# Descriptive/Summary Statistics with descriptr

February 19, 2019
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We are pleased to introduce the descriptr package, a set of tools for
generating descriptive/summary statistics.

## Installation

``````# Install release version from CRAN
install.packages("descriptr")

# Install development version from GitHub
# install.packages("devtools")

## Shiny App

descriptr includes a shiny app which can be launched using

``ds_launch_shiny_app()``

or try the live version here.

descriptr website for
detailed documentation on using the package.

## Data

We have modified the `mtcars` data to create a new data set `mtcarz`. The only
difference between the two data sets is related to the variable types.

``str(mtcarz)``
``````## 'data.frame':    32 obs. of  11 variables:
##  \$ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  \$ cyl : Factor w/ 3 levels "4","6","8": 2 2 1 2 3 2 3 1 1 2 ...
##  \$ disp: num  160 160 108 258 360 ...
##  \$ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
##  \$ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  \$ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  \$ qsec: num  16.5 17 18.6 19.4 17 ...
##  \$ vs  : Factor w/ 2 levels "0","1": 1 1 2 2 1 2 1 2 2 2 ...
##  \$ am  : Factor w/ 2 levels "0","1": 2 2 2 1 1 1 1 1 1 1 ...
##  \$ gear: Factor w/ 3 levels "3","4","5": 2 2 2 1 1 1 1 2 2 2 ...
##  \$ carb: Factor w/ 6 levels "1","2","3","4",..: 4 4 1 1 2 1 4 2 2 4 ...``````

## Data Screening

The `ds_screener()` function will screen a data set and return the following:
â€“ Column/Variable Names
â€“ Data Type
â€“ Levels (in case of categorical data)
â€“ Number of missing observations
â€“ % of missing observations

``ds_screener(mtcarz)``
``````## -----------------------------------------------------------------------
## |  Column Name  |  Data Type  |  Levels   |  Missing  |  Missing (%)  |
## -----------------------------------------------------------------------
## |      mpg      |   numeric   |    NA     |     0     |       0       |
## |      cyl      |   factor    |   4 6 8   |     0     |       0       |
## |     disp      |   numeric   |    NA     |     0     |       0       |
## |      hp       |   numeric   |    NA     |     0     |       0       |
## |     drat      |   numeric   |    NA     |     0     |       0       |
## |      wt       |   numeric   |    NA     |     0     |       0       |
## |     qsec      |   numeric   |    NA     |     0     |       0       |
## |      vs       |   factor    |    0 1    |     0     |       0       |
## |      am       |   factor    |    0 1    |     0     |       0       |
## |     gear      |   factor    |   3 4 5   |     0     |       0       |
## |     carb      |   factor    |1 2 3 4 6 8|     0     |       0       |
## -----------------------------------------------------------------------
##
##  Overall Missing Values           0
##  Percentage of Missing Values     0 %
##  Rows with Missing Values         0
##  Columns With Missing Values      0``````

## Continuous Data

### Summary Statistics

The `ds_summary_stats()` function returns a comprehensive set of statistics
including measures of location, variation, symmetry and extreme observations.

``ds_summary_stats(mtcarz, mpg)``
``````## ------------------------------ Variable: mpg ------------------------------
##
##                         Univariate Analysis
##
##  N                       32.00      Variance                36.32
##  Missing                  0.00      Std Deviation            6.03
##  Mean                    20.09      Range                   23.50
##  Median                  19.20      Interquartile Range      7.38
##  Mode                    10.40      Uncorrected SS       14042.31
##  Trimmed Mean            19.95      Corrected SS          1126.05
##  Skewness                 0.67      Coeff Variation         30.00
##  Kurtosis                -0.02      Std Error Mean           1.07
##
##                               Quantiles
##
##               Quantile                            Value
##
##              Max                                  33.90
##              99%                                  33.44
##              95%                                  31.30
##              90%                                  30.09
##              Q3                                   22.80
##              Median                               19.20
##              Q1                                   15.43
##              10%                                  14.34
##              5%                                   12.00
##              1%                                   10.40
##              Min                                  10.40
##
##                             Extreme Values
##
##                 Low                                High
##
##   Obs                        Value       Obs                        Value
##   15                         10.4        20                         33.9
##   16                         10.4        18                         32.4
##   24                         13.3        19                         30.4
##    7                         14.3        28                         30.4
##   17                         14.7        26                         27.3``````

