FreqTools

A package that produces frequency tables and associated summary tables. It mostly is a wrapper for the excellent FreqTables.jl package. tab is the main function. It is intended for interactive use and does not return any values.

Installation

  ] add FreqTools

Syntax

tab(df::AbstractDataFrame, vars::Union{String,Symbol}...; skipmissing = true, sort = nothing, pct = :rce, summarize = nothing)
tab(na::NamedArray; skipmissing = true, pct = :rce)
tab(m::Matrix)

Produce an one-way or two-way frequency table from a DataFrame or a NamedArray returned from freqtable function. tab is mainly a wrapper for the excellent FreqTables package.

If a matrix of counts is used as an argument, a Pearson chi-square test will be performed.

This package reexports FreqTables.jl.

Options:

skipmissing - set to false to include missing values in the frequency table (default = true)
sort - set it to true to sort the output table by the order of frequency with the largest category on top. It can only be used in the one-way table (default = false)
pct - set it to any combination of r (row), c (column), and/or e (cell) as a Symbol to request row, column, and cell percentages (default = :rce). For example, :rce will produce a table with row, column, and cell percentages (in that order) in the same table
summarize - specify a "continuous" variable to produce means, standard deviations, and counts in a one-way or two-way tables (default = nothing)

Examples

julia> using RDatasets

julia> lbw = dataset("COUNT","lbw");

julia> describe(lbw)
10×7 DataFrame
 Row │ variable  mean          min    median   max    nmissing  eltype   
     │ Symbol    Float64       Int64  Float64  Int64  Int64     DataType
─────┼───────────────────────────────────────────────────────────────────
   1 │ Low          0.312169       0      0.0      1         0  Int64
   2 │ Smoke        0.391534       0      0.0      1         0  Int64
   3 │ Race         1.84656        1      1.0      3         0  Int64
   4 │ Age         23.2381        14     23.0     45         0  Int64
   5 │ LWt        129.82          80    121.0    250         0  Int64
   6 │ PTL          0.195767       0      0.0      3         0  Int64
   7 │ Ht           0.0634921      0      0.0      1         0  Int64
   8 │ UI           0.148148       0      0.0      1         0  Int64
   9 │ FTV          0.793651       0      0.0      6         0  Int64
  10 │ BWt       2944.29         709   2977.0   4990         0  Int64

1. One-way frequency table

1.a Frequencies

julia> tab(lbw, :Low)
───────┬───────────────────────────
   Low │ Counts   Percent  Cum Pct 
───────┼───────────────────────────
     0 │    130    68.783   68.783
     1 │     59    31.217  100.000
───────┼───────────────────────────
 Total │    189   100.000  100.000
───────┴───────────────────────────

1.b Summarize birthweight by smoking status

julia> tab(lbw, :Smoke, summarize = :BWt)
───────┬────────────────────────
 Smoke │   N      Mean    StDev 
───────┼────────────────────────
     0 │ 115  3054.957  752.409
     1 │  74  2772.297  659.807
───────┼────────────────────────
 Total │ 189  2944.286  729.016
───────┴────────────────────────

1.c Frequency sorted by counts

julia> tab(lbw,:Race, sort=true)
───────┬───────────────────────────
  Race │ Counts   Percent  Cum Pct 
───────┼───────────────────────────
     1 │     96    50.794   50.794
     3 │     67    35.450   86.243
     2 │     26    13.757  100.000
───────┼───────────────────────────
 Total │    189   100.000  100.000
───────┴───────────────────────────

2. Two-way frequency table

2.a Frequency table with row, column, and cell percentages (default)

julia> tab(lbw, :Race, :Smoke)

──────────────┬───────────────────────────
 Race / Smoke │       0        1    Total 
──────────────┼───────────────────────────
            1 │      44       52       96
              │  45.833   54.167  100.000
              │  38.261   70.270   50.794
              │  23.280   27.513   50.794
──────────────┼───────────────────────────
            2 │      16       10       26
              │  61.538   38.462  100.000
              │  13.913   13.514   13.757
              │   8.466    5.291   13.757
──────────────┼───────────────────────────
            3 │      55       12       67
              │  82.090   17.910  100.000
              │  47.826   16.216   35.450
              │  29.101    6.349   35.450
──────────────┼───────────────────────────
        Total │     115       74      189
              │  60.847   39.153  100.000
              │ 100.000  100.000  100.000
              │  60.847   39.153  100.000
──────────────┴───────────────────────────
Pearson chi-square = 21.7790 (2), p < 0.0001

