HW 2
Adrian Gallegos
2024-09-29
library(tidycensus)
library(ggplot2)
library(writexl)
census_api_key("4156b3413d433f2f6803ff4b60faa2a8bb579da2", overwrite = "TRUE")## To install your API key for use in future sessions, run this function with `install = TRUE`.TX <- get_decennial(geography = "tract", variables = 'P013002', year = 2010,
state = "TX", geometry = TRUE) ## Getting data from the 2010 decennial Census## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.## Using Census Summary File 1## | | | 0% | | | 1% | |= | 1% | |= | 2% | |== | 2% | |== | 3% | |=== | 4% | |=== | 5% | |==== | 5% | |==== | 6% | |===== | 7% | |====== | 8% | |====== | 9% | |======= | 10% | |======== | 11% | |======== | 12% | |========= | 13% | |========== | 14% | |========== | 15% | |=========== | 16% | |============ | 17% | |============= | 18% | |============= | 19% | |============== | 20% | |=============== | 21% | |=============== | 22% | |================ | 23% | |================= | 24% | |================= | 25% | |================== | 25% | |================== | 26% | |=================== | 27% | |==================== | 28% | |==================== | 29% | |===================== | 29% | |===================== | 30% | |====================== | 31% | |====================== | 32% | |======================= | 32% | |======================= | 33% | |======================== | 35% | |========================= | 35% | |========================= | 36% | |========================== | 37% | |========================== | 38% | |=========================== | 38% | |=========================== | 39% | |============================ | 40% | |============================= | 41% | |============================= | 42% | |============================== | 42% | |============================== | 43% | |=============================== | 44% | |=============================== | 45% | |================================ | 45% | |================================ | 46% | |================================= | 47% | |================================== | 48% | |================================== | 49% | |=================================== | 50% | |=================================== | 51% | |==================================== | 51% | |==================================== | 52% | |===================================== | 53% | |====================================== | 54% | |====================================== | 55% | |======================================= | 55% | |======================================= | 56% | |======================================== | 57% | |======================================== | 58% | |========================================= | 58% | |========================================= | 59% | |========================================== | 60% | |=========================================== | 61% | |=========================================== | 62% | |============================================ | 62% | |============================================ | 63% | |============================================= | 64% | |============================================== | 66% | |=============================================== | 67% | |================================================================ | 92% | |================================================================= | 93% | |================================================================== | 94% | |================================================================== | 95% | |=================================================================== | 95% | |=================================================================== | 96% | |==================================================================== | 97% | |==================================================================== | 98% | |===================================================================== | 98% | |===================================================================== | 99% | |======================================================================| 100%write_xlsx(x = TX, path = "C:/Users/adrian.gallegos/OneDrive - BASIS.ed/Desktop/FALL UTSA/HW2/TX_Med_Age_M_2010_Decennial.xlsx", col_names = TRUE)
texas_bexar_medincome <- get_acs(geography = "tract", variables = "B19013_001E",
state = "TX", county = "Bexar", output="wide", geometry = TRUE, year = 2018) ## Getting data from the 2014-2018 5-year ACS## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.## | | | 0% | |= | 1% | |= | 2% | |== | 3% | |=== | 4% | |==== | 5% | |==== | 6% | |===== | 7% | |===== | 8% | |====== | 8% | |====== | 9% | |======= | 9% | |======= | 10% | |======= | 11% | |======== | 11% | |======== | 12% | |========= | 12% | |========= | 13% | |========== | 14% | |========== | 15% | |=========== | 15% | |=========== | 16% | |============ | 16% | |============ | 17% | |============ | 18% | |============= | 18% | |============= | 19% | |============== | 20% | |=============== | 21% | |=============== | 22% | |================ | 22% | |================ | 23% | |================= | 24% | |================= | 25% | |================== | 25% | |================== | 26% | |=================== | 27% | |=================== | 28% | |==================== | 28% | |==================== | 29% | |===================== | 29% | |===================== | 30% | |====================== | 31% | |====================== | 32% | |======================= | 32% | |======================= | 33% | |======================== | 34% | |======================== | 35% | |========================= | 35% | |========================= | 36% | |====================================== | 55% | |============================================ | 63% | |============================================= | 64% | |============================================== | 