You can pass multiple variables as shown below:

``ds_summary_stats(mtcarz, mpg, disp)``
``````## ------------------------------ Variable: mpg ------------------------------
##
##                         Univariate Analysis
##
##  N                       32.00      Variance                36.32
##  Missing                  0.00      Std Deviation            6.03
##  Mean                    20.09      Range                   23.50
##  Median                  19.20      Interquartile Range      7.38
##  Mode                    10.40      Uncorrected SS       14042.31
##  Trimmed Mean            19.95      Corrected SS          1126.05
##  Skewness                 0.67      Coeff Variation         30.00
##  Kurtosis                -0.02      Std Error Mean           1.07
##
##                               Quantiles
##
##               Quantile                            Value
##
##              Max                                  33.90
##              99%                                  33.44
##              95%                                  31.30
##              90%                                  30.09
##              Q3                                   22.80
##              Median                               19.20
##              Q1                                   15.43
##              10%                                  14.34
##              5%                                   12.00
##              1%                                   10.40
##              Min                                  10.40
##
##                             Extreme Values
##
##                 Low                                High
##
##   Obs                        Value       Obs                        Value
##   15                         10.4        20                         33.9
##   16                         10.4        18                         32.4
##   24                         13.3        19                         30.4
##    7                         14.3        28                         30.4
##   17                         14.7        26                         27.3
##
##
##
## ------------------------------ Variable: disp -----------------------------
##
##                           Univariate Analysis
##
##  N                         32.00      Variance               15360.80
##  Missing                    0.00      Std Deviation            123.94
##  Mean                     230.72      Range                    400.90
##  Median                   196.30      Interquartile Range      205.18
##  Mode                     275.80      Uncorrected SS       2179627.47
##  Trimmed Mean             228.00      Corrected SS          476184.79
##  Skewness                   0.42      Coeff Variation           53.72
##  Kurtosis                  -1.07      Std Error Mean            21.91
##
##                                 Quantiles
##
##                Quantile                              Value
##
##               Max                                    472.00
##               99%                                    468.28
##               95%                                    449.00
##               90%                                    396.00
##               Q3                                     326.00
##               Median                                 196.30
##               Q1                                     120.83
##               10%                                    80.61
##               5%                                     77.35
##               1%                                     72.53
##               Min                                    71.10
##
##                               Extreme Values
##
##                  Low                                  High
##
##   Obs                          Value       Obs                          Value
##   20                           71.1        15                            472
##   19                           75.7        16                            460
##   18                           78.7        17                            440
##   26                            79         25                            400
##   28                           95.1         5                            360``````

If you do not specify any variables, it will detect all the continuous
variables in the data set and return summary statistics for each of them.

### Frequency Distribution

The `ds_freq_table()` function creates frequency tables for continuous variables.
The default number of intervals is 5.

``ds_freq_table(mtcarz, mpg, 4)``
``````##                                 Variable: mpg
## |---------------------------------------------------------------------------|
## |      Bins       | Frequency | Cum Frequency |   Percent    | Cum Percent  |
## |---------------------------------------------------------------------------|
## |  10.4  -  16.3  |    10     |      10       |    31.25     |    31.25     |
## |---------------------------------------------------------------------------|
## |  16.3  -  22.1  |    13     |      23       |    40.62     |    71.88     |
## |---------------------------------------------------------------------------|
## |  22.1  -   28   |     5     |      28       |    15.62     |     87.5     |
## |---------------------------------------------------------------------------|
## |   28   -  33.9  |     4     |      32       |     12.5     |     100      |
## |---------------------------------------------------------------------------|
## |      Total      |    32     |       -       |    100.00    |      -       |
## |---------------------------------------------------------------------------|``````

