2015=B25075_010E,
                       SixtykTo70k_value_2015=B25075_011E, 
                       SeventykTo80k_value_2015=B25075_012E,
                       Eightykto90k_value_2015=B25075_013E,
                       Ninetykto100k_value_2015=B25075_014E,
                       OnehundredkTo125k_value_2015=B25075_015E, 
                     OnetwentyfivekTo150k_value_2015=B25075_016E,
                       OnefiftykTo175k_value_2015=B25075_017E, 
                       One75kTo200k_value_2015=B25075_018E, 
                       Twohundredkto250k_value_2015=B25075_019E, 
                       Twofiftykto300k_value_2015=B25075_020E, 
                       Threehundredkto400k_value_2015=B25075_021E,
                       Fourhundredkto500k_value_2015=B25075_022E, 
                       Fivehundredkto750k_value_2015=B25075_023E, 
                       Sevenfiftykto1mil_value_2015=B25075_024E, 
                       OnemiltoOnemilhalf_value_2015=B25075_025E,
                       Onemilhalfto2mil_value_2015=B25075_026E,
                       Twomilplus_value_2015=B25075_027E)

### Create percentage variables of each educational category
value.pop.2015 <- value.pop.2015 %>% group_by(tract) %>% 
  mutate((Lessthan10k_Percent_2015 = Lessthan10k_value_2015 / Total_value_2015) * 100) %>%
  mutate(( TenkTo14k_Percent_2015 = TenkTo14k_value_2015 / Total_value_2015) * 100) %>%
mutate(( TenkTo14k_Percent_2015 = TenkTo14k_value_2015 / Total_value_2015) * 100) %>% 
mutate(( Fifteenkto20k_Percent_2015 = Fifteenkto20k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( TwentykTo25k_Percent_2015 = TwentykTo25k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( TwentyfivekTo30k_Percent_2015 = TwentyfivekTo30k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( ThirtykTo35k_2015 = ThirtykTo35k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( ThirtyfivekTo40k_Percent_2015 = ThirtyfivekTo40k_value_2015  / Total_value_2015 ) * 100) %>%
mutate(( FortykTo50k_Percent_2015 = FortykTo50k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( FiftykTo60k_Percent_2015 = FiftykTo60k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( SixtykTo70k_Percent_2015 = SixtykTo70k_value_2015 / Total_value_2015 ) * 100) %>%
mutate((  Eightykto90k_Percent_2015 =  Eightykto90k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( Ninetykto100k_Percent_2015 = Ninetykto100k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( OnehundredkTo125k_Percent_2015 = OnehundredkTo125k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( OnetwentyfivekTo150k_Percent_2015 = OnetwentyfivekTo150k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( OnefiftykTo175k_Percent_2015 = OnefiftykTo175k_value_2015 / Total_value_2015 ) * 100) %>%
mutate((  One75kTo200k_Percent_2015 =  One75kTo200k_value_2015 / Total_value_2015 ) * 100) %>%
mutate(( Twohundredkto250k_Percent_2015 = Twohundredkto250k_value_2015 / Total_value_2015 ) * 100) %>%
  mutate(( Twofiftykto300k_Percent_2015 = Twofiftykto300k_value_2015 / Total_value_2015 ) * 100) %>%
  mutate(( Threehundredkto400k_Percent_2015 = Threehundredkto400k_value_2015 / Total_value_2015 ) * 100) %>%
  mutate(( Fourhundredkto500k_Percent_2015 = Fourhundredkto500k_value_2015 / Total_value_2015 ) * 100) %>%
  mutate(( Fivehundredkto750k_Percent_2015 = Fivehundredkto750k_value_2015 / Total_value_2015 ) * 100) %>%
  mutate(( Sevenfiftykto1mil_Percent_2015 = Sevenfiftykto1mil_value_2015 / Total_value_2015 ) * 100) %>%
  mutate(( Sevenfiftykto1mil_Percent_2015 = Sevenfiftykto1mil_value_2015 / Total_value_2015 ) * 100) %>%
   mutate(( OnemiltoOnemilhalf_Percent_2015 = OnemiltoOnemilhalf_value_2015 / Total_value_2015 ) * 100) %>%
    mutate(( Onemilhalfto2mil_Percent_2015 = Onemilhalfto2mil_value_2015 / Total_value_2015 ) * 100) %>%
     mutate(( Twomilplus_Percent_2015 = Twomilplus_value_2015 / Total_value_2015 ) * 100)

##Geoid

###Create GEOID of FIPS Code elements
value_geoid_2015 <- paste0( value.pop.2015$state, value.pop.2015$county, value.pop.2015$tract)

value.pop.2015$geoid <- value_geoid_2015


# Number of units

# Occupancy

##2015
### Read csv file with only occupancy variables.
occupancy_vars_2015 <- read.csv("variable_lists/occupancy_vars_2015.csv")

## Warning in read.table(file = file, header = header, sep = sep, quote =
## quote, : incomplete final line found by readTableHeader on 'variable_lists/
## occupancy_vars_2015.csv'

### Create Variable list based off variables in the first column
occupancy.list.age.2015 <- occupancy_vars_2015$name

### Download the data
occupancy.pop.2015 <- getCensus( name = "acs/acs5", vintage = 2015,
                                 key=censuskey,
                               vars = occupancy.list.age.2015,
                               region="tract:*",
                               regionin="state:04&county:013" )

### Rename the variables
occupancy.pop.2015 <- rename(occupancy.pop.2015,
                       Total_occupancy_2015= B25002_001E,
                         occupied_2015= B25002_001E,
                         vacant_2015= B25002_001E)

