TAS_counts

TAS Descriptive statistics

We will be going through

Step 1: Loading Packages

library(tidyverse)
library(readxl)

Step 2: Import the data

TAS_original_data_new <- read_excel("C:/ZZ_SherMay/TAS_original_data_new.xlsx")

Step 3: Preview the data

view(TAS_original_data_new)

head(TAS_original_data_new)

## # A tibble: 6 × 101
##     TAS TAS05 TAS09 TAS15 ER30001 ER30002 ER32000 ER32006 ER33801 ER33802
##   <dbl> <dbl> <dbl> <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
## 1     1    NA     1    NA       4      37       1       2    1288       3
## 2     1    NA     1    NA       4      38       2       2    6880       2
## 3     2    NA     1     1       4      39       2       2     289       3
## 4     1    NA    NA     1       4      41       2       2    1157       3
## 5     2     1     1    NA       4     180       2       3     771       2
## 6     2     1     1    NA       5      32       2       2     624       3
## # ℹ 91 more variables: ER33803 <dbl>, TA050001 <dbl>, TA050044 <dbl>,
## #   TA050047 <dbl>, TA050050 <dbl>, TA050065 <dbl>, TA050066 <dbl>,
## #   TA050067 <dbl>, TA050070 <dbl>, TA050071 <dbl>, TA050127 <dbl>,
## #   TA050128 <dbl>, TA050129 <dbl>, TA050130 <dbl>, TA050573 <dbl>,
## #   TA050574 <dbl>, TA050575 <dbl>, TA050594 <dbl>, TA050595 <dbl>,
## #   TA050639 <dbl>, TA050663 <dbl>, TA050664 <dbl>, TA050665 <dbl>,
## #   TA050670 <dbl>, TA050675 <dbl>, TA050676 <dbl>, TA050884 <dbl>, …

Step 4: Descriptive statistics

2005 COUNT

TA050044: B5A Responsibility for own

TAS_original_data_new %>% count(TA050044)

## # A tibble: 6 × 2
##   TA050044     n
##      <dbl> <int>
## 1        1    31
## 2        2   124
## 3        3   155
## 4        4   238
## 5        5   197
## 6       NA  1941

TA050047: B5D Managing own money

TAS_original_data_new %>% count(TA050047)

## # A tibble: 6 × 2
##   TA050047     n
##      <dbl> <int>
## 1        1    18
## 2        2    19
## 3        3    70
## 4        4   184
## 5        5   454
## 6       NA  1941

TA050050: B6C Money management skills

TAS_original_data_new %>% count(TA050050)

## # A tibble: 8 × 2
##   TA050050     n
##      <dbl> <int>
## 1        1    15
## 2        2    26
## 3        3    39
## 4        4    92
## 5        5   204
## 6        6   170
## 7        7   199
## 8       NA  1941

TA050065: C2D Worry about expenses

TAS_original_data_new %>% count(TA050065)

## # A tibble: 8 × 2
##   TA050065     n
##      <dbl> <int>
## 1        1   114
## 2        2   115
## 3        3   122
## 4        4   130
## 5        5   113
## 6        6    70
## 7        7    81
## 8       NA  1941

TA050066: C2E Worry about future job

TAS_original_data_new %>% count(TA050066)

## # A tibble: 8 × 2
##   TA050066     n
##      <dbl> <int>
## 1        1   144
## 2        2   126
## 3        3   115
## 4        4    87
## 5        5   109
## 6        6    85
## 7        7    79
## 8       NA  1941

TA050067: C2F Discouraged about future

TAS_original_data_new %>% count(TA050067)

## # A tibble: 9 × 2
##   TA050067     n
##      <dbl> <int>
## 1        1   191
## 2        2   153
## 3        3   124
## 4        4   100
## 5        5    80
## 6        6    50
## 7        7    45
## 8        8     2
## 9       NA  1941

TA050071: D2D3 Widowed – Year

TAS_original_data_new %>% count(TA050071)

## # A tibble: 3 × 2
##   TA050071     n
##      <dbl> <int>
## 1        0   744
## 2     2005     1
## 3       NA  1941

TA050127: E1 Employment status – 1st mention

TAS_original_data_new %>% count(TA050127)

## # A tibble: 8 × 2
##   TA050127     n
##      <dbl> <int>
## 1        1   364
## 2        2     4
## 3        3    98
## 4        5     2
## 5        6    23
## 6        7   246
## 7        8     8
## 8       NA  1941