#### Histogram

A `plot()` method has been defined which will generate a histogram.

``````k <- ds_freq_table(mtcarz, mpg, 4)
plot(k)``````

### Auto Summary

If you want to view summary statistics and frequency tables of all or subset of
variables in a data set, use `ds_auto_summary()`.

``ds_auto_summary_stats(mtcarz, disp, mpg)``
``````## ------------------------------ Variable: disp -----------------------------
##
## ---------------------------- Summary Statistics ---------------------------
##
## ------------------------------ Variable: disp -----------------------------
##
##                           Univariate Analysis
##
##  N                         32.00      Variance               15360.80
##  Missing                    0.00      Std Deviation            123.94
##  Mean                     230.72      Range                    400.90
##  Median                   196.30      Interquartile Range      205.18
##  Mode                     275.80      Uncorrected SS       2179627.47
##  Trimmed Mean             228.00      Corrected SS          476184.79
##  Skewness                   0.42      Coeff Variation           53.72
##  Kurtosis                  -1.07      Std Error Mean            21.91
##
##                                 Quantiles
##
##                Quantile                              Value
##
##               Max                                    472.00
##               99%                                    468.28
##               95%                                    449.00
##               90%                                    396.00
##               Q3                                     326.00
##               Median                                 196.30
##               Q1                                     120.83
##               10%                                    80.61
##               5%                                     77.35
##               1%                                     72.53
##               Min                                    71.10
##
##                               Extreme Values
##
##                  Low                                  High
##
##   Obs                          Value       Obs                          Value
##   20                           71.1        15                            472
##   19                           75.7        16                            460
##   18                           78.7        17                            440
##   26                            79         25                            400
##   28                           95.1         5                            360
##
##
##
## NULL
##
##
## -------------------------- Frequency Distribution -------------------------
##
##                                Variable: disp
## |---------------------------------------------------------------------------|
## |      Bins       | Frequency | Cum Frequency |   Percent    | Cum Percent  |
## |---------------------------------------------------------------------------|
## |  71.1  - 151.3  |    12     |      12       |     37.5     |     37.5     |
## |---------------------------------------------------------------------------|
## | 151.3  - 231.5  |     5     |      17       |    15.62     |    53.12     |
## |---------------------------------------------------------------------------|
## | 231.5  - 311.6  |     6     |      23       |    18.75     |    71.88     |
## |---------------------------------------------------------------------------|
## | 311.6  - 391.8  |     5     |      28       |    15.62     |     87.5     |
## |---------------------------------------------------------------------------|
## | 391.8  -  472   |     4     |      32       |     12.5     |     100      |
## |---------------------------------------------------------------------------|
## |      Total      |    32     |       -       |    100.00    |      -       |
## |---------------------------------------------------------------------------|
##
##
## ------------------------------ Variable: mpg ------------------------------
##
## ---------------------------- Summary Statistics ---------------------------
##
## ------------------------------ Variable: mpg ------------------------------
##
##                         Univariate Analysis
##
##  N                       32.00      Variance                36.32
##  Missing                  0.00      Std Deviation            6.03
##  Mean                    20.09      Range                   23.50
##  Median                  19.20      Interquartile Range      7.38
##  Mode                    10.40      Uncorrected SS       14042.31
##  Trimmed Mean            19.95      Corrected SS          1126.05
##  Skewness                 0.67      Coeff Variation         30.00
##  Kurtosis                -0.02      Std Error Mean           1.07
##
##                               Quantiles
##
##               Quantile                            Value
##
##              Max                                  33.90
##              99%                                  33.44
##              95%                                  31.30
##              90%                                  30.09
##              Q3                                   22.80
##              Median                               19.20
##              Q1                                   15.43
##              10%                                  14.34
##              5%                                   12.00
##              1%                                   10.40
##              Min                                  10.40
##
##                             Extreme Values
##
##                 Low                                High
##
##   Obs                        Value       Obs                        Value
##   15                         10.4        20                         33.9
##   16                         10.4        18                         32.4
##   24                         13.3        19                         30.4
##    7                         14.3        28                         30.4
##   17                         14.7        26                         27.3
##
##
##
## NULL
##
##
## -------------------------- Frequency Distribution -------------------------
##
##                               Variable: mpg
## |-----------------------------------------------------------------------|
## |    Bins     | Frequency | Cum Frequency |   Percent    | Cum Percent  |
## |-----------------------------------------------------------------------|
## | 10.4 - 15.1 |     6     |       6       |    18.75     |    18.75     |
## |-----------------------------------------------------------------------|
## | 15.1 - 19.8 |    12     |      18       |     37.5     |    56.25     |
## |-----------------------------------------------------------------------|
## | 19.8 - 24.5 |     8     |      26       |      25      |    81.25     |
## |-----------------------------------------------------------------------|
## | 24.5 - 29.2 |     2     |      28       |     6.25     |     87.5     |
## |-----------------------------------------------------------------------|
## | 29.2 - 33.9 |     4     |      32       |     12.5     |     100      |
## |-----------------------------------------------------------------------|
## |    Total    |    32     |       -       |    100.00    |      -       |
## |-----------------------------------------------------------------------|``````