### Create GEOID of FIPS Code elements
occupancy_geoid_2015 <- paste0( occupancy.pop.2015$state, occupancy.pop.2015$county, occupancy.pop.2015$tract)

occupancy.pop.2015$geoid <- occupancy_geoid_2015

# Vacancy

## 2015 

### Read csv file with only vacancy variables. 
vacancy_vars_2015 <- read.csv("variable_lists/vacancy_vars_2015.csv")

### Create Variable list based off variables in the first column
var.list.vacancy.2015 <- vacancy_vars_2015$name

### Download the data
vacancy.pop.2015 <- getCensus( name = "acs/acs5", vintage = 2015,
                               key=censuskey,
                               vars = var.list.vacancy.2015,
                               region="tract:*",
                               regionin="state:04&county:013" )

## #Rename the variables
vacancy.pop.2015 <- rename(vacancy.pop.2015, Total_vacancy_2015=B25004_001E,
                        For_rent_2015=B25004_002E, 
                        Rented_unoccupied_2015=B25004_003E,
                        Forsale_2015=B25004_004E,
                        Sold_unoccupied_2015=B25004_005E, 
                        Seasonaluse_2015=B25004_006E, 
                        Migrant_workers_2015= B25004_007E,
                       Other_vacant_2015=B25004_008E)

### Create percentages
vacancy.pop.2015 <- vacancy.pop.2015 %>% group_by(tract) %>% 
  mutate((forsale_percent_2015 = Forsale_2015 / Total_vacancy_2015) * 100)

### Create GEOID of FIPS Code elements
vacancy_geoid_2015 <- paste0( vacancy.pop.2015$state, vacancy.pop.2015$county, vacancy.pop.2015$tract)
vacancy.pop.2015$geoid <- vacancy_geoid_2015


# Travel Time
## 2010 

### Read csv file with only travel time to work variables.
traveltime_vars_2010 <- read.csv("variable_lists/traveltime_vars_2010.csv")

### Create Variable list based off variables in the first column
var.list.travel.2010 <- traveltime_vars_2010$name

### Download the data
travel.pop.2010 <- getCensus( name = "acs/acs5", vintage = 2010,
                              key=censuskey,
                               vars = var.list.travel.2010,
                               region="tract:*",
                              regionin="state:04&county:013" )

### Rename the data
travel.pop.2010 <- rename(travel.pop.2010, Total_travel_2010=B08303_001E,
                        Lessthan5_2010=B08303_002E, 
                        Fiveto9_2010=B08303_003E,
                        Tento14_2010=B08303_004E,
                        Fifteento19_2010=B08303_005E, 
                        Twentyto24_2010=B08303_006E, 
                        Twentyfiveto29_2010=B08303_007E,
                       Thirtyto34_2010=B08303_008E,
                       Thirtyfiveto39_2010=B08303_009E,
                       Fortyto44_2010=B08303_010E,
                       Fortyfiveto59_2010=B08303_011E,
                       Sixtyto89_2010=B08303_012E, 
                       Ninetyplus_2010=B08303_013E)

### Create GEOID of FIPS Code elements
travel_geoid_2010 <- paste0( travel.pop.2010$state, travel.pop.2010$county, travel.pop.2010$tract)
travel.pop.2010$geoid <- travel_geoid_2010

##2015

###Read csv file with only travel time to work variables. 
traveltime_vars_2015 <- read.csv("variable_lists/traveltime_vars_2015.csv")

### Create Variable list based off variables in the first column
var.list.travel.2015 <- traveltime_vars_2015$name

### Download the data
travel.pop.2015 <- getCensus( name = "acs/acs5", vintage = 2015,
                              key=censuskey,
                               vars = var.list.travel.2015,
                               region="tract:*",
                              regionin="state:04&county:013" )

###Rename the variables
travel.pop.2015 <- rename(travel.pop.2015, Total_travel_2015=B08303_001E,
                        Lessthan5_2015=B08303_002E, 
                        Fiveto9_2015=B08303_003E,
                        Tento14_2015=B08303_004E,
                        Fifteento19_2015=B08303_005E, 
                        Twentyto24_2015=B08303_006E, 
                        Twentyfiveto29_2015=B08303_007E,
                       Thirtyto34_2015=B08303_008E,
                       Thirtyfiveto39_2015=B08303_009E,
                       Fortyto44_2015=B08303_010E,
                       Fortyfiveto59_2015=B08303_011E,
                       Sixtyto89_2015=B08303_012E, 
                       Ninetyplus_2015=B08303_013E)

### Geoid

### Create GEOID of FIPS Code elements
travel_geoid_2015 <- paste0( travel.pop.2015$state, travel.pop.2015$county, travel.pop.2015$tract)
travel.pop.2015$geoid <- travel_geoid_2015


#Load shapefiles

## Import Shapefile
download.file( "https://github.com/lecy/neighborhood_change_phx/raw/master/shapefiles/tl_2010_04013_tract10.zip", 
"maricopa-az-census_tract10.zip" )
unzip( "maricopa-az-census_tract10.zip" )
file.remove( "maricopa-az-census_tract10.zip" )

## [1] TRUE

library( rgdal )
phx <- readOGR("tl_2010_04013_tract10.shp")

## OGR data source with driver: ESRI Shapefile 
## Source: "/Users/abigailhenderson/Desktop/Capstone/neighborhood_change_phx/data/tl_2010_04013_tract10.shp", layer: "tl_2010_04013_tract10"
## with 916 features
## It has 12 fields
## Integer64 fields read as strings:  ALAND10 AWATER10

phx <- spTransform( phx, CRS("+proj=longlat +datum=WGS84") )

phx$geoid2 <- paste0( "G", phx$STATEFP10, 
                     "0", phx$COUNTYFP10, "0", phx$TRACTCE10 )