TA050128: E1 Employment status – 2nd mention

TAS_original_data_new %>% count(TA050128)

## # A tibble: 7 × 2
##   TA050128     n
##      <dbl> <int>
## 1        0   560
## 2        1    32
## 3        3    13
## 4        5     1
## 5        6     8
## 6        7   131
## 7       NA  1941

TA050129: E1 Employment status – 3rd mention

TAS_original_data_new %>% count(TA050129)

## # A tibble: 6 × 2
##   TA050129     n
##      <dbl> <int>
## 1        0   740
## 2        1     1
## 3        3     1
## 4        6     1
## 5        7     2
## 6       NA  1941

TA050130: E3 Work for money

TAS_original_data_new %>% count(TA050130)

## # A tibble: 5 × 2
##   TA050130     n
##      <dbl> <int>
## 1        0   400
## 2        1    86
## 3        5   258
## 4        9     1
## 5       NA  1941

TA050573: G1 Graduated high school

TAS_original_data_new %>% count(TA050573)

## # A tibble: 5 × 2
##   TA050573     n
##      <dbl> <int>
## 1        1   601
## 2        2    46
## 3        3    96
## 4        9     2
## 5       NA  1941

TA050575: G2 Year Graduated high school

TAS_original_data_new %>% count(TA050575)

## # A tibble: 8 × 2
##   TA050575     n
##      <dbl> <int>
## 1        0   146
## 2     2000     2
## 3     2001     2
## 4     2002    83
## 5     2003   164
## 6     2004   169
## 7     2005   179
## 8       NA  1941

TA050594: G10 Attended college

TAS_original_data_new %>% count(TA050594)

## # A tibble: 5 × 2
##   TA050594     n
##      <dbl> <int>
## 1        0    97
## 2        1   487
## 3        5   160
## 4        9     1
## 5       NA  1941

TA050595: G11 Attending college

TAS_original_data_new %>% count(TA050595)

## # A tibble: 4 × 2
##   TA050595     n
##      <dbl> <int>
## 1        0   258
## 2        1   397
## 3        5    90
## 4       NA  1941

TA050639: G30A Likelihood of well-paying job

TAS_original_data_new %>% count(TA050639)

## # A tibble: 9 × 2
##   TA050639     n
##      <dbl> <int>
## 1        0    79
## 2        1     3
## 3        2     1
## 4        3     7
## 5        4    39
## 6        5   132
## 7        6   235
## 8        7   249
## 9       NA  1941

TA050663: G41A Importance of job status

TAS_original_data_new %>% count(TA050663)

## # A tibble: 8 × 2
##   TA050663     n
##      <dbl> <int>
## 1        1    26
## 2        2    29
## 3        3    47
## 4        4    78
## 5        5   168
## 6        6   160
## 7        7   237
## 8       NA  1941

TA050664: G41B Importance of decision-making

TAS_original_data_new %>% count(TA050664)

## # A tibble: 8 × 2
##   TA050664     n
##      <dbl> <int>
## 1        1     3
## 2        2     8
## 3        3    21
## 4        4    52
## 5        5   181
## 6        6   250
## 7        7   230
## 8       NA  1941

TA050665: G41C Importance of challenging work

TAS_original_data_new %>% count(TA050665)

## # A tibble: 8 × 2
##   TA050665     n
##      <dbl> <int>
## 1        1     2
## 2        2     9
## 3        3    29
## 4        4    94
## 5        5   212
## 6        6   223
## 7        7   176
## 8       NA  1941

TA050670: G41H Importance of healthcare benefits

TAS_original_data_new %>% count(TA050670)

## # A tibble: 8 × 2
##   TA050670     n
##      <dbl> <int>
## 1        1     3
## 2        2     4
## 3        3     8
## 4        4    28
## 5        5    74
## 6        6   176
## 7        7   452
## 8       NA  1941

TA050675: G41P Importance of job central to identity

TAS_original_data_new %>% count(TA050675)

## # A tibble: 10 × 2
##    TA050675     n
##       <dbl> <int>
##  1        1    22
##  2        2    29
##  3        3    63
##  4        4   121
##  5        5   187
##  6        6   166
##  7        7   154
##  8        8     2
##  9        9     1
## 10       NA  1941

TA050676: H1 Health level

TAS_original_data_new %>% count(TA050676)

## # A tibble: 7 × 2
##   TA050676     n
##      <dbl> <int>
## 1        1   188
## 2        2   288
## 3        3   207
## 4        4    53
## 5        5     7
## 6        9     2
## 7       NA  1941

