A translation of the visualisation chapters from “R for Data Science” to Python using Plotnine and Pandas.
This repository contains all the code and text to generate this tutorial. The tutorial is also available as a Jupyter notebook and an R notebook; these are located in the output directory.
To run these notebooks, make sure you have the necessary dependencies installed. After cloning this repository you can:
- Run
make venvto create a virtualenv with Python 3.7, install the packages listed in requirements.txt, and create a Jupyter kernel specification. - Run
make labto start Jupyter Lab using the virtualenv. - Run
make renv/libraryto use to install all