# Combine to match geoids
##ACS5
mcpa_educ_2010 <- merge(phx, educ.pop.2010, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_income_2010 <- merge(phx, income.pop.2010, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_value_2010 <- merge(phx, value.pop.2010, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_travel_2010 <- merge(phx, travel.pop.2010, by.x="GEOID10", by.y="geoid", all.x=T)


mcpa_race_2015 <- merge(phx, race.pop.2015, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_educ_2015 <- merge(phx, educ.pop.2015, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_income_2015 <- merge(phx, income.pop.2015, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_occupancy_2015 <- merge(phx, occupancy.pop.2015, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_sex_2015 <- merge(phx, sex.pop.2015, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_vacancy_2015 <- merge(phx, vacancy.pop.2015, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_value_2015 <- merge(phx, value.pop.2015, by.x="GEOID10", by.y="geoid", all.x=T)
mcpa_travel_2015 <- merge(phx, travel.pop.2015, by.x="GEOID10", by.y="geoid", all.x=T)

write.csv( NHGIS_data, "NHGIS_data_rename1", row.names=F)

#Combine above datasets by year
###2010

phx.dat.2010.1 <- merge(educ.pop.2010, income.pop.2010, by.x="geoid", by.y="geoid", all.x=T)

###Checked: nrow 916 consistent, length 23 + 61 = 84

phx.dat.2010.2 <- merge(travel.pop.2010, value.pop.2010, by.x="geoid", by.y="geoid", all.x=T)

###Checked: nrow 916 consistent, length 17 + 30 = 46

phx.dat.2010 <- merge(phx.dat.2010.1, phx.dat.2010.2, by.x="geoid", by.y="geoid", all.x=T)

###Checked: nrow 916 consistent, length 46 + 84 = 128

###2015
phx.dat.2015.1 <- merge(race.pop.2015, educ.pop.2015, by.x="geoid", by.y="geoid", all.x=T)

###Checked: nrow 916 consistent, length 21 + 43 = 63

phx.dat.2015.2 <- merge(occupancy.pop.2015, income.pop.2015, by.x="geoid", by.y="geoid", all.x=T)

###Checked: nrow 916 consistent, length 7 + 23 = 29

phx.dat.2015.3 <- merge(sex.pop.2015, vacancy.pop.2015, by.x="geoid", by.y="geoid", all.x=T)

###Checked: nrow 916 consistent, length 7 + 12 = 18


phx.dat.2015.4 <- merge(travel.pop.2015, value.pop.2015, by.x="geoid", by.y="geoid", all.x=T)

###Checked: nrow 916 consistent, length 7 + 32 = 38

phx.dat.2015.5 <- merge(phx.dat.2015.1, phx.dat.2015.2, by.x="geoid", by.y="geoid", all.x=T)

###Checked: nrow 916 consistent, length 63 + 29 = 91

phx.dat.2015.6 <- merge(phx.dat.2015.3, phx.dat.2015.4, by.x="geoid", by.y="geoid", all.x=T)

###Checked: nrow 916 consistent, length 18 + 38 = 55

phx.dat.2015 <- merge(phx.dat.2015.5, phx.dat.2015.6, by.x="geoid", by.y="geoid", all.x=T, all.y=F)

## Warning in merge.data.frame(phx.dat.2015.5, phx.dat.2015.6, by.x =
## "geoid", : column names '*....x', '*....y' are duplicated in the result

###Checked: nrow 916 consistent, length 55 + 107 = 162

#Combine datasets for 2010 and 2015

phx.dat <- merge(phx.dat.2010, phx.dat.2015, by.x="geoid", by.y="geoid", all.x=T, all.y=F)

## Warning in merge.data.frame(phx.dat.2010, phx.dat.2015, by.x = "geoid", :
## column names '*....x.y', '*....y.y' are duplicated in the result

write.csv( phx.dat, "phx.dat.csv", row.names=F)

###Checked: nrow 916 consistent, length 128 + 161 = 288

#Combine ACS 5 datasets with NHGIS data

phx.dat$geoid3 <- paste0( "G", phx$STATEFP10, 
                     "0", phx$COUNTYFP10, "0", phx$TRACTCE10 )


phx.combined.data <- merge(NHGIS_data, phx.dat, by.x="GISJOIN", by.y="geoid3", all.x=T, all.y=F)

## Warning in merge.data.frame(NHGIS_data, phx.dat, by.x = "GISJOIN", by.y
## = "geoid3", : column names '*....x.y', '*....y.y' are duplicated in the
## result

write.csv( phx.combined.data, "phx.combined.data.csv", row.names=F)

###Checked: nrow 916 consistent, length 330 + 288 = 618

#Merge the combined dataset with the shapefile
phx.shape.data <- merge(phx, phx.combined.data, by.x="geoid2", by.y="GISJOIN", all.x=T)

#Convert large data file into GeoJson & write as GeoJson in shapefiles folder

geojson_write( phx.shape.data, file = "../shapefiles/phx.geojson" )

## Success! File is at ../shapefiles/phx.geojson

## <geojson-file>
##   Path:       ../shapefiles/phx.geojson
##   From class: SpatialPolygonsDataFrame

#Convert to tidy data

url <- "https://raw.githubusercontent.com/lecy/neighborhood_change_phx/master/data/archive/phx.dashboard.dat.csv"
dat <- read.csv( url, stringsAsFactors=F )

dat <- gather(  dat, "var_name", "value", 5:71 )

dat <- separate( dat, var_name, c("level", "year")  )

write.csv(dat, "tidy.dashboard.dat.csv", row.names=F)

#Convert shapefile to a dataframe for ggplot maps

library(broom)
phx_fortified <- tidy( phx, region = "geoid2")

## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector

library(ggplot2)

library(mapproj)

ggplot() +
  geom_polygon( data = phx_fortified, aes( x = long, y = lat, group = group ), col="gray" ) +
  theme_void() +
  coord_map()

library( dplyr)


phx.tidy <- merge( phx_fortified, phx.combined.data, by.x="id", by.y="GISJOIN", all.x=T)

ggplot( data = phx.tidy, 
               aes( x = long, y = lat, group = group, fill = Asian_2000 ) ) + 
  geom_polygon() +
  coord_map()

write_rds( phx.tidy, “../data/raw/phx.tidy.rds”, compress= “none”)

