synthetic_population.md
In sociome: Operationalizing Social Determinants of Health Data for Researchers

synthetic_population() works

Code
  synthetic_population(geography = "state", state = "UT", year = 2019, max_age = 87,
    rate = 10)
Message

  1 call(s) to tidycensus beginning.
  Getting data from the 2015-2019 5-year ACS
Output
  # A tibble: 3,096,848 x 8
     GEOID NAME  age_sex             sex    age_lo age_hi    age
     <chr> <chr> <chr>               <chr>   <dbl>  <dbl>  <dbl>
   1 49    Utah  males_30_to_34      male       30     34 31.8  
   2 49    Utah  males_under_5       male        0      4  0.298
   3 49    Utah  males_25_to_29      male       25     29 29.8  
   4 49    Utah  females_85_and_over female     85     87 85.1  
   5 49    Utah  females_10_to_14    female     10     14 11.1  
   6 49    Utah  females_under_5     female      0      4  2.77 
   7 49    Utah  females_67_to_69    female     67     69 68.6  
   8 49    Utah  males_35_to_39      male       35     39 35.4  
   9 49    Utah  females_60_and_61   female     60     61 61.2  
  10 49    Utah  females_62_to_64    female     62     64 62.6  
     race_ethnicity                    
     <chr>                             
   1 not_hispanic_or_latino_asian_alone
   2 not_hispanic_or_latino_white_alone
   3 not_hispanic_or_latino_white_alone
   4 not_hispanic_or_latino_white_alone
   5 not_hispanic_or_latino_white_alone
   6 not_hispanic_or_latino_white_alone
   7 not_hispanic_or_latino_white_alone
   8 not_hispanic_or_latino_white_alone
   9 not_hispanic_or_latino_white_alone
  10 hispanic_or_latino                
  # i 3,096,838 more rows

Code
  synthetic_population(geography = "block", geoid = c("51001", "40117957200",
    "490572105041"), year = 2000, dataset = "decennial")
Message

  3 call(s) to tidycensus beginning.
  Getting data from the 2000 decennial Census
  Using Census Summary File 1
  Using Census Summary File 1
  Getting data from the 2000 decennial Census
  Using Census Summary File 1
  Using Census Summary File 1
  Getting data from the 2000 decennial Census
  Using Census Summary File 1
  Using Census Summary File 1
Output
  # A tibble: 44,416 x 8
     GEOID          
     <chr>          
   1 510019901001000
   2 510019901001000
   3 510019901001000
   4 510019901001000
   5 510019901001000
   6 510019901001000
   7 510019901001000
   8 510019901001000
   9 510019901001000
  10 510019901001000
     NAME                                                                   
     <chr>                                                                  
   1 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
   2 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
   3 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
   4 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
   5 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
   6 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
   7 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
   8 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
   9 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
  10 Block 1000, Block Group 1, Census Tract 9901, Accomack County, Virginia
     age_sex          sex    age_lo age_hi   age
     <chr>            <chr>   <dbl>  <dbl> <dbl>
   1 females_75_to_79 female     75     79  77.9
   2 females_22_to_24 female     22     24  24.7
   3 males_70_to_74   male       70     74  71.4
   4 females_35_to_39 female     35     39  36.7
   5 females_55_to_59 female     55     59  59.6
   6 males_75_to_79   male       75     79  77.2
   7 females_62_to_64 female     62     64  63.2
   8 females_62_to_64 female     62     64  62.9
   9 females_30_to_34 female     30     34  33.4
  10 males_62_to_64   male       62     64  63.0
     race_ethnicity                                        
     <chr>                                                 
   1 not_hispanic_or_latino_white_alone                    
   2 not_hispanic_or_latino_white_alone                    
   3 not_hispanic_or_latino_white_alone                    
   4 not_hispanic_or_latino_black_or_african_american_alone
   5 not_hispanic_or_latino_white_alone                    
   6 not_hispanic_or_latino_white_alone                    
   7 not_hispanic_or_latino_white_alone                    
   8 not_hispanic_or_latino_white_alone                    
   9 not_hispanic_or_latino_white_alone                    
  10 not_hispanic_or_latino_black_or_african_american_alone
  # i 44,406 more rows