65% | |============================================== | 66% | |=============================================== | 67% | |=============================================== | 68% | |================================================ | 68% | |================================================ | 69% | |================================================= | 70% | |================================================== | 71% | |================================================== | 72% | |=================================================== | 73% | |==================================================== | 74% | |==================================================== | 75% | |===================================================== | 76% | |====================================================== | 77% | |====================================================== | 78% | |======================================================= | 78% | |======================================================= | 79% | |======================================================== | 79% | |======================================================== | 80% | |========================================================= | 81% | |========================================================= | 82% | |========================================================== | 82% | |========================================================== | 83% | |=========================================================== | 84% | |=========================================================== | 85% | |============================================================ | 85% | |============================================================ | 86% | |============================================================= | 87% | |============================================================== | 88% | |============================================================== | 89% | |=============================================================== | 90% | |================================================================ | 91% | |================================================================ | 92% | |================================================================= | 92% | |================================================================= | 93% | |================================================================== | 94% | |================================================================== | 95% | |=================================================================== | 95% | |=================================================================== | 96% | |==================================================================== | 97% | |==================================================================== | 98% | |===================================================================== | 98% | |===================================================================== | 99% | |======================================================================| 100%hispanic_pop_TX <- get_acs(geography = "county", variables = "B03002_012E",
state = "TX" , output="wide", year = 2018, geometry = TRUE)## Getting data from the 2014-2018 5-year ACS
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|===================================================================== | 99% | |======================================================================| 99% | |======================================================================| 100%names(hispanic_pop_TX)[3] <- "HispanicPop"
names(hispanic_pop_TX)## [1] "GEOID" "NAME" "HispanicPop" "B03002_012M" "geometry"ggplot(hispanic_pop_TX, aes(y = HispanicPop)) +
geom_boxplot()
texas_bexar_poverty <- get_acs(geography = "tract", variables = "B17017_002E",
state = "TX", county = "Bexar", output="wide", geometry = TRUE, year = 2018) ## Getting data from the 2014-2018 5-year ACS
## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.var <- c(hispanic='B03002_012E',
white='B03002_003E',
black='B03002_004E')
texas_bexar_hispanic_white_black <- get_acs(geography = "tract", variables = var,
state = "TX", county = "Bexar", output="wide", geometry = TRUE, year = 2018) ## Getting data from the 2014-2018 5-year ACS
## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.var2 <- c(poptotal='B03002_001E',
hispanic='B03002_012E',
white='B03002_003E',
black='B03002_004E',
poptotal2='B17017_001E',
poverty='B17017_002E')
texas_bexar_ethnicity_poverty <- get_acs(geography = "tract", variables = var2,
state = "TX", county = "Bexar", output="wide", geometry = TRUE, year = 2018) ## Getting data from the 2014-2018 5-year ACS
## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.texas_bexar_ethnicity_poverty$black_pct <-texas_bexar_ethnicity_poverty$black/texas_bexar_ethnicity_poverty$poptotal
texas_bexar_ethnicity_poverty$white_pct <- texas_bexar_ethnicity_poverty$white/texas_bexar_ethnicity_poverty$poptotal
texas_bexar_ethnicity_poverty$hispanic_pct <- texas_bexar_ethnicity_poverty$hispanic/texas_bexar_ethnicity_poverty$poptotal
texas_bexar_ethnicity_poverty$poverty_pct <- texas_bexar_ethnicity_poverty$poverty /texas_bexar_ethnicity_poverty$poptotal2
texas_bexar_ethnicity_poverty$Race <- "Other"
texas_bexar_ethnicity_poverty$Race[texas_bexar_ethnicity_poverty$white_pct > 0.5] <- "White"
texas_bexar_ethnicity_poverty$Race[texas_bexar_ethnicity_poverty$black_pct > 0.5] <- "Black"
texas_bexar_ethnicity_poverty$Race[texas_bexar_ethnicity_poverty$hispanic_pct > 0.5] <- "Hispanic"
texas_bexar_ethnicity_poverty$Poor <- ifelse(texas_bexar_ethnicity_poverty$poverty_pct > 0.3, "Poor", "Nonpoor")
texas_bexar_ethnicity_poverty$race_poverty <- paste0(texas_bexar_ethnicity_poverty$Poor, " and ", texas_bexar_ethnicity_poverty$Race)
ggplot(texas_bexar_ethnicity_poverty, aes(y=race_poverty, fill=race_poverty )) +
geom_bar()