This is going to be a slow developping project because 1) I'm a bit rusty in Python and 2) I don't have much free time. So if you'd like to contribute by all means do!
To see what summarytools is all about, see summarytools: An R Package For Descriptive Statistics
Just copy the summarytools.py file in your Python/Lib/site-packages folder.
First, a quick setup
import pandas as pd
from summarytools import freqImport a sample dataset:
link = "https://raw.githubusercontent.com/dcomtois/summarytools-python/master/data/tobacco.csv"
tobacco = pd.read_csv(link)freq(tobacco.age_gr) Freq % Valid % Valid Cum. % Total % Total Cum.
----- ------ --------- -------------- --------- --------------
18-34 258 26.46 26.46 25.80 25.80
35-50 241 24.72 51.18 24.10 49.90
51-70 317 32.51 83.69 31.70 81.60
71 + 159 16.31 100.00 15.90 97.50
NaN 25 2.50 100.00
Total 1000 100.00 100.00 100.00 100.00
The returned object is a pandas Dataframe, and it is displayed using the tabulate library.
When switching format to 'pipe', we get pretty formatted markdown tables where mardown is supported, such as here on GitHub.
freq(tobacco.gender, format = 'pipe')| | Freq | % Valid | % Valid Cum. | % Total | % Total Cum. |
|:------|-------:|----------:|---------------:|----------:|---------------:|
| F | 489 | 50.00 | 50.00 | 48.90 | 48.90 |
| M | 489 | 50.00 | 100.00 | 48.90 | 97.80 |
| NaN | 22 | | | 2.20 | 100.00 |
| Total | 978 | 100.00 | 100.00 | 100.00 | 100.00 |
When working in a regular Python console or in IPython, the 'fancy_grid' format from tabular produces good results:
freq(tobacco.gender, format = 'fancy_grid')╒═══════╤════════╤═══════════╤════════════════╤═══════════╤════════════════╕
│ │ Freq │ % Valid │ % Valid Cum. │ % Total │ % Total Cum. │
╞═══════╪════════╪═══════════╪════════════════╪═══════════╪════════════════╡
│ F │ 489 │ 50.00 │ 50.00 │ 48.90 │ 48.90 │
├───────┼────────┼───────────┼────────────────┼───────────┼────────────────┤
│ M │ 489 │ 50.00 │ 100.00 │ 48.90 │ 97.80 │
├───────┼────────┼───────────┼────────────────┼───────────┼────────────────┤
│ NaN │ 22 │ │ │ 2.20 │ 100.00 │
├───────┼────────┼───────────┼────────────────┼───────────┼────────────────┤
│ Total │ 1000 │ 100.00 │ 100.00 │ 100.00 │ 100.00 │
╘═══════╧════════╧═══════════╧════════════════╧═══════════╧════════════════╛
For now, only a few parameters are implemented. We'll store a frequency table to show how we can tweak the display after its creation, using the print() method.
ft = freq(tobacco.gender, format = 'pipe')ft.print(totals=False)| Freq | % Valid | % Valid Cum. | % Total | % Total Cum. | |
|---|---|---|---|---|---|
| F | 489 | 50.00 | 50.00 | 48.90 | 48.90 |
| M | 489 | 50.00 | 100.00 | 48.90 | 97.80 |
| NaN | 22 | 2.20 | 100.00 |
ft.print(nans=False)| Freq | % Valid | % Valid Cum. | |
|---|---|---|---|
| F | 489 | 50.00 | 50.00 |
| M | 489 | 50.00 | 100.00 |
| Total | 978 | 100.00 | 100.00 |
ft.print(digits=1)| Freq | % Valid | % Valid Cum. | % Total | % Total Cum. | |
|---|---|---|---|---|---|
| F | 489 | 50.0 | 50.0 | 48.9 | 48.9 |
| M | 489 | 50.0 | 100.0 | 48.9 | 97.8 |
| NaN | 22 | 2.2 | 100.0 | ||
| Total | 978 | 100.0 | 100.0 | 100.0 | 100.0 |
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