2.b Pearson chi-square test for a matrix of counts

julia> tab([44 52 ; 16 10; 55 12])
───────┬───────────────────────────
 A / B │       1        2    Total 
───────┼───────────────────────────
     1 │      44       52       96
       │  45.833   54.167  100.000
       │  38.261   70.270   50.794
       │  23.280   27.513   50.794
───────┼───────────────────────────
     2 │      16       10       26
       │  61.538   38.462  100.000
       │  13.913   13.514   13.757
       │   8.466    5.291   13.757
───────┼───────────────────────────
     3 │      55       12       67
       │  82.090   17.910  100.000
       │  47.826   16.216   35.450
       │  29.101    6.349   35.450
───────┼───────────────────────────
 Total │     115       74      189
       │  60.847   39.153  100.000
       │ 100.000  100.000  100.000
       │  60.847   39.153  100.000
───────┴───────────────────────────
Pearson chi-square = 21.7790 (2), p < 0.0001

2.c Frequency table with no percentages

julia> tab(lbw,:Race,:Smoke, pct = nothing )
──────────────┬────────────────
 Race / Smoke │   0   1  Total 
──────────────┼────────────────
            1 │  44  52     96
            2 │  16  10     26
            3 │  55  12     67
──────────────┼────────────────
        Total │ 115  74    189
──────────────┴────────────────
Pearson chi-square = 21.7790 (2), p < 0.0001

2.d Frequency table with row percentages alone

julia> tab(lbw, :Race, :Smoke, pct = :r)
──────────────┬─────────────────────────
 Race / Smoke │      0       1    Total 
──────────────┼─────────────────────────
            1 │     44      52       96
              │ 45.833  54.167  100.000
──────────────┼─────────────────────────
            2 │     16      10       26
              │ 61.538  38.462  100.000
──────────────┼─────────────────────────
            3 │     55      12       67
              │ 82.090  17.910  100.000
──────────────┼─────────────────────────
        Total │    115      74      189
              │ 60.847  39.153  100.000
──────────────┴─────────────────────────
Pearson chi-square = 21.7790 (2), p < 0.0001

2.e Frequency table with column percentages alone

julia> tab(lbw, :Race, :Smoke, pct = :c)
──────────────┬───────────────────────────
 Race / Smoke │       0        1    Total 
──────────────┼───────────────────────────
            1 │      44       52       96
              │  38.261   70.270   50.794
──────────────┼───────────────────────────
            2 │      16       10       26
              │  13.913   13.514   13.757
──────────────┼───────────────────────────
            3 │      55       12       67
              │  47.826   16.216   35.450
──────────────┼───────────────────────────
        Total │     115       74      189
              │ 100.000  100.000  100.000
──────────────┴───────────────────────────
Pearson chi-square = 21.7790 (2), p < 0.0001

2.f Frequency table with cell percentages alone

julia> tab(lbw, :Race, :Smoke, pct = :e)
──────────────┬─────────────────────────
 Race / Smoke │      0       1    Total 
──────────────┼─────────────────────────
            1 │     44      52       96
              │ 23.280  27.513   50.794
──────────────┼─────────────────────────
            2 │     16      10       26
              │  8.466   5.291   13.757
──────────────┼─────────────────────────
            3 │     55      12       67
              │ 29.101   6.349   35.450
──────────────┼─────────────────────────
        Total │    115      74      189
              │ 60.847  39.153  100.000
──────────────┴─────────────────────────
Pearson chi-square = 21.7790 (2), p < 0.0001

2.g Frequency table with row and column percentages

julia> tab(lbw, :Race, :Smoke, pct = :rc)
──────────────┬───────────────────────────
 Race / Smoke │       0        1    Total 
──────────────┼───────────────────────────
            1 │      44       52       96
              │  45.833   54.167  100.000
              │  38.261   70.270   50.794
──────────────┼───────────────────────────
            2 │      16       10       26
              │  61.538   38.462  100.000
              │  13.913   13.514   13.757
──────────────┼───────────────────────────
            3 │      55       12       67
              │  82.090   17.910  100.000
              │  47.826   16.216   35.450
──────────────┼───────────────────────────
        Total │     115       74      189
              │  60.847   39.153  100.000
              │ 100.000  100.000  100.000
──────────────┴───────────────────────────
Pearson chi-square = 21.7790 (2), p < 0.0001

2.h Frequency table with summary values (mean, standard deviation, and count) of another variable

julia> tab(lbw, :Race, :Smoke, summarize = :BWt)
──────────────┬──────────────────────────────
 Race / Smoke │        0         1     Total 
──────────────┼──────────────────────────────
            1 │ 3428.750  2827.385  3103.010
              │  710.099   626.684   727.872
              │       44        52        96
──────────────┼──────────────────────────────
            2 │ 2854.500  2504.000  2719.692
              │  621.254   637.057   638.684
              │       16        10        26
──────────────┼──────────────────────────────
            3 │ 2814.236  2757.167  2804.015
              │  708.261   810.045   721.301
              │       55        12        67
──────────────┼──────────────────────────────
        Total │ 3054.957  2772.297  2944.286
              │  752.409   659.807   729.016
              │      115        74       189
──────────────┴──────────────────────────────

3. Three-way frequency table

3.a Frequency table

julia> tab(lbw, :Race, :Smoke, :UI)


