Census Data Using an API on R studio - r

Question

So, I am new to using R, so sorry if the questions seem a little basic!
But my work is asking me to look through census data using an API and identify some variables in each tract, then create a csv file they can look at. The code is fully written for me, I believe, but I need to change the variables to:
S2602_C01_023E - black / his
S2602_C01_081E - unemployment rate
S2602_C01_070E - not US citizen (divide by total population)
S0101_C01_030E - # over 65 (divide by total pop)
S1603_C01_009E - # below poverty (divide by total pop)
S1251_C01_010E - # child under 18 (divide by # households)
S2503_C01_013E - median income
S0101_C01_001E - total population
S2602_C01_078E - in labor force
And, I need to divide some of the variables, like I have written, and export all of this into a CSV file. I just don't really know what to do with the code..like I am just lost because I have never used R. I try changing the variables to the ones I need, but an error comes up. Any help would be greatly appreciated!
library(tidycensus)
library(tidyverse)
library(stringr)
library(haven)
library(profvis)
#list of variables possible
v18 <- load_variables(year = 2018,
dataset = "acs5",
cache = TRUE)
#function to get variables for all states. Year, variables can be
easily edited.
get_census_data <- function(st) {
Sys.sleep(5)
df <- get_acs(year = 2018,
variables = c(totpop = "B01003_001",
male = "B01001_002",
female = "B01001_026",
white_alone = "B02001_002",
black_alone = "B02001_003",
americanindian_alone = "B02001_004",
asian_alone = "B02001_005",
nativehaw_alone = "B02001_006",
other_alone = "B02001_007",
twoormore = "B02001_008",
nh = "B03003_002",
his = "B03003_003",
noncit = "B05001_006",
povstatus = "B17001_002",
num_households = "B19058_001",
SNAP_households = "B19058_002",
medhhi = "B19013_001",
hsdiploma_25plus = "B15003_017",
bachelors_25plus = "B15003_022",
greater25 = "B15003_001",
inlaborforce = "B23025_002",
notinlaborforce = "B23025_007",
greater16 = "B23025_001",
civnoninstitutional = "B27010_001",
withmedicare_male_0to19 = "C27006_004",
withmedicare_male_19to64 = "C27006_007",
withmedicare_male_65plus = "C27006_010",
withmedicare_female_0to19 = "C27006_014",
withmedicare_female_19to64 = "C27006_017",
withmedicare_female_65plus = "C27006_020",
withmedicaid_male_0to19 = "C27007_004",
withmedicaid_male_19to64 = "C27007_007",
withmedicaid_male_65plus = "C27007_010",
withmedicaid_female_0to19 = "C27007_014",
withmedicaid_female_19to64 = "C27007_017",
withmedicaid_female_65plus ="C27007_020"),
geography = "tract",
state = st )
return(df)
}
#loops over all states
df_list <- setNames(lapply(states, get_census_data), states)
##if you want to keep margin of error, remove everything after %>%
in next two lines
final_df <- bind_rows(df_list) %>%
select(-moe)
colnames(final_df)[3] <- "varname"
#cleaning up final data, making it wide instead of long
final_df_wide <- final_df %>%
gather(variable, value, -(GEOID:varname)) %>%
unite(temp, varname, variable) %>%
spread(temp, value)
#exporting to csv file, adjust your path
write.csv(final_df,"C:\Users\NAME\Documents\acs_2018_tractlevel_dat.
a.csv" )

Answer 1

Since you can't really give an reproducible example without revealing your API key, I'll try my best to figure out what could work here:
Let's first edit the function that pulls data from the API:
get_census_data <- function(st) {
Sys.sleep(5)
df <- get_acs(year = 2018,
variables = c(blackHis= "S2602_C01_023E",
unEmployRate = "S2602_C01_081E",
notUSCit = "S2602_C01_070E")
geography = "tract",
state = st )
return(df)
}
I've just put in two of the variables, but you should get the point.
Try if this works for you. And returns the data that is stored in the respective variables.