### Group Summary

The `ds_group_summary()` function returns descriptive statistics of a continuous
variable for the different levels of a categorical variable.

``````k <- ds_group_summary(mtcarz, cyl, mpg)
k``````
``````##                                        mpg by cyl
## -----------------------------------------------------------------------------------------
## |     Statistic/Levels|                    4|                    6|                    8|
## -----------------------------------------------------------------------------------------
## |                  Obs|                   11|                    7|                   14|
## |              Minimum|                 21.4|                 17.8|                 10.4|
## |              Maximum|                 33.9|                 21.4|                 19.2|
## |                 Mean|                26.66|                19.74|                 15.1|
## |               Median|                   26|                 19.7|                 15.2|
## |                 Mode|                 22.8|                   21|                 10.4|
## |       Std. Deviation|                 4.51|                 1.45|                 2.56|
## |             Variance|                20.34|                 2.11|                 6.55|
## |             Skewness|                 0.35|                -0.26|                -0.46|
## |             Kurtosis|                -1.43|                -1.83|                 0.33|
## |       Uncorrected SS|              8023.83|              2741.14|              3277.34|
## |         Corrected SS|               203.39|                12.68|                 85.2|
## |      Coeff Variation|                16.91|                 7.36|                16.95|
## |      Std. Error Mean|                 1.36|                 0.55|                 0.68|
## |                Range|                 12.5|                  3.6|                  8.8|
## |  Interquartile Range|                  7.6|                 2.35|                 1.85|
## -----------------------------------------------------------------------------------------``````

`ds_group_summary()` returns a tibble which can be used for further analysis.

``k\$tidy_stats``
``````## # A tibble: 3 x 15
##   cyl   length   min   max  mean median  mode    sd variance skewness
##
## 1 4         11  21.4  33.9  26.7   26    22.8  4.51    20.3     0.348
## 2 6          7  17.8  21.4  19.7   19.7  21    1.45     2.11   -0.259
## 3 8         14  10.4  19.2  15.1   15.2  10.4  2.56     6.55   -0.456
## # ... with 5 more variables: kurtosis , coeff_var ,
## #   std_error , range , iqr ``````

#### Box Plot

A `plot()` method has been defined for comparing distributions.

``````k <- ds_group_summary(mtcarz, cyl, mpg)
plot(k)``````

### Multiple Variables

If you want grouped summary statistics for multiple variables in a data set, use
`ds_auto_group_summary()`.