# Static Maps for each variable
##Ethnicity
hispanic_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, 
                    fill = Hispanic.Latino1990 ) ) + 
                geom_polygon() +
               coord_map() +
               scale_fill_distiller(palette="Set3", direction=1,
                                    name="Population") +
     labs(title="Hispanic/Latino1990 Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

hispanic_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=Hispanic.Latino2000)) +
  geom_polygon() +
               coord_map() +
     scale_fill_distiller(palette="Set3", direction=1, name="Population") +
     labs(title="Hispanic/Latino2000 Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

hispanic_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=Hispanic.Latino2010)) +
  geom_polygon() +
               coord_map() +
     scale_fill_distiller(palette="Set3", direction=1, name="Population") +
     labs(title="Hispanic/Latino2010 Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")



not_hispanic_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=NotHispanic.Latino_1990)) +
  geom_polygon() +
               coord_map() +
     scale_fill_distiller(palette="Set3", direction=1, name="Population") +
     labs(title="Not Hispanic/Latino1990 Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

 not_hispanic_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=NotHispanic.Latino_2000)) +
  geom_polygon() +
               coord_map() +
     scale_fill_distiller(palette="Set3", direction=1, name="Population") +
     labs(title="Not Hispanic/Latino2000 Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

not_hispanic_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
NotHispanic.Latino_2010)) +
  geom_polygon() +
               coord_map() +
     scale_fill_distiller(palette="Accent", direction=1, name="Population") +
     labs(title="Not Hispanic/Latino2010 Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

hispanic_2015 <- 
ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Hispanic_2015)) +
  geom_polygon() +
               coord_map() +
  scale_fill_distiller(palette="YlGn", direction=1, name="Population") +
  labs(title="Hispanic Population", title.cex=0.5, caption="2015 Source: US Census")

not_hispanic_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Not_hispanic_2015)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="YlGn", direction=1, name="Population") +
  labs(title="Adult Females", title.cex=0.5, caption="2015 Source: US Census")

##Sex

male_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Male_1990)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Male Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

male_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Male_2000)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Male Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

male_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Male_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Male Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

female_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Female_1990)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Female Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

female_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Female_2000)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Female Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

female_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Female_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Female Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

male_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Male_2015)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PiYG", direction=1, name="Population") +
  labs(title="Adult Males", title.cex=0.5, caption="2015 Source: US Census")

female_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Female_2015)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PiYG", direction=1, name="Population") +
  labs(title="Adult Females", title.cex=0.5, caption="2015 Source: US Census")

##Race

#white
white_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
White_1990)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Set1", direction=1, name="Population") +
     labs(title="White 1990 Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

white_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
White_2000)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Set1", direction=1, name="Population") +
     labs(title="White 2000 Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

white_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
White_2010)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Set1", direction=1, name="Population") +
     labs(title="White 2010 Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

#Black.AA

black_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Black_AA_1990)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
     labs(title="Black/African American1990 Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

black_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Black_AA_2000)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
     labs(title="Black/African American2000 Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

black_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Black_AA_2010)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
     labs(title="Black/African American2010 Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

# NativeAm_Alaskan Maps

native_american_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
NativeAm_Alaskan1990)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdGy", direction=1, name="Population") +
     labs(title="NativeAm_Alaskan1990 Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

native_american_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
NativeAm_Alaskan2000)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdGy", direction=1, name="Population") +
     labs(title="NativeAm_Alaskan2000 Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

native_american_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
NativeAm_Alaskan2010)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdGy", direction=1, name="Population") +
     labs(title="NativeAm_Alaskan2010 Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

# Asian

asian_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Asian_1990)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Paired", direction=1, name="Population") +
     labs(title="Asian1990 Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

asian_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Asian_2000)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Paired", direction=1, name="Population") +
     labs(title="Asian2000 Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

asian_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Asian_2010)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Paired", direction=1, name="Population") +
     labs(title="Asian2010 Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

# NativeHawaiian.PacificIslander

pacific_islander_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
NativeHawaiian.PacificIslander_1990)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="BrBG", direction=1, name="Population") +
     labs(title="NativeHawaiian.PacificIslander_1990 Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

pacific_islander_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
NativeHawaiian.PacificIslander_2000)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="BrBG", direction=1, name="Population") +
     labs(title="NativeHawaiian.PacificIslander_2000 Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

pacific_islander_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
NativeHawaiian.PacificIslander_2010)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="BrBG", direction=1, name="Population") +
     labs(title="NativeHawaiian.PacificIslander_2010 Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

# SomeOther Variable

some_other_race_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SomeOther_1990)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="PiYG", direction=1, name="Population") +
     labs(title="SomeOther_1990 Population in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

some_other_race_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SomeOther_2000)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="PiYG", direction=1, name="Population") +
     labs(title="SomeOther_2000 Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

some_other_race_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SomeOther_2010)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="PiYG", direction=1, name="Population") +
     labs(title="SomeOther_2010 Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

# Two or More Races Variable

# Data not available for 1990

tworaces_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Two.OrMore_2000)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdBu", direction=1, name="Population") +
     labs(title="Two Or More Races 2000 Population in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

tworaces_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Two.OrMore_2010)) +
  geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdBu", direction=1, name="Population") +
     labs(title="Two Or More Races 2010 Population in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

white_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
White_2015)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="White", caption="2015 Source: US Census")

black_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Black_2015)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Black", caption="2015 Source: US Census")

native_american_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
American_Indian_2015)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Native American", caption="2015 Source: US Census")

asian_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Asian_2015)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Asian", caption="2015 Source: US Census")

pacific_islander_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Pacific_Islander_2015)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Hawaiian or Pacific Islander", caption="2015 Source: US Census")

other_race_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Other_Race_2015)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Other Race", caption="2015 Source: US Census")