Code
  synthetic_population(geography = "zcta", state = c("CA", "OH", "AL"), zcta = c(
    "90210", "44133", "44147", "44136", "01001", "01010"), year = 2013, dataset = "acs5")
Message

  1 call(s) to tidycensus beginning.
  Getting data from the 2009-2013 5-year ACS
Condition
  Warning in `filter_ref_area()`:

  The following ZCTAs had no match in census data:
  01001,
  01010
Output
  # A tibble: 96,989 x 8
     GEOID NAME        age_sex           sex    age_lo age_hi   age
     <chr> <chr>       <chr>             <chr>   <dbl>  <dbl> <dbl>
   1 90210 ZCTA5 90210 females_35_to_39  female     35     39  38.4
   2 90210 ZCTA5 90210 males_62_to_64    male       62     64  63.1
   3 90210 ZCTA5 90210 females_80_to_84  female     80     84  80.7
   4 90210 ZCTA5 90210 males_55_to_59    male       55     59  55.7
   5 90210 ZCTA5 90210 females_80_to_84  female     80     84  82.2
   6 90210 ZCTA5 90210 males_85_and_over male       85    115  89.1
   7 90210 ZCTA5 90210 males_55_to_59    male       55     59  58.0
   8 90210 ZCTA5 90210 females_65_and_66 female     65     66  66.7
   9 90210 ZCTA5 90210 males_55_to_59    male       55     59  59.2
  10 90210 ZCTA5 90210 males_67_to_69    male       67     69  70.0
     race_ethnicity                    
     <chr>                             
   1 not_hispanic_or_latino_white_alone
   2 not_hispanic_or_latino_white_alone
   3 not_hispanic_or_latino_white_alone
   4 not_hispanic_or_latino_asian_alone
   5 not_hispanic_or_latino_white_alone
   6 not_hispanic_or_latino_white_alone
   7 not_hispanic_or_latino_white_alone
   8 not_hispanic_or_latino_white_alone
   9 not_hispanic_or_latino_white_alone
  10 not_hispanic_or_latino_white_alone
  # i 96,979 more rows

Code
  synthetic_population(geography = "county", state = "NY", county = c("New York",
    "Queen", "King", "Bronx", "Richmond"), year = 2005, dataset = "acs1")
Message

  1 call(s) to tidycensus beginning.
  Getting data from the 2005 1-year ACS
  The 1-year ACS provides data for geographies with populations of 65,000 and greater.
Output
  # A tibble: 7,956,113 x 8
     GEOID NAME                   age_sex           sex    age_lo age_hi   age
     <chr> <chr>                  <chr>             <chr>   <dbl>  <dbl> <dbl>
   1 36005 Bronx County, New York females_80_to_84  female     80     84 82.4 
   2 36005 Bronx County, New York females_18_and_19 female     18     19 18.9 
   3 36005 Bronx County, New York males_10_to_14    male       10     14 10.6 
   4 36005 Bronx County, New York males_35_to_39    male       35     39 36.5 
   5 36005 Bronx County, New York males_under_5     male        0      4  1.60
   6 36005 Bronx County, New York females_55_to_59  female     55     59 57.1 
   7 36005 Bronx County, New York females_50_to_54  female     50     54 53.7 
   8 36005 Bronx County, New York males_35_to_39    male       35     39 39.7 
   9 36005 Bronx County, New York females_5_to_9    female      5      9  8.23
  10 36005 Bronx County, New York males_5_to_9      male        5      9  9.76
     race_ethnicity                                                
     <chr>                                                         
   1 not_hispanic_or_latino_white_alone                            
   2 hispanic_or_latino                                            
   3 hispanic_or_latino                                            
   4 hispanic_or_latino                                            
   5 hispanic_or_latino                                            
   6 hispanic_or_latino                                            
   7 hispanic_or_latino                                            
   8 not_hispanic_or_latino_white_alone                            
   9 hispanic_or_latino                                            
  10 not_hispanic_or_latino_american_indian_and_alaska_native_alone
  # i 7,956,103 more rows