``ds_auto_group_summary(mtcarz, cyl, gear, mpg)``
``````##                                        mpg by cyl
## -----------------------------------------------------------------------------------------
## |     Statistic/Levels|                    4|                    6|                    8|
## -----------------------------------------------------------------------------------------
## |                  Obs|                   11|                    7|                   14|
## |              Minimum|                 21.4|                 17.8|                 10.4|
## |              Maximum|                 33.9|                 21.4|                 19.2|
## |                 Mean|                26.66|                19.74|                 15.1|
## |               Median|                   26|                 19.7|                 15.2|
## |                 Mode|                 22.8|                   21|                 10.4|
## |       Std. Deviation|                 4.51|                 1.45|                 2.56|
## |             Variance|                20.34|                 2.11|                 6.55|
## |             Skewness|                 0.35|                -0.26|                -0.46|
## |             Kurtosis|                -1.43|                -1.83|                 0.33|
## |       Uncorrected SS|              8023.83|              2741.14|              3277.34|
## |         Corrected SS|               203.39|                12.68|                 85.2|
## |      Coeff Variation|                16.91|                 7.36|                16.95|
## |      Std. Error Mean|                 1.36|                 0.55|                 0.68|
## |                Range|                 12.5|                  3.6|                  8.8|
## |  Interquartile Range|                  7.6|                 2.35|                 1.85|
## -----------------------------------------------------------------------------------------
##
##
##
##                                        mpg by gear
## -----------------------------------------------------------------------------------------
## |     Statistic/Levels|                    3|                    4|                    5|
## -----------------------------------------------------------------------------------------
## |                  Obs|                   15|                   12|                    5|
## |              Minimum|                 10.4|                 17.8|                   15|
## |              Maximum|                 21.5|                 33.9|                 30.4|
## |                 Mean|                16.11|                24.53|                21.38|
## |               Median|                 15.5|                 22.8|                 19.7|
## |                 Mode|                 10.4|                   21|                   15|
## |       Std. Deviation|                 3.37|                 5.28|                 6.66|
## |             Variance|                11.37|                27.84|                44.34|
## |             Skewness|                -0.09|                  0.7|                 0.56|
## |             Kurtosis|                -0.38|                -0.77|                -1.83|
## |       Uncorrected SS|              4050.52|               7528.9|              2462.89|
## |         Corrected SS|               159.15|               306.29|               177.37|
## |      Coeff Variation|                20.93|                21.51|                31.15|
## |      Std. Error Mean|                 0.87|                 1.52|                 2.98|
## |                Range|                 11.1|                 16.1|                 15.4|
## |  Interquartile Range|                  3.9|                 7.08|                 10.2|
## -----------------------------------------------------------------------------------------``````

## Multiple Variable Statistics

The `ds_tidy_stats()` function returns summary/descriptive statistics for
variables in a data frame/tibble.

``ds_tidy_stats(mtcarz, mpg, disp, hp)``
``````## # A tibble: 3 x 16
##   vars    min   max  mean t_mean median  mode range variance  stdev  skew
##
## 1 disp   71.1 472   231.   228    196.  276.  401.   15361.  124.   0.420
## 2 hp     52   335   147.   144.   123   110   283     4701.   68.6  0.799
## 3 mpg    10.4  33.9  20.1   20.0   19.2  10.4  23.5     36.3   6.03 0.672
## # ... with 5 more variables: kurtosis , coeff_var , q1 ,
## #   q3 , iqrange ``````

### Measures

If you want to view the measure of location, variation, symmetry, percentiles
and extreme observations as tibbles, use the below functions. All of them,
except for `ds_extreme_obs()` will work with single or multiple variables. If
you do not specify the variables, they will return the results for all the
continuous variables in the data set.

#### Measures of Location

``ds_measures_location(mtcarz)``
``````## # A tibble: 6 x 5
##   var     mean trim_mean median   mode
##
## 1 disp  231.      228    196.   276.
## 2 drat    3.60      3.58   3.70   3.07
## 3 hp    147.      144.   123    110
## 4 mpg    20.1      20.0   19.2   10.4
## 5 qsec   17.8      17.8   17.7   17.0
## 6 wt      3.22      3.20   3.32   3.44``````

#### Measures of Variation

``ds_measures_variation(mtcarz)``
``````## # A tibble: 6 x 7
##   var    range     iqr  variance      sd coeff_var std_error
##
## 1 disp  401.   205.    15361.    124.         53.7   21.9
## 2 drat    2.17   0.840     0.286   0.535      14.9    0.0945
## 3 hp    283     83.5    4701.     68.6        46.7   12.1
## 4 mpg    23.5    7.38     36.3     6.03       30.0    1.07
## 5 qsec    8.40   2.01      3.19    1.79       10.0    0.316
## 6 wt      3.91   1.03      0.957   0.978      30.4    0.173``````