TA050884: L7 Race – 1st mention

TAS_original_data_new %>% count(TA050884)

## # A tibble: 9 × 2
##   TA050884     n
##      <dbl> <int>
## 1        1   378
## 2        2   312
## 3        3     6
## 4        4     8
## 5        5     3
## 6        7     8
## 7        8     2
## 8        9    28
## 9       NA  1941

TA050885: L7 Race – 2nd mention

TAS_original_data_new %>% count(TA050885)

## # A tibble: 7 × 2
##   TA050885     n
##      <dbl> <int>
## 1        0   728
## 2        1     1
## 3        2     4
## 4        3     7
## 5        5     2
## 6        7     3
## 7       NA  1941

TA050886: L7 Race – 3rd mention

TAS_original_data_new %>% count(TA050886)

## # A tibble: 4 × 2
##   TA050886     n
##      <dbl> <int>
## 1        0   743
## 2        3     1
## 3        5     1
## 4       NA  1941

---

2009 COUNT

TA090045: B5A Responsibility for self

TAS_original_data_new %>% count(TA090045)

## # A tibble: 7 × 2
##   TA090045     n
##      <dbl> <int>
## 1        1    61
## 2        2   167
## 3        3   238
## 4        4   462
## 5        5   624
## 6        9     2
## 7       NA  1132

TA090048: B5D Managing own money

TAS_original_data_new %>% count(TA090048)

## # A tibble: 7 × 2
##   TA090048     n
##      <dbl> <int>
## 1        1    36
## 2        2    29
## 3        3    94
## 4        4   284
## 5        5  1110
## 6        9     1
## 7       NA  1132

TA090051: B6C Money management skills

TAS_original_data_new %>% count(TA090051)

## # A tibble: 8 × 2
##   TA090051     n
##      <dbl> <int>
## 1        1    14
## 2        2    30
## 3        3    65
## 4        4   201
## 5        5   450
## 6        6   401
## 7        7   393
## 8       NA  1132

TA090066: C2D Worry about expenses

TAS_original_data_new %>% count(TA090066)

## # A tibble: 8 × 2
##   TA090066     n
##      <dbl> <int>
## 1        1   195
## 2        2   236
## 3        3   231
## 4        4   281
## 5        5   237
## 6        6   166
## 7        7   208
## 8       NA  1132

TA090067: C2E Worry about future job

TAS_original_data_new %>% count(TA090067)

## # A tibble: 8 × 2
##   TA090067     n
##      <dbl> <int>
## 1        1   246
## 2        2   250
## 3        3   239
## 4        4   252
## 5        5   216
## 6        6   147
## 7        7   204
## 8       NA  1132

TA090068: C2F Discouraged about future

TAS_original_data_new %>% count(TA090068)

## # A tibble: 8 × 2
##   TA090068     n
##      <dbl> <int>
## 1        1   297
## 2        2   344
## 3        3   277
## 4        4   241
## 5        5   190
## 6        6    97
## 7        7   108
## 8       NA  1132

TA090080: D2D3 Widowed – Year

TAS_original_data_new %>% count(TA090080)

## # A tibble: 6 × 2
##   TA090080     n
##      <dbl> <int>
## 1        0  1544
## 2     2005     1
## 3     2006     2
## 4     2007     1
## 5     2009     6
## 6       NA  1132

TA090136: E1 Employment status – 1st mention

TAS_original_data_new %>% count(TA090136)

## # A tibble: 9 × 2
##   TA090136     n
##      <dbl> <int>
## 1        1   854
## 2        2     2
## 3        3   322
## 4        5     8
## 5        6    54
## 6        7   308
## 7        8     4
## 8       99     2
## 9       NA  1132

TA090137: E1 Employment status – 2nd mention

TAS_original_data_new %>% count(TA090137)

## # A tibble: 9 × 2
##   TA090137     n
##      <dbl> <int>
## 1        0  1078
## 2        1    70
## 3        2     1
## 4        3    61
## 5        5     3
## 6        6    26
## 7        7   313
## 8        8     2
## 9       NA  1132

TA090138: E1 Employment status – 3rd mention

TAS_original_data_new %>% count(TA090138)

## # A tibble: 5 × 2
##   TA090138     n
##      <dbl> <int>
## 1        0  1550
## 2        1     1
## 3        6     1
## 4        7     2
## 5       NA  1132

TA090139: E3 Work for money

TAS_original_data_new %>% count(TA090139)