##Education


###2010
noschool_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
NoSchool_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="No School", caption="2015 Source: US Census")


lessthanninth_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
LessThanNinth_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="Less than a Ninth Grade Education", caption="2015 Source: US Census")


ninthgrade_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Ninthgrade_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A 9th Grade Education", caption="2015 Source: US Census")

tenthgrade_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Tenthgrade_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A 10th Grade Education", caption="2015 Source: US Census")

eleventhgrade_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Eleventhgrade_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="An 11th Grade Education", caption="2015 Source: US Census")

twelfthgrade_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Twelfthgrade_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A 12th Grade Education- No Diploma", caption="2015 Source: US Census")


hsdiploma_ged_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HSDiploma_GED_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A High School Diploma or GED", caption="2015 Source: US Census")


somecollege_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SomeCollege_2010)) +
  geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="Some College but No Degree", caption="2015 Source: US Census")
  
aa_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
AA_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="An AA Degree", caption="2015 Source: US Census")


ba_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
BA_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A Bachelor's Degree", caption="2015 Source: US Census")

masters_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Masters_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A Master's Degree", caption="2015 Source: US Census")


profschool_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ProfSchool_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A Professional Degree", caption="2015 Source: US Census")

doctoral_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill= Doctoral_2010)) + 
                geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A Doctoral Degree", caption="2015 Source: US Census")

hs_above_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
hs_above_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A Professional Degree", caption="2015 Source: US Census")

###2015

noschool_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
No_school_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="No Schooling", caption="2015 Source: US Census")

lessthanninth_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
LessThanNinth_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="Less than a Ninth Grade Education", caption="2015 Source: US Census")

ninthgrade_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Ninthgrade_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A 9th Grade Education", caption="2015 Source: US Census")

tenthgrade_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Tenthgrade_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A 10th Grade Education", caption="2015 Source: US Census")

eleventhgrade_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Eleventhgrade_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="An 11th Grade Education", caption="2015 Source: US Census")

twelfthgrade_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Twelfthgrade_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A 12th Grade Education- No Diploma", caption="2015 Source: US Census")

hs_above_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
hs_above_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A High School Diploma or Above", caption="2015 Source: US Census")


hsdiploma_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HSdiploma_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A High School Diploma", caption="2015 Source: US Census")

ged_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
GED_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A GED", caption="2015 Source: US Census")


somecollege_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SomeCollege_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="Some College but No Degree", caption="2015 Source: US Census")
  
aa_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
AA_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="An AA Degree", caption="2015 Source: US Census")


ba_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Bachelors_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A Bachelor's Degree", caption="2015 Source: US Census")

masters_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Masters_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A Master's Degree", caption="2015 Source: US Census")


profschool_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ProfSchool_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A Professional Degree", caption="2015 Source: US Census")

doctoral_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Doctoral_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Greens", direction=1, name="Population") +
  labs(title="A Doctoral Degree", caption="2015 Source: US Census")

##Income

###2010

belowpoverty_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill= belowpoverty_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Households Below the Poverty Line", title.cex=0.5, caption="2010 Source: US Census")

belowpoverty_percent_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill= belowpoverty_percent_2010)) +
  geom_polygon() + coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Percent of Households Below the Poverty Line", title.cex=0.5, caption="2010 Source: US Census")


lessthan10k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Lessthan10k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Less than $10k", title.cex=0.5, caption="2010 Source: US Census")

tenkto14k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Tento14k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $10,000 and $14,999", title.cex=0.5, caption="2010 Source: US Census")

fifteenkto20k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fifteenkto20k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $15,000 and $19,999", title.cex=0.5, caption="2010 Source: US Census")

twentykto25k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwentykTo25k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $20,000 and $24,999", title.cex=0.5, caption="2010 Source: US Census")

twentfivekto30k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwentyfivekTo30k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $25,000 and $29,999", title.cex=0.5, caption="2010 Source: US Census")

thirtykto35k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ThirtykTo35k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $30,000 and $34,999", title.cex=0.5, caption="2010 Source: US Census")

thirtyfivekto40k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ThirtyfivekTo40k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $35,000 and $39,999", title.cex=0.5, caption="2010 Source: US Census")

fortyktofortyfivek_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FortykTo45k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $40,000 and $44,999", title.cex=0.5, caption="2010 Source: US Census")

fortyfivekto50k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FortyfivekTo50k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $45,000 and $49,999", title.cex=0.5, caption="2010 Source: US Census")

fiftykto60k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FiftykTo60k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $50,000 and $59,999", title.cex=0.5, caption="2010 Source: US Census")

sixtykto75k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SixtykTo75k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $60,000 and $74,999", title.cex=0.5, caption="2010 Source: US Census")

seventyfivekto100k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SeventyfivekTo100k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $75,000 and $99,999", title.cex=0.5, caption="2010 Source: US Census")


onehundredkto125k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnehundredkTo125k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $100,000 and $124,999", title.cex=0.5, caption="2010 Source: US Census")


onetwentyfivekto150k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnetwentyfivekTo150k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $125,000 and $149,999", title.cex=0.5, caption="2010 Source: US Census")
  
onefiftykto200k_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnefiftykTo200k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $150,000 and $199,999", title.cex=0.5, caption="2010 Source: US Census")


twohundredkplus_income_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwohundredkPlus_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="$200,000 and Above", title.cex=0.5, caption="2010 Source: US Census")