#### Measures of Symmetry

``ds_measures_symmetry(mtcarz)``
``````## # A tibble: 6 x 3
##   var   skewness kurtosis
##
## 1 disp     0.420  -1.07
## 2 drat     0.293  -0.450
## 3 hp       0.799   0.275
## 4 mpg      0.672  -0.0220
## 5 qsec     0.406   0.865
## 6 wt       0.466   0.417``````

#### Percentiles

``ds_percentiles(mtcarz)``
``````## # A tibble: 6 x 12
##   var     min  per1  per5 per10     q1 median     q3  per95  per90  per99
##
## 1 disp  71.1  72.5  77.4  80.6  121.   196.   326    449    396.   468.
## 2 drat   2.76  2.76  2.85  3.01   3.08   3.70   3.92   4.31   4.21   4.78
## 3 hp    52    55.1  63.6  66     96.5  123    180    254.   244.   313.
## 4 mpg   10.4  10.4  12.0  14.3   15.4   19.2   22.8   31.3   30.1   33.4
## 5 qsec  14.5  14.5  15.0  15.5   16.9   17.7   18.9   20.1   20.0   22.1
## 6 wt     1.51  1.54  1.74  1.96   2.58   3.32   3.61   5.29   4.05   5.40
## # ... with 1 more variable: max ``````

## Categorical Data

### Cross Tabulation

The `ds_cross_table()` function creates two way tables of categorical variables.

``ds_cross_table(mtcarz, cyl, gear)``
``````##     Cell Contents
##  |---------------|
##  |     Frequency |
##  |       Percent |
##  |       Row Pct |
##  |       Col Pct |
##  |---------------|
##
##  Total Observations:  32
##
## ----------------------------------------------------------------------------
## |              |                           gear                            |
## ----------------------------------------------------------------------------
## |          cyl |            3 |            4 |            5 |    Row Total |
## ----------------------------------------------------------------------------
## |            4 |            1 |            8 |            2 |           11 |
## |              |        0.031 |         0.25 |        0.062 |              |
## |              |         0.09 |         0.73 |         0.18 |         0.34 |
## |              |         0.07 |         0.67 |          0.4 |              |
## ----------------------------------------------------------------------------
## |            6 |            2 |            4 |            1 |            7 |
## |              |        0.062 |        0.125 |        0.031 |              |
## |              |         0.29 |         0.57 |         0.14 |         0.22 |
## |              |         0.13 |         0.33 |          0.2 |              |
## ----------------------------------------------------------------------------
## |            8 |           12 |            0 |            2 |           14 |
## |              |        0.375 |            0 |        0.062 |              |
## |              |         0.86 |            0 |         0.14 |         0.44 |
## |              |          0.8 |            0 |          0.4 |              |
## ----------------------------------------------------------------------------
## | Column Total |           15 |           12 |            5 |           32 |
## |              |        0.468 |        0.375 |        0.155 |              |
## ----------------------------------------------------------------------------``````

If you want the above result as a tibble, use `ds_twoway_table()`.

``ds_twoway_table(mtcarz, cyl, gear)``
``## Joining, by = c("cyl", "gear", "count")``
``````## # A tibble: 8 x 6
##   cyl   gear  count percent row_percent col_percent
##
## 1 4     3         1  0.0312      0.0909      0.0667
## 2 4     4         8  0.25        0.727       0.667
## 3 4     5         2  0.0625      0.182       0.4
## 4 6     3         2  0.0625      0.286       0.133
## 5 6     4         4  0.125       0.571       0.333
## 6 6     5         1  0.0312      0.143       0.2
## 7 8     3        12  0.375       0.857       0.8
## 8 8     5         2  0.0625      0.143       0.4``````

A `plot()` method has been defined which will generate:

