data_tabulate.md
In datawizard: Easy Data Wrangling and Statistical Transformations

data_tabulate print

Code
  data_tabulate(efc$e42dep)
Output
  elder's dependency (efc$e42dep) <categorical>
  # total N=100 valid N=97

  Value |  N | Raw % | Valid % | Cumulative %
  ------+----+-------+---------+-------------
  1     |  2 |  2.00 |    2.06 |         2.06
  2     |  4 |  4.00 |    4.12 |         6.19
  3     | 28 | 28.00 |   28.87 |        35.05
  4     | 63 | 63.00 |   64.95 |       100.00
  <NA>  |  3 |  3.00 |    <NA> |         <NA>

data_tabulate print multiple

Code
  data_tabulate(efc, c("c172code", "e16sex"))
Output
  carer's level of education (c172code) <numeric>
  # total N=100 valid N=90

  Value |  N | Raw % | Valid % | Cumulative %
  ------+----+-------+---------+-------------
  1     |  8 |  8.00 |    8.89 |         8.89
  2     | 66 | 66.00 |   73.33 |        82.22
  3     | 16 | 16.00 |   17.78 |       100.00
  <NA>  | 10 | 10.00 |    <NA> |         <NA>

  elder's gender (e16sex) <numeric>
  # total N=100 valid N=100

  Value |  N | Raw % | Valid % | Cumulative %
  ------+----+-------+---------+-------------
  1     | 46 | 46.00 |   46.00 |        46.00
  2     | 54 | 54.00 |   54.00 |       100.00
  <NA>  |  0 |  0.00 |    <NA> |         <NA>

data_tabulate big numbers

Code
  data_tabulate(x)
Output
  x <integer>
  # total N=10,000,000 valid N=10,000,000

  Value |         N | Raw % | Valid % | Cumulative %
  ------+-----------+-------+---------+-------------
  1     | 1,998,318 | 19.98 |   19.98 |        19.98
  2     | 1,998,338 | 19.98 |   19.98 |        39.97
  3     | 2,001,814 | 20.02 |   20.02 |        59.98
  4     | 1,999,423 | 19.99 |   19.99 |        79.98
  5     | 2,002,107 | 20.02 |   20.02 |       100.00
  <NA>  |         0 |  0.00 |    <NA> |         <NA>

Code
  print(data_tabulate(x), big_mark = "-")
Output
  x <integer>
  # total N=10-000-000 valid N=10-000-000

  Value |         N | Raw % | Valid % | Cumulative %
  ------+-----------+-------+---------+-------------
  1     | 1-998-318 | 19.98 |   19.98 |        19.98
  2     | 1-998-338 | 19.98 |   19.98 |        39.97
  3     | 2-001-814 | 20.02 |   20.02 |        59.98
  4     | 1-999-423 | 19.99 |   19.99 |        79.98
  5     | 2-002-107 | 20.02 |   20.02 |       100.00
  <NA>  |         0 |  0.00 |    <NA> |         <NA>

data_tabulate print multiple, collapse

Code
  data_tabulate(efc, c("c172code", "e16sex"), collapse = TRUE)
Output
  # Frequency Table

  Variable | Value |  N | Raw % | Valid % | Cumulative %
  ---------+-------+----+-------+---------+-------------
  c172code |     1 |  8 |  8.00 |    8.89 |         8.89
           |     2 | 66 | 66.00 |   73.33 |        82.22
           |     3 | 16 | 16.00 |   17.78 |       100.00
           |  <NA> | 10 | 10.00 |    <NA> |         <NA>
  ---------+-------+----+-------+---------+-------------
  e16sex   |     1 | 46 | 46.00 |   46.00 |        46.00
           |     2 | 54 | 54.00 |   54.00 |       100.00
           |  <NA> |  0 |  0.00 |    <NA> |         <NA>
  ------------------------------------------------------

data_tabulate print grouped data

Code
  data_tabulate(poorman::group_by(efc, e16sex), "c172code")
Output
  carer's level of education (c172code) <numeric>
  Grouped by e16sex (1)
  # total N=46 valid N=41

  Value |  N | Raw % | Valid % | Cumulative %
  ------+----+-------+---------+-------------
  1     |  5 | 10.87 |   12.20 |        12.20
  2     | 32 | 69.57 |   78.05 |        90.24
  3     |  4 |  8.70 |    9.76 |       100.00
  <NA>  |  5 | 10.87 |    <NA> |         <NA>

  carer's level of education (c172code) <numeric>
  Grouped by e16sex (2)
  # total N=54 valid N=49

  Value |  N | Raw % | Valid % | Cumulative %
  ------+----+-------+---------+-------------
  1     |  3 |  5.56 |    6.12 |         6.12
  2     | 34 | 62.96 |   69.39 |        75.51
  3     | 12 | 22.22 |   24.49 |       100.00
  <NA>  |  5 |  9.26 |    <NA> |         <NA>

data_tabulate print, collapse groups

Code
  data_tabulate(poorman::group_by(efc, e16sex), "c172code", collapse = TRUE)
Output
  # Frequency Table

  Variable |      Group | Value |  N | Raw % | Valid % | Cumulative %
  ---------+------------+-------+----+-------+---------+-------------
  c172code | e16sex (1) |     1 |  5 | 10.87 |   12.20 |        12.20
           |            |     2 | 32 | 69.57 |   78.05 |        90.24
           |            |     3 |  4 |  8.70 |    9.76 |       100.00
           |            |  <NA> |  5 | 10.87 |    <NA> |         <NA>
  ---------+------------+-------+----+-------+---------+-------------
  c172code | e16sex (2) |     1 |  3 |  5.56 |    6.12 |         6.12
           |            |     2 | 34 | 62.96 |   69.39 |        75.51
           |            |     3 | 12 | 22.22 |   24.49 |       100.00
           |            |  <NA> |  5 |  9.26 |    <NA> |         <NA>
  -------------------------------------------------------------------

data_tabulate print, collapse groups, drop levels

Code
  data_tabulate(poorman::group_by(efc, e16sex), "e42dep", collapse = TRUE,
  drop_levels = TRUE)
Output
  # Frequency Table

  Variable |      Group | Value |  N | Raw % | Valid % | Cumulative %
  ---------+------------+-------+----+-------+---------+-------------
  e42dep   | e16sex (1) |     1 |  2 |  4.35 |    4.44 |         4.44
           |            |     2 |  2 |  4.35 |    4.44 |         8.89
           |            |     3 |  8 | 17.39 |   17.78 |        26.67
           |            |     4 | 33 | 71.74 |   73.33 |       100.00
           |            |  <NA> |  1 |  2.17 |    <NA> |         <NA>
  ---------+------------+-------+----+-------+---------+-------------
  e42dep   | e16sex (2) |     2 |  2 |  3.70 |    3.85 |         3.85
           |            |     3 | 20 | 37.04 |   38.46 |        42.31
           |            |     4 | 30 | 55.56 |   57.69 |       100.00
           |            |  <NA> |  2 |  3.70 |    <NA> |         <NA>
  -------------------------------------------------------------------