###2015

belowpoverty_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill= belowpoverty_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Households Below the Poverty Line", title.cex=0.5, caption="2010 Source: US Census")

belowpoverty_percent_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill= belowpoverty_percent_2015)) +
      geom_polygon() + coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Percent of Households Below the Poverty Line", title.cex=0.5, caption="2010 Source: US Census")

lessthan10k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Lessthan10k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Less than $10k", title.cex=0.5, caption="2015 Source: US Census")

tenkto14k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Tento14k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $10,000 and $14,999", title.cex=0.5, caption="2015 Source: US Census")

fifteenkto20k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fifteenkto20k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $15,000 and $19,999", title.cex=0.5, caption="2015 Source: US Census")

twentykto25k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwentykTo25k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $20,000 and $24,999", title.cex=0.5, caption="2015 Source: US Census")

twentfivekto30k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwentyfivekTo30k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $25,000 and $29,999", title.cex=0.5, caption="2015 Source: US Census")

thirtykto35k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ThirtykTo35k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $30,000 and $34,999", title.cex=0.5, caption="2015 Source: US Census")

thirtyfivekto40k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ThirtyfivekTo40k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $35,000 and $39,999", title.cex=0.5, caption="2015 Source: US Census")

fortyktofortyfivek_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FortykTo45k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $40,000 and $44,999", title.cex=0.5, caption="2015 Source: US Census")

fortyfivekto50k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FortyfivekTo50k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $45,000 and $49,999", title.cex=0.5, caption="2015 Source: US Census")

fiftykto60k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FiftykTo60k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $50,000 and $59,999", title.cex=0.5, caption="2015 Source: US Census")

sixtykto75k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SixtykTo75k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $60,000 and $74,999", title.cex=0.5, caption="2015 Source: US Census")

seventyfivekto100k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SeventyfivekTo100k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $75,000 and $99,999", title.cex=0.5, caption="2015 Source: US Census")


onehundredkto125k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnehundredkTo125k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $100,000 and $124,999", title.cex=0.5, caption="2015 Source: US Census")

onetwentyfivekto150k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnetwentyfivekTo150k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $125,000 and $149,999", title.cex=0.5, caption="2015 Source: US Census")
  
onefiftykto200k_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnefiftykTo200k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="Between $150,000 and $199,999", title.cex=0.5, caption="2015 Source: US Census")


twohundredkplus_income_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwohundredkPlus_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Purples", direction=1, name="Population") +
  labs(title="$200,000 and Above", title.cex=0.5, caption="2015 Source: US Census")

##Value

lessthan10k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
 Lessthan10k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Less than $10k", title.cex=0.5, caption="2010 Source: US Census")

tenkto14k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TenkTo14k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $10,000 and $14,000", title.cex=0.5, caption="2010 Source: US Census")

fifteenkto20k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fifteenkto20k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $15,000 and $20,000", title.cex=0.5, caption="2010 Source: US Census")

twentykto25k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwentykTo25k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $20,000 and $25,000", title.cex=0.5, caption="2010 Source: US Census")

twentyfivekto30k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwentyfivekTo30k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $25,000 and $30,000", title.cex=0.5, caption="2010 Source: US Census")

thirtykto35k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ThirtykTo35k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $30,000 and $35,000", title.cex=0.5, caption="2010 Source: US Census")

thirtyfivekto40k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ThirtyfivekTo40k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $35,000 and $40,000", title.cex=0.5, caption="2010 Source: US Census")

fortykto50k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FortykTo50k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $40,000 and $50,000", title.cex=0.5, caption="2010 Source: US Census")
  
fiftykto60k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FiftykTo60k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $50,000 and $60,000", title.cex=0.5, caption="2010 Source: US Census")

sixtykto70k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SixtykTo70k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $60,000 and $70,000", title.cex=0.5, caption="2010 Source: US Census")
  
seventykto80k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SeventykTo80k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $70,000 and $80,000", title.cex=0.5, caption="2010 Source: US Census")
  
eightykto90k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Eightykto90k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $80,000 and $90,000", title.cex=0.5, caption="2010 Source: US Census")
  
ninetykto100k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Ninetykto100k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $90,000 and $100,000", title.cex=0.5, caption="2010 Source: US Census")
  
onehundredkto125k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnehundredkTo125k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $100,000 and $125,000", title.cex=0.5, caption="2010 Source: US Census")
  
onetwentyfivekto150k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnetwentyfivekTo150k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $125,000 and $150,000", title.cex=0.5, caption="2010 Source: US Census")
  
onefiftykto175k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnefiftykTo175k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $150,000 and $175,000", title.cex=0.5, caption="2010 Source: US Census")
  
oneseventyfivekto200k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
One75kTo200k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $175,000 and $200,000", title.cex=0.5, caption="2010 Source: US Census")
 
twohundredkto250k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill= 
                      Twohundredkto250k_value_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $200,000 and $250,000", title.cex=0.5, caption="2010 Source: US Census")
  
twofiftykto300k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Twofiftykto300k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $250,000 and $300,000", title.cex=0.5, caption="2010 Source: US Census")
  
threehundredkto400k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Threehundredkto400k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $300,000 and $400,000", title.cex=0.5, caption="2010 Source: US Census")
  
fourhundredkto500k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fourhundredkto500k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $400,000 and $500,000", title.cex=0.5, caption="2010 Source: US Census")
  
fivehundredkto750k_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fivehundredkto750k_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $500,000 and $750,000", title.cex=0.5, caption="2010 Source: US Census")

seventyfiftykto1mil_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Sevenfiftykto1mil_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $750,000 and $1,000,000", title.cex=0.5, caption="2010 Source: US Census")

onemilplus_value_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnemilPlus_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Over $1,000,000", title.cex=0.5, caption="2010 Source: US Census")



lessthan10k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
 Lessthan10k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Less than $10k", title.cex=0.5, caption="2015 Source: US Census")

tenkto14k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TenkTo14k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $10,000 and $14,000", title.cex=0.5, caption="2015 Source: US Census")

fifteenkto20k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fifteenkto20k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $15,000 and $20,000", title.cex=0.5, caption="2015 Source: US Census")

twentykto25k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwentykTo25k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $20,000 and $25,000", title.cex=0.5, caption="2015 Source: US Census")

twentyfivekto30k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
TwentyfivekTo30k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $25,000 and $30,000", title.cex=0.5, caption="2015 Source: US Census")