UI = 0

──────────────┬───────────────────────────
 Race / Smoke │       0        1    Total 
──────────────┼───────────────────────────
            1 │      40       43       83
              │  48.193   51.807  100.000
              │  40.000   70.492   51.553
              │  24.845   26.708   51.553
──────────────┼───────────────────────────
            2 │      13       10       23
              │  56.522   43.478  100.000
              │  13.000   16.393   14.286
              │   8.075    6.211   14.286
──────────────┼───────────────────────────
            3 │      47        8       55
              │  85.455   14.545  100.000
              │  47.000   13.115   34.161
              │  29.193    4.969   34.161
──────────────┼───────────────────────────
        Total │     100       61      161
              │  62.112   37.888  100.000
              │ 100.000  100.000  100.000
              │  62.112   37.888  100.000
──────────────┴───────────────────────────
Pearson chi-square = 19.8732 (2), p < 0.0001


UI = 1

──────────────┬───────────────────────────
 Race / Smoke │       0        1    Total 
──────────────┼───────────────────────────
            1 │       4        9       13
              │  30.769   69.231  100.000
              │  26.667   69.231   46.429
              │  14.286   32.143   46.429
──────────────┼───────────────────────────
            2 │       3        0        3
              │ 100.000    0.000  100.000
              │  20.000    0.000   10.714
              │  10.714    0.000   10.714
──────────────┼───────────────────────────
            3 │       8        4       12
              │  66.667   33.333  100.000
              │  53.333   30.769   42.857
              │  28.571   14.286   42.857
──────────────┼───────────────────────────
        Total │      15       13       28
              │  53.571   46.429  100.000
              │ 100.000  100.000  100.000
              │  53.571   46.429  100.000
──────────────┴───────────────────────────
Pearson chi-square = 6.1449 (2), p = 0.0463075

3.b Summarize birthweight (BWt) by three variables

julia> tab(lbw, :Race, :Smoke, :UI, summarize = :BWt)


UI = 0

──────────────┬──────────────────────────────
 Race / Smoke │        0         1     Total 
──────────────┼──────────────────────────────
            1 │ 3494.500  2874.163  3173.120
              │  622.518   634.652   698.474
              │       40        43        83
──────────────┼──────────────────────────────
            2 │ 3002.615  2504.000  2785.826
              │  583.831   637.057   644.843
              │       13        10        23
──────────────┼──────────────────────────────
            3 │ 2884.617  3104.750  2916.636
              │  700.495   407.027   667.539
              │       47         8        55
──────────────┼──────────────────────────────
        Total │ 3143.910  2843.721  3030.174
              │  711.463   625.409   693.696
              │      100        61       161
──────────────┴──────────────────────────────


UI = 1

──────────────┬──────────────────────────────
 Race / Smoke │        0         1     Total 
──────────────┼──────────────────────────────
            1 │ 2771.250  2603.889  2655.385
              │ 1247.209   566.666   780.654
              │        4         9        13
──────────────┼──────────────────────────────
            2 │ 2212.667         .  2212.667
              │  298.329         .   298.329
              │        3         0         3
──────────────┼──────────────────────────────
            3 │ 2400.750  2062.000  2287.833
              │  645.396  1026.103   761.602
              │        8         4        12
──────────────┼──────────────────────────────
        Total │ 2461.933  2437.154  2450.429
              │  772.723   738.281   742.977
              │       15        13        28
──────────────┴──────────────────────────────

Name		Name	Last commit message	Last commit date
Latest commit History 153 Commits
src		src
test		test
LICENSE		LICENSE
Project.toml		Project.toml
README.md		README.md

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FreqTools

Installation

Syntax

Options:

Examples

1. One-way frequency table

1.a Frequencies

1.b Summarize birthweight by smoking status

1.c Frequency sorted by counts

2. Two-way frequency table

2.a Frequency table with row, column, and cell percentages (default)

2.b Pearson chi-square test for a matrix of counts

2.c Frequency table with no percentages

2.d Frequency table with row percentages alone

2.e Frequency table with column percentages alone

2.f Frequency table with cell percentages alone

2.g Frequency table with row and column percentages

2.h Frequency table with summary values (mean, standard deviation, and count) of another variable

3. Three-way frequency table

3.a Frequency table

3.b Summarize birthweight (BWt) by three variables

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mwsohn/FreqTools.jl

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FreqTools

Installation

Syntax

Options:

Examples

1. One-way frequency table

1.a Frequencies

1.b Summarize birthweight by smoking status

1.c Frequency sorted by counts

2. Two-way frequency table

2.a Frequency table with row, column, and cell percentages (default)

2.b Pearson chi-square test for a matrix of counts

2.c Frequency table with no percentages

2.d Frequency table with row percentages alone

2.e Frequency table with column percentages alone

2.f Frequency table with cell percentages alone

2.g Frequency table with row and column percentages

2.h Frequency table with summary values (mean, standard deviation, and count) of another variable

3. Three-way frequency table

3.a Frequency table

3.b Summarize birthweight (BWt) by three variables

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