#### Grouped Bar Plots

``````k <- ds_cross_table(mtcarz, cyl, gear)
plot(k)``````

#### Stacked Bar Plots

``````k <- ds_cross_table(mtcarz, cyl, gear)
plot(k, stacked = TRUE)``````

#### Proportional Bar Plots

``````k <- ds_cross_table(mtcarz, cyl, gear)
plot(k, proportional = TRUE)``````

### Frequency Table

The `ds_freq_table()` function creates frequency tables.

``ds_freq_table(mtcarz, cyl)``
``````##                              Variable: cyl
## -----------------------------------------------------------------------
## Levels     Frequency    Cum Frequency       Percent        Cum Percent
## -----------------------------------------------------------------------
##    4          11             11              34.38            34.38
## -----------------------------------------------------------------------
##    6           7             18              21.88            56.25
## -----------------------------------------------------------------------
##    8          14             32              43.75             100
## -----------------------------------------------------------------------
##  Total        32              -             100.00              -
## -----------------------------------------------------------------------``````

A `plot()` method has been defined which will create a bar plot.

``````k <- ds_freq_table(mtcarz, cyl)
plot(k)``````

### Multiple One Way Tables

The `ds_auto_freq_table()` function creates multiple one way tables by creating a
frequency table for each categorical variable in a data set. You can also
specify a subset of variables if you do not want all the variables in the data
set to be used.

``ds_auto_freq_table(mtcarz)``
``````##                              Variable: cyl
## -----------------------------------------------------------------------
## Levels     Frequency    Cum Frequency       Percent        Cum Percent
## -----------------------------------------------------------------------
##    4          11             11              34.38            34.38
## -----------------------------------------------------------------------
##    6           7             18              21.88            56.25
## -----------------------------------------------------------------------
##    8          14             32              43.75             100
## -----------------------------------------------------------------------
##  Total        32              -             100.00              -
## -----------------------------------------------------------------------
##
##                              Variable: vs
## -----------------------------------------------------------------------
## Levels     Frequency    Cum Frequency       Percent        Cum Percent
## -----------------------------------------------------------------------
##    0          18             18              56.25            56.25
## -----------------------------------------------------------------------
##    1          14             32              43.75             100
## -----------------------------------------------------------------------
##  Total        32              -             100.00              -
## -----------------------------------------------------------------------
##
##                              Variable: am
## -----------------------------------------------------------------------
## Levels     Frequency    Cum Frequency       Percent        Cum Percent
## -----------------------------------------------------------------------
##    0          19             19              59.38            59.38
## -----------------------------------------------------------------------
##    1          13             32              40.62             100
## -----------------------------------------------------------------------
##  Total        32              -             100.00              -
## -----------------------------------------------------------------------
##
##                             Variable: gear
## -----------------------------------------------------------------------
## Levels     Frequency    Cum Frequency       Percent        Cum Percent
## -----------------------------------------------------------------------
##    3          15             15              46.88            46.88
## -----------------------------------------------------------------------
##    4          12             27              37.5             84.38
## -----------------------------------------------------------------------
##    5           5             32              15.62             100
## -----------------------------------------------------------------------
##  Total        32              -             100.00              -
## -----------------------------------------------------------------------
##
##                             Variable: carb
## -----------------------------------------------------------------------
## Levels     Frequency    Cum Frequency       Percent        Cum Percent
## -----------------------------------------------------------------------
##    1           7              7              21.88            21.88
## -----------------------------------------------------------------------
##    2          10             17              31.25            53.12
## -----------------------------------------------------------------------
##    3           3             20              9.38             62.5
## -----------------------------------------------------------------------
##    4          10             30              31.25            93.75
## -----------------------------------------------------------------------
##    6           1             31              3.12             96.88
## -----------------------------------------------------------------------
##    8           1             32              3.12              100
## -----------------------------------------------------------------------
##  Total        32              -             100.00              -
## -----------------------------------------------------------------------``````

### Multiple Two Way Tables

The `ds_auto_cross_table()` function creates multiple two way tables by creating a
cross table for each unique pair of categorical variables in a data set. You
can also specify a subset of variables if you do not want all the variables in
the data set to be used.