thirtykto35k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ThirtykTo35k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $30,000 and $35,000", title.cex=0.5, caption="2015 Source: US Census")

thirtyfivekto40k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
ThirtyfivekTo40k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $35,000 and $40,000", title.cex=0.5, caption="2015 Source: US Census")

fortykto50k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FortykTo50k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $40,000 and $50,000", title.cex=0.5, caption="2015 Source: US Census")
  
fiftykto60k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
FiftykTo60k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $50,000 and $60,000", title.cex=0.5, caption="2015 Source: US Census")

sixtykto70k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SixtykTo70k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $60,000 and $70,000", title.cex=0.5, caption="2015 Source: US Census")
  
seventykto80k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
SeventykTo80k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $70,000 and $80,000", title.cex=0.5, caption="2015 Source: US Census")
  
eightykto90k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Eightykto90k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $80,000 and $90,000", title.cex=0.5, caption="2015 Source: US Census")
  
ninetykto100k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Ninetykto100k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $90,000 and $100,000", title.cex=0.5, caption="2015 Source: US Census")
  
onehundredkto125k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnehundredkTo125k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $100,000 and $125,000", title.cex=0.5, caption="2015 Source: US Census")
  
onetwentyfivekto150k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnetwentyfivekTo150k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $125,000 and $150,000", title.cex=0.5, caption="2015 Source: US Census")
  
onefiftykto175k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnefiftykTo175k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $150,000 and $175,000", title.cex=0.5, caption="2015 Source: US Census")
  
oneseventyfivekto200k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
One75kTo200k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $175,000 and $200,000", title.cex=0.5, caption="2015 Source: US Census")
 
twohundredkto250k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
                      Twohundredkto250k_value_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $200,000 and $250,000", title.cex=0.5, caption="2015 Source: US Census")
  
twofiftykto300k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Twofiftykto300k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $250,000 and $300,000", title.cex=0.5, caption="2015 Source: US Census")
  
threehundredkto400k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Threehundredkto400k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $300,000 and $400,000", title.cex=0.5, caption="2015 Source: US Census")
  
fourhundredkto500k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fourhundredkto500k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $400,000 and $500,000", title.cex=0.5, caption="2015 Source: US Census")
  
fivehundredkto750k_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fivehundredkto750k_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $500,000 and $750,000", title.cex=0.5, caption="2015 Source: US Census")

sevenfiftykto1mil_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Sevenfiftykto1mil_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $750,000 and $1,000,000", title.cex=0.5, caption="2015 Source: US Census")

onemilto1.5mil_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
OnemiltoOnemilhalf_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $1,000,000 and $1,500,000", title.cex=0.5, caption="2015 Source: US Census")

oneandahalfmilto2mil_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Onemilhalfto2mil_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Between $1,500,000 and $2,000,000", title.cex=0.5, caption="2015 Source: US Census")
  
twomilplus_value_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Twomilplus_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="BuGn", direction=1, name="Population") +
  labs(title="Over $2,000,000", title.cex=0.5, caption="2015 Source: US Census")

##Units

housingunits_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdBu", direction=1, name="Population") +
     labs(title="Housing Units 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

housingunits_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdBu", direction=1, name="Population") +
     labs(title="Housing Units 2000 in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

housingunits_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdBu", direction=1, name="Population") +
     labs(title="Housing Units 2010 in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

##Occupancy

occupied_units_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_Occupied_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Pastel2", direction=1, name="Population") +
     labs(title="Occupied Housing Units 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

occupied_units_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_Occupied_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Pastel2", direction=1, name="Population") +
     labs(title="Occupied Housing Units 2000 in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

occupied_units_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_Occupied_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Pastel2", direction=1, name="Population") +
     labs(title="Occupied Housing Units 2010 in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

vacant_units_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_Vacant_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Pastel1", direction=1, name="Population") +
     labs(title="Vacant Housing Units 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

vacant_units_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_Vacant_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Pastel1", direction=1, name="Population") +
     labs(title="Vacant Housing Units 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

vacant_units_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_Vacant_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Pastel1", direction=1, name="Population") +
     labs(title="Vacant Housing Units 2000 in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

vacant_units_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
HousingUnits_Vacant_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Pastel1", direction=1, name="Population") +
     labs(title="Vacant Housing Units 2010 in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

occupied_units_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
occupied_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="RdYlBu", direction=1, name="Population") +
  labs(title="Occupied Homes", title.cex=0.5, caption="2015 Source: US Census")

vacant_units_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
vacant_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="RdYlBu", direction=1, name="Population") +
  labs(title="Vacant Homes", title.cex=0.5, caption="2015 Source: US Census")

##Vacancy

forrent_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_ForRent_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant For Rent Housing Unit 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

forrent_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_ForRent_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant For Rent Housing Unit 2000 in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

forrent_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_ForRent_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant For Rent Housing Unit 2010 in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

forsale_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_ForSale_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant For Sale Housing Unit 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

forsale_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_ForSale_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdYlGn", direction=1, name="Population") +
     labs(title="Vacant For Sale Housing Unit 2000 in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

forsale_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_ForSale_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdYlGn", direction=1, name="Population") +
     labs(title="Vacant For Sale Housing Unit 2010 in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

forsale_percent_1990 <-ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
forsale_percent_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdYlGn", direction=1, name="Population") +
     labs(title="Percentage of Homes for Sale in 1990", title.cex=.75, caption="1990 Source: US Census, NHGIS")

forsale_percent_2000 <-ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
forsale_percent_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdYlGn", direction=1, name="Population") +
     labs(title="Percentage of Homes for Sale in 2000", title.cex=.75, caption="2000 Source: US Census, NHGIS")

forsale_percent_2010 <-ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
forsale_percent_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdYlGn", direction=1, name="Population") +
     labs(title="Percentage of Homes for Sale in 2010", title.cex=.75, caption="2010 Source: US Census, NHGIS")

