Let’s use the Youth Tobacco Survey data again:
yts <-
read_csv("https://sisbid.github.io/Data-Wrangling/data/Youth_Tobacco_Survey_YTS_Data.csv")
head(yts)
# A tibble: 6 × 31
YEAR LocationAbbr LocationDesc TopicType TopicDesc MeasureDesc DataSource
<dbl> <chr> <chr> <chr> <chr> <chr> <chr>
1 2015 AZ Arizona Tobacco Use … Cessatio… Percent of… YTS
2 2015 AZ Arizona Tobacco Use … Cessatio… Percent of… YTS
3 2015 AZ Arizona Tobacco Use … Cessatio… Percent of… YTS
4 2015 AZ Arizona Tobacco Use … Cessatio… Quit Attem… YTS
5 2015 AZ Arizona Tobacco Use … Cessatio… Quit Attem… YTS
6 2015 AZ Arizona Tobacco Use … Cessatio… Quit Attem… YTS
# ℹ 24 more variables: Response <chr>, Data_Value_Unit <chr>,
# Data_Value_Type <chr>, Data_Value <dbl>, Data_Value_Footnote_Symbol <chr>,
# Data_Value_Footnote <chr>, Data_Value_Std_Err <dbl>,
# Low_Confidence_Limit <dbl>, High_Confidence_Limit <dbl>, Sample_Size <dbl>,
# Gender <chr>, Race <chr>, Age <chr>, Education <chr>, GeoLocation <chr>,
# TopicTypeId <chr>, TopicId <chr>, MeasureId <chr>, StratificationID1 <chr>,
# StratificationID2 <chr>, StratificationID3 <chr>, …