## # A tibble: 4 × 2
##   TA090139     n
##      <dbl> <int>
## 1        0   928
## 2        1    96
## 3        5   530
## 4       NA  1132

TA090590: G1 Education status

TAS_original_data_new %>% count(TA090590)

## # A tibble: 5 × 2
##   TA090590     n
##      <dbl> <int>
## 1        1  1292
## 2        2   108
## 3        3   153
## 4        9     1
## 5       NA  1132

TA090592: G2 High School Graduation – Year

TAS_original_data_new %>% count(TA090592)

## # A tibble: 13 × 2
##    TA090592     n
##       <dbl> <int>
##  1        0   264
##  2     1999     1
##  3     2000     1
##  4     2001     2
##  5     2002    84
##  6     2003   153
##  7     2004   161
##  8     2005   183
##  9     2006   172
## 10     2007   166
## 11     2008   172
## 12     2009   195
## 13       NA  1132

TA090611: G10 Attended college

TAS_original_data_new %>% count(TA090611)

## # A tibble: 5 × 2
##   TA090611     n
##      <dbl> <int>
## 1        0   154
## 2        1  1043
## 3        5   352
## 4        9     5
## 5       NA  1132

TA090612: G11 Attending college

TAS_original_data_new %>% count(TA090612)

## # A tibble: 4 × 2
##   TA090612     n
##      <dbl> <int>
## 1        0   511
## 2        1   631
## 3        5   412
## 4       NA  1132

TA090663: G30A Likelihood of well-paying job

TAS_original_data_new %>% count(TA090663)

## # A tibble: 9 × 2
##   TA090663     n
##      <dbl> <int>
## 1        1    14
## 2        2     7
## 3        3    17
## 4        4    90
## 5        5   367
## 6        6   464
## 7        7   594
## 8        9     1
## 9       NA  1132

TA090687: G41A Importance of job status

TAS_original_data_new %>% count(TA090687)

## # A tibble: 9 × 2
##   TA090687     n
##      <dbl> <int>
## 1        1   115
## 2        2    74
## 3        3   112
## 4        4   215
## 5        5   371
## 6        6   269
## 7        7   396
## 8        9     2
## 9       NA  1132

TA090688: G41B Importance of decision-making

TAS_original_data_new %>% count(TA090688)

## # A tibble: 9 × 2
##   TA090688     n
##      <dbl> <int>
## 1        1    21
## 2        2    13
## 3        3    39
## 4        4   134
## 5        5   403
## 6        6   472
## 7        7   471
## 8        9     1
## 9       NA  1132

TA090689: G41C Importance of challenging work

TAS_original_data_new %>% count(TA090689)

## # A tibble: 9 × 2
##   TA090689     n
##      <dbl> <int>
## 1        1    24
## 2        2    19
## 3        3    56
## 4        4   169
## 5        5   420
## 6        6   471
## 7        7   394
## 8        9     1
## 9       NA  1132

TA090694: G41H Importance of healthcare benefits

TAS_original_data_new %>% count(TA090694)

## # A tibble: 9 × 2
##   TA090694     n
##      <dbl> <int>
## 1        1    14
## 2        2    11
## 3        3    16
## 4        4    62
## 5        5   155
## 6        6   345
## 7        7   950
## 8        9     1
## 9       NA  1132

TA090699: G41P Importance of job central to identity

TAS_original_data_new %>% count(TA090699)

## # A tibble: 10 × 2
##    TA090699     n
##       <dbl> <int>
##  1        1   100
##  2        2   104
##  3        3   125
##  4        4   293
##  5        5   366
##  6        6   245
##  7        7   315
##  8        8     3
##  9        9     3
## 10       NA  1132

TA090700: H1 General Health

TAS_original_data_new %>% count(TA090700)

## # A tibble: 7 × 2
##   TA090700     n
##      <dbl> <int>
## 1        1   375
## 2        2   646
## 3        3   411
## 4        4   109
## 5        5    12
## 6        9     1
## 7       NA  1132

TA090925: L7 Race – 1st mention

TAS_original_data_new %>% count(TA090925)

## # A tibble: 9 × 2
##   TA090925     n
##      <dbl> <int>
## 1        1   768
## 2        2   660
## 3        3    16
## 4        4    23
## 5        5     2
## 6        7    77
## 7        8     3
## 8        9     5
## 9       NA  1132

TA090926: L7 Race – 2nd mention

TAS_original_data_new %>% count(TA090926)

