pyRdatasets

pyRdatasets is a collection of 2293 datasets taken from https://github.com/vincentarelbundock/Rdatasets. The datasets were extracted from various R packages and stored as gzip packed pickle files in pandas DataFrame structure. A description to each dataset can be found here: http://vincentarelbundock.github.io/Rdatasets/datasets.html

All 2293 data records are already included in the package (no internet connection necessary), which has a size around 40 Mb.

Installation

pip install rdatasets

or

conda install conda-forge::rdatasets

Usage

>>> import rdatasets
>>> dataset = rdatasets.data("iris")
>>> dataset
     Sepal.Length  Sepal.Width  Petal.Length  Petal.Width    Species
0             5.1          3.5           1.4          0.2     setosa
1             4.9          3.0           1.4          0.2     setosa
2             4.7          3.2           1.3          0.2     setosa
3             4.6          3.1           1.5          0.2     setosa
4             5.0          3.6           1.4          0.2     setosa
..            ...          ...           ...          ...        ...
145           6.7          3.0           5.2          2.3  virginica
146           6.3          2.5           5.0          1.9  virginica
147           6.5          3.0           5.2          2.0  virginica
148           6.2          3.4           5.4          2.3  virginica
149           5.9          3.0           5.1          1.8  virginica

[150 rows x 5 columns]
>>> rdatasets.data("forecast", "co2")
Could not read forecast/co2
Which item did you mean: ['gas', 'gold', 'taylor', 'wineind', 'woolyrnq']?
>>> rdatasets.data("forecast", "gas")
            time  value
0    1956.000000   1709
1    1956.083333   1646
2    1956.166667   1794
3    1956.250000   1878
4    1956.333333   2173
..           ...    ...
471  1995.250000  49013
472  1995.333333  56624
473  1995.416667  61739
474  1995.500000  66600
475  1995.583333  60054

[476 rows x 2 columns]

The dataset description can be printed by:

import rdatasets
print(rdatasets.descr("iris"))

A summary of all datasets is available as DataFrame object:

import rdatasets
rdatasets.summary()

Thanks to

The archive of datasets distributed with R: of https://github.com/vincentarelbundock/Rdatasets

Pre-commit-config

Installation

$ pip install pre-commit

Using homebrew:

$ brew install pre-commit

$ pre-commit --version
pre-commit 2.10.0

Install the git hook scripts

$ pre-commit install

Run against all the files

pre-commit run --all-files
pre-commit run --show-diff-on-failure --color=always --all-files

Update package rev in pre-commit yaml

pre-commit autoupdate
pre-commit run --show-diff-on-failure --color=always --all-files