get_variable_names.md
In RcensusPkg: Easily Access US Census Bureau Survey and Geographic Data

get_variable_names()

Code
  variables_dt <- RcensusPkg::get_variable_names(dataset = "acs/acs1/profile",
    vintage = 2019, filter_label_str = "educational attainment")
  variables_dt[23:33, .(name, label, dataset)]
Output
             name
           <char>
   1:  DP02_0060E
   2: DP02_0060PE
   3:  DP02_0061E
   4: DP02_0061PE
   5:  DP02_0062E
   6: DP02_0062PE
   7:  DP02_0063E
   8: DP02_0063PE
   9:  DP02_0064E
  10: DP02_0064PE
  11:  DP02_0065E
                                                                                                            label
                                                                                                           <char>
   1:                         Estimate!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!Less than 9th grade
   2:                          Percent!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!Less than 9th grade
   3:               Estimate!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!9th to 12th grade, no diploma
   4:                Percent!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!9th to 12th grade, no diploma
   5: Estimate!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!High school graduate (includes equivalency)
   6:  Percent!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!High school graduate (includes equivalency)
   7:                     Estimate!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!Some college, no degree
   8:                      Percent!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!Some college, no degree
   9:                          Estimate!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!Associate's degree
  10:                           Percent!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!Associate's degree
  11:                           Estimate!!EDUCATIONAL ATTAINMENT!!Population 25 years and over!!Bachelor's degree
               dataset
                <char>
   1: acs/acs1/profile
   2: acs/acs1/profile
   3: acs/acs1/profile
   4: acs/acs1/profile
   5: acs/acs1/profile
   6: acs/acs1/profile
   7: acs/acs1/profile
   8: acs/acs1/profile
   9: acs/acs1/profile
  10: acs/acs1/profile
  11: acs/acs1/profile

get_variable_names() category

Code
  variables_dt <- RcensusPkg::get_variable_names(category = "acs1", vintage = 2023,
    filter_label_str = "computers")
  variables_dt[44:49, .(name, label, dataset)]
Output
            name
          <char>
  1:  DP02_0152E
  2: DP02_0152PE
  3:  DP02_0153E
  4: DP02_0153PE
  5:  DP02_0154E
  6: DP02_0154PE
                                                                                              label
                                                                                             <char>
  1:                                         Estimate!!COMPUTERS AND INTERNET USE!!Total households
  2:                                          Percent!!COMPUTERS AND INTERNET USE!!Total households
  3:                        Estimate!!COMPUTERS AND INTERNET USE!!Total households!!With a computer
  4:                         Percent!!COMPUTERS AND INTERNET USE!!Total households!!With a computer
  5: Estimate!!COMPUTERS AND INTERNET USE!!Total households!!With a broadband Internet subscription
  6:  Percent!!COMPUTERS AND INTERNET USE!!Total households!!With a broadband Internet subscription
              dataset
               <char>
  1: acs/acs1/profile
  2: acs/acs1/profile
  3: acs/acs1/profile
  4: acs/acs1/profile
  5: acs/acs1/profile
  6: acs/acs1/profile