## # A tibble: 9 × 2
##   TA090926     n
##      <dbl> <int>
## 1        0  1467
## 2        1    13
## 3        2    14
## 4        3    45
## 5        4     2
## 6        5     4
## 7        7     8
## 8        9     1
## 9       NA  1132

TA090927: L7 Race – 3rd mention

TAS_original_data_new %>% count(TA090927)

## # A tibble: 5 × 2
##   TA090927     n
##      <dbl> <int>
## 1        0  1545
## 2        3     6
## 3        5     1
## 4        7     2
## 5       NA  1132

---

2015 COUNT

TA150045: B5A Responsibility for self

TAS_original_data_new %>% count(TA150045)

## # A tibble: 7 × 2
##   TA150045     n
##      <dbl> <int>
## 1        1    52
## 2        2   147
## 3        3   217
## 4        4   422
## 5        5   800
## 6        8     3
## 7       NA  1045

TA150048: B5D Managing own money

TAS_original_data_new %>% count(TA150048)

## # A tibble: 7 × 2
##   TA150048     n
##      <dbl> <int>
## 1        1    28
## 2        2    39
## 3        3    92
## 4        4   243
## 5        5  1237
## 6        9     2
## 7       NA  1045

TA150051: B6C Money management skills

TAS_original_data_new %>% count(TA150051)

## # A tibble: 8 × 2
##   TA150051     n
##      <dbl> <int>
## 1        1    13
## 2        2    29
## 3        3    76
## 4        4   229
## 5        5   470
## 6        6   428
## 7        7   396
## 8       NA  1045

TA150066: C2D Worry about expenses

TAS_original_data_new %>% count(TA150066)

## # A tibble: 8 × 2
##   TA150066     n
##      <dbl> <int>
## 1        1   268
## 2        2   285
## 3        3   283
## 4        4   257
## 5        5   245
## 6        6   141
## 7        7   162
## 8       NA  1045

TA150067: C2E Worry about future job

TAS_original_data_new %>% count(TA150067)

## # A tibble: 8 × 2
##   TA150067     n
##      <dbl> <int>
## 1        1   321
## 2        2   308
## 3        3   249
## 4        4   243
## 5        5   215
## 6        6   130
## 7        7   175
## 8       NA  1045

TA150068: C2F Discouraged about future

TAS_original_data_new %>% count(TA150068)

## # A tibble: 8 × 2
##   TA150068     n
##      <dbl> <int>
## 1        1   378
## 2        2   375
## 3        3   272
## 4        4   239
## 5        5   194
## 6        6    86
## 7        7    97
## 8       NA  1045

TA150072: D2D3 Widowed – Year

TAS_original_data_new %>% count(TA150072)

## # A tibble: 7 × 2
##   TA150072     n
##      <dbl> <int>
## 1        0  1620
## 2     2009     2
## 3     2010     2
## 4     2011     1
## 5     2012     4
## 6     2014    12
## 7       NA  1045

TA150128: E1 Employment status – 1st mention

TAS_original_data_new %>% count(TA150128)

## # A tibble: 7 × 2
##   TA150128     n
##      <dbl> <int>
## 1        1  1103
## 2        2     6
## 3        3   246
## 4        5     9
## 5        6    60
## 6        7   217
## 7       NA  1045

TA150129: E1 Employment status – 2nd mention

TAS_original_data_new %>% count(TA150129)

## # A tibble: 7 × 2
##   TA150129     n
##      <dbl> <int>
## 1        0  1248
## 2        1    55
## 3        2     1
## 4        3    34
## 5        6    36
## 6        7   267
## 7       NA  1045

TA150130: E1 Employment status – 3rd mention

TAS_original_data_new %>% count(TA150130)

## # A tibble: 6 × 2
##   TA150130     n
##      <dbl> <int>
## 1        0  1637
## 2        1     1
## 3        3     1
## 4        6     1
## 5        7     1
## 6       NA  1045

TA150131: E3 Work for money

TAS_original_data_new %>% count(TA150131)

## # A tibble: 5 × 2
##   TA150131     n
##      <dbl> <int>
## 1        0  1165
## 2        1    51
## 3        5   424
## 4        9     1
## 5       NA  1045

TA150701: G1 Education status

TAS_original_data_new %>% count(TA150701)

## # A tibble: 6 × 2
##   TA150701     n
##      <dbl> <int>
## 1        0   710
## 2        1   799
## 3        2    52
## 4        3    79
## 5        9     1
## 6       NA  1045

TA150703: G2 High School Graduation – Year

TAS_original_data_new %>% count(TA150703)