``ds_auto_cross_table(mtcarz, cyl, gear, am)``
``````##     Cell Contents
##  |---------------|
##  |     Frequency |
##  |       Percent |
##  |       Row Pct |
##  |       Col Pct |
##  |---------------|
##
##  Total Observations:  32
##
##                                 cyl vs gear
## ----------------------------------------------------------------------------
## |              |                           gear                            |
## ----------------------------------------------------------------------------
## |          cyl |            3 |            4 |            5 |    Row Total |
## ----------------------------------------------------------------------------
## |            4 |            1 |            8 |            2 |           11 |
## |              |        0.031 |         0.25 |        0.062 |              |
## |              |         0.09 |         0.73 |         0.18 |         0.34 |
## |              |         0.07 |         0.67 |          0.4 |              |
## ----------------------------------------------------------------------------
## |            6 |            2 |            4 |            1 |            7 |
## |              |        0.062 |        0.125 |        0.031 |              |
## |              |         0.29 |         0.57 |         0.14 |         0.22 |
## |              |         0.13 |         0.33 |          0.2 |              |
## ----------------------------------------------------------------------------
## |            8 |           12 |            0 |            2 |           14 |
## |              |        0.375 |            0 |        0.062 |              |
## |              |         0.86 |            0 |         0.14 |         0.44 |
## |              |          0.8 |            0 |          0.4 |              |
## ----------------------------------------------------------------------------
## | Column Total |           15 |           12 |            5 |           32 |
## |              |        0.468 |        0.375 |        0.155 |              |
## ----------------------------------------------------------------------------
##
##
##                          cyl vs am
## -------------------------------------------------------------
## |              |                     am                     |
## -------------------------------------------------------------
## |          cyl |            0 |            1 |    Row Total |
## -------------------------------------------------------------
## |            4 |            3 |            8 |           11 |
## |              |        0.094 |         0.25 |              |
## |              |         0.27 |         0.73 |         0.34 |
## |              |         0.16 |         0.62 |              |
## -------------------------------------------------------------
## |            6 |            4 |            3 |            7 |
## |              |        0.125 |        0.094 |              |
## |              |         0.57 |         0.43 |         0.22 |
## |              |         0.21 |         0.23 |              |
## -------------------------------------------------------------
## |            8 |           12 |            2 |           14 |
## |              |        0.375 |        0.062 |              |
## |              |         0.86 |         0.14 |         0.44 |
## |              |         0.63 |         0.15 |              |
## -------------------------------------------------------------
## | Column Total |           19 |           13 |           32 |
## |              |        0.594 |        0.406 |              |
## -------------------------------------------------------------
##
##
##                          gear vs am
## -------------------------------------------------------------
## |              |                     am                     |
## -------------------------------------------------------------
## |         gear |            0 |            1 |    Row Total |
## -------------------------------------------------------------
## |            3 |           15 |            0 |           15 |
## |              |        0.469 |            0 |              |
## |              |            1 |            0 |         0.47 |
## |              |         0.79 |            0 |              |
## -------------------------------------------------------------
## |            4 |            4 |            8 |           12 |
## |              |        0.125 |         0.25 |              |
## |              |         0.33 |         0.67 |         0.38 |
## |              |         0.21 |         0.62 |              |
## -------------------------------------------------------------
## |            5 |            0 |            5 |            5 |
## |              |            0 |        0.156 |              |
## |              |            0 |            1 |         0.16 |
## |              |            0 |         0.38 |              |
## -------------------------------------------------------------
## | Column Total |           19 |           13 |           32 |
## |              |        0.594 |        0.406 |              |
## -------------------------------------------------------------``````

## Visualization

descriptr can help visualize multiple variables by automatically
detecting their data types.

### Continuous Data

``ds_plot_scatter(mtcarz, mpg, disp, hp)``

### Categorical Data

``ds_plot_bar_stacked(mtcarz, cyl, gear, am)``

## Learning More

The descriptr website includes
comprehensive documentation on using the package, including the following
articles that cover various aspects of using rfm:

## Feedback

All feedback is welcome. Issues (bugs and feature
requests) can be posted to github tracker.
For help with code or other related questions, feel free to reach me [email protected].

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