forsale_percent_2015 <-ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
forsale_percent_2015)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="RdYlGn", direction=1, name="Population") +
     labs(title="Percentage of Homes for Sale in 2015", title.cex=.75, caption="2010 Source: US Census, ACS 5")

rentedorsold_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_RentedOrSold_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Rented Or Sold 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

rentedorsold_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_RentedOrSold_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Rented Or Sold 2000 in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

rentedorsold_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_RentedOrSold_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Rented Or Sold 2010 in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

occasionaluse_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_OccasionalUse_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Occasional Use 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

occasionaluse_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_OccasionalUse_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Occasional Use 2000 in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

occasionaluse_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_OccasionalUse_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Occasional Use 2010 in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

migrantworkers_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_MigrantWorkers_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Migrant Workers 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

migrantworkers_2000 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_MigrantWorkers_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Migrant Workers 2000 in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

migrantworkers_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_MigrantWorkers_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Migrant Workers 2010 in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")

vacant_other_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_Other_1990)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Other 1990 in Maricopa County", title.cex=.75, caption="1990 Source: US Census, NHGIS")

vacant_other_1990 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_Other_2000)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Other 2000 in Maricopa County", title.cex=.75, caption="2000 Source: US Census, NHGIS")

vacant_other_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Vacant_Other_2010)) + geom_polygon() +  coord_map() +
     scale_fill_distiller(palette="Dark2", direction=1, name="Population") +
     labs(title="Vacant Other 2010 in Maricopa County", title.cex=.75, caption="2010 Source: US Census, NHGIS")


forrent_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
For_rent_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="For Rent", title.cex=0.5, caption="2015 Source: US Census")

rented_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Rented_unoccupied_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Rented but Unoccupied", title.cex=0.5, caption="2015 Source: US Census")

forsale_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Forsale_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="RdYlGn", direction=1, name="Population") +
  labs(title="For Sale", title.cex=0.5, caption="2015 Source: US Census")

sold_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Sold_unoccupied_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Sold but Unoccupied", title.cex=0.5, caption="2015 Source: US Census")

seasonal_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Seasonaluse_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Reserved for seasonal or recreational use", title.cex=0.5, caption="2015 Source: US Census")

migrantworkers_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Migrant_workers_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Housing reserved for migrant workers", title.cex=0.5, caption="2015 Source: US Census")

vacant_other_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Other_vacant_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="Oranges", direction=1, name="Population") +
  labs(title="Vacant for some other reason", title.cex=0.5, caption="2015 Source: US Census")

##Travel Time

###2010

travel_lessthan5_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Lessthan5_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Less than 5 minutes", title.cex=0.5, caption="2010 Source: US Census")

travel_5to9_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fiveto9_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 5 and 9 minutes", title.cex=0.5, caption="2010 Source: US Census")

travel_10to14_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Tento14_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 10 and 14 minutes", title.cex=0.5, caption="2010 Source: US Census")

travel_15to19_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fifteento19_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 15 and 19 minutes", title.cex=0.5, caption="2010 Source: US Census")

travel_20to24_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Twentyto24_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 20 and 24 minutes", title.cex=0.5, caption="2010 Source: US Census")

travel_25to29_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Twentyfiveto29_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 25 and 29 minutes", title.cex=0.5, caption="2010 Source: US Census")

travel_30to34_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Thirtyto34_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 30 and 34 minutes", title.cex=0.5, caption="2010 Source: US Census")


travel_35to39_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Thirtyfiveto39_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 35 and 39 minutes", title.cex=0.5, caption="2010 Source: US Census")

travel_40to44_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fortyto44_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 40 and 44 minutes", title.cex=0.5, caption="2010 Source: US Census")

travel_45to59_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fortyfiveto59_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 45 to 59 minutes", title.cex=0.5, caption="2010 Source: US Census")
  
  travel_60to89_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Sixtyto89_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 60 and 89 minutes", title.cex=0.5, caption="2010 Source: US Census")
  
  travel_90plus_2010 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Ninetyplus_2010)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Over 90 minutes", title.cex=0.5, caption="2010 Source: US Census")


###2015 

travel_lessthan5_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Lessthan5_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Less than 5 minutes", title.cex=0.5, caption="2015 Source: US Census")

travel_5to9_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
 Fiveto9_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 5 and 9 minutes", title.cex=0.5, caption="2015 Source: US Census")

travel_10to14_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Tento14_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 10 and 14 minutes", title.cex=0.5, caption="2015 Source: US Census")

travel_15to19_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fifteento19_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 15 and 19 minutes", title.cex=0.5, caption="2015 Source: US Census")

travel_20to24_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Twentyto24_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 20 and 24 minutes", title.cex=0.5, caption="2015 Source: US Census")

travel_25to29_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
 Twentyfiveto29_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 25 and 29 minutes", title.cex=0.5, caption="2015 Source: US Census")

travel_30to34_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Thirtyto34_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 30 and 34 minutes", title.cex=0.5, caption="2015 Source: US Census")

travel_35to39_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Thirtyfiveto39_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 35 and 39 minutes", title.cex=0.5, caption="2015 Source: US Census")

travel_40to44_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Fortyto44_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 40 and 44 minutes", title.cex=0.5, caption="2015 Source: US Census")

travel_45to59_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
 Fortyfiveto59_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 45 to 59 minutes", title.cex=0.5, caption="2015 Source: US Census")
  
  travel_60to89_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Sixtyto89_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Between 60 and 89 minutes", title.cex=0.5, caption="2015 Source: US Census")

  
  travel_90plus_2015 <- ggplot( data = phx.tidy, 
               aes( x = long, y = lat, 
                    group = group, fill=
Ninetyplus_2015)) + geom_polygon() +  coord_map() +
  scale_fill_distiller(palette="PuOr", direction=1, name="Population") +
  labs(title="Over 90 minutes", title.cex=0.5, caption="2015 Source: US Census")