## # A tibble: 14 × 2
##    TA150703     n
##       <dbl> <int>
##  1        0   940
##  2     2001     1
##  3     2004     1
##  4     2006    15
##  5     2007    31
##  6     2008    37
##  7     2009    55
##  8     2010    93
##  9     2011   146
## 10     2012    32
## 11     2013    36
## 12     2014   163
## 13     2015    91
## 14       NA  1045

TA150730: G10 Attended college

TAS_original_data_new %>% count(TA150730)

## # A tibble: 4 × 2
##   TA150730     n
##      <dbl> <int>
## 1        0   762
## 2        1   531
## 3        5   348
## 4       NA  1045

TA150731: G11 Attending college

TAS_original_data_new %>% count(TA150731)

## # A tibble: 4 × 2
##   TA150731     n
##      <dbl> <int>
## 1        0   455
## 2        1   482
## 3        5   704
## 4       NA  1045

TA150784: G30A Likelihood of well-paying job

TAS_original_data_new %>% count(TA150784)

## # A tibble: 9 × 2
##   TA150784     n
##      <dbl> <int>
## 1        1     8
## 2        2     7
## 3        3    19
## 4        4    99
## 5        5   332
## 6        6   453
## 7        7   721
## 8        9     2
## 9       NA  1045

TA150808: G41A Importance of job status

TAS_original_data_new %>% count(TA150808)

## # A tibble: 9 × 2
##   TA150808     n
##      <dbl> <int>
## 1        1   140
## 2        2   108
## 3        3   122
## 4        4   231
## 5        5   372
## 6        6   286
## 7        7   380
## 8        9     2
## 9       NA  1045

TA150809: G41B Importance of decision-making

TAS_original_data_new %>% count(TA150809)

## # A tibble: 9 × 2
##   TA150809     n
##      <dbl> <int>
## 1        1    38
## 2        2    21
## 3        3    55
## 4        4   146
## 5        5   429
## 6        6   451
## 7        7   499
## 8        9     2
## 9       NA  1045

TA150810: G41C Importance of challenging work

TAS_original_data_new %>% count(TA150810)

## # A tibble: 10 × 2
##    TA150810     n
##       <dbl> <int>
##  1        0   500
##  2        1    16
##  3        2    12
##  4        3    51
##  5        4   132
##  6        5   319
##  7        6   326
##  8        7   283
##  9        9     2
## 10       NA  1045

TA150815: G41H Importance of healthcare benefits

TAS_original_data_new %>% count(TA150815)

## # A tibble: 9 × 2
##   TA150815     n
##      <dbl> <int>
## 1        1    22
## 2        2    22
## 3        3    25
## 4        4    67
## 5        5   213
## 6        6   377
## 7        7   913
## 8        9     2
## 9       NA  1045

TA150820: G41P Importance of job central to identity

TAS_original_data_new %>% count(TA150820)

## # A tibble: 10 × 2
##    TA150820     n
##       <dbl> <int>
##  1        1    79
##  2        2    83
##  3        3   126
##  4        4   303
##  5        5   387
##  6        6   300
##  7        7   358
##  8        8     2
##  9        9     3
## 10       NA  1045

TA150821: H1 General Health

TAS_original_data_new %>% count(TA150821)

## # A tibble: 7 × 2
##   TA150821     n
##      <dbl> <int>
## 1        1   333
## 2        2   694
## 3        3   423
## 4        4   170
## 5        5    19
## 6        9     2
## 7       NA  1045

TA151132: L7 Race – 1st mention

TAS_original_data_new %>% count(TA151132)

## # A tibble: 9 × 2
##   TA151132     n
##      <dbl> <int>
## 1        1   818
## 2        2   694
## 3        3    15
## 4        4    32
## 5        5     3
## 6        7    70
## 7        8     1
## 8        9     8
## 9       NA  1045

TA151133: L7 Race – 2nd mention

TAS_original_data_new %>% count(TA151133)

## # A tibble: 9 × 2
##   TA151133     n
##      <dbl> <int>
## 1        0  1523
## 2        1    15
## 3        2    17
## 4        3    56
## 5        4     7
## 6        5     8
## 7        7    14
## 8        9     1
## 9       NA  1045

TA151134: L7 Race – 3rd mention

TAS_original_data_new %>% count(TA151134)

## # A tibble: 6 × 2
##   TA151134     n
##      <dbl> <int>
## 1        0  1625
## 2        1     9
## 3        3     4
## 4        5     1
## 5        7     2
## 6       NA  1045