profiling_num: Profiling numerical data

Description Usage Arguments Value Examples

View source: R/exploratory_data_analysis.R

Description

Get a metric table with many indicators for all numerical variables, automatically skipping the non-numerical variables. Current metrics are: mean, std_dev: standard deviation, all the p_XX: percentile at XX number, skewness, kurtosis, iqr: inter quartile range, variation_coef: the ratio of sd/mean, range_98 is the limit for which the 98

Usage

1

Arguments

data

data frame

Value

metrics table

Examples

1

Example output

Loading required package: Hmisc
Loading required package: lattice
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2

Attaching package: 'Hmisc'

The following objects are masked from 'package:base':

    format.pval, round.POSIXt, trunc.POSIXt, units

sh: 1: cannot create /dev/null: Permission denied
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   variable   mean std_dev variation_coef p_01 p_05  p_25  p_50  p_75  p_95
1       mpg  20.09    6.03           0.30 10.4 12.0  15.4  19.2  22.8  31.3
2       cyl   6.19    1.79           0.29  4.0  4.0   4.0   6.0   8.0   8.0
3      disp 230.72  123.94           0.54 72.5 77.3 120.8 196.3 326.0 449.0
4        hp 146.69   68.56           0.47 55.1 63.6  96.5 123.0 180.0 253.5
5      drat   3.60    0.53           0.15  2.8  2.9   3.1   3.7   3.9   4.3
6        wt   3.22    0.98           0.30  1.5  1.7   2.6   3.3   3.6   5.3
7      qsec  17.85    1.79           0.10 14.5 15.0  16.9  17.7  18.9  20.1
8        vs   0.44    0.50           1.15  0.0  0.0   0.0   0.0   1.0   1.0
9        am   0.41    0.50           1.23  0.0  0.0   0.0   0.0   1.0   1.0
10     gear   3.69    0.74           0.20  3.0  3.0   3.0   4.0   4.0   5.0
11     carb   2.81    1.62           0.57  1.0  1.0   2.0   2.0   4.0   4.9
    p_99 skewness kurtosis    iqr        range_98       range_80
1   33.4     0.64      2.8   7.38   [10.4, 33.44] [14.34, 30.09]
2    8.0    -0.18      1.3   4.00          [4, 8]         [4, 8]
3  468.3     0.40      1.9 205.18 [72.53, 468.28]   [80.61, 396]
4  313.0     0.76      3.1  83.50  [55.1, 312.99]    [66, 243.5]
5    4.8     0.28      2.4   0.84    [2.76, 4.78]   [3.01, 4.21]
6    5.4     0.44      3.2   1.03     [1.54, 5.4]   [1.96, 4.05]
7   22.1     0.39      3.6   2.01  [14.53, 22.07] [15.53, 19.99]
8    1.0     0.25      1.1   1.00          [0, 1]         [0, 1]
9    1.0     0.38      1.1   1.00          [0, 1]         [0, 1]
10   5.0     0.55      2.1   1.00          [3, 5]         [3, 5]
11   7.4     1.10      4.5   2.00       [1, 7.38]         [1, 4]

funModeling documentation built on Sept. 9, 2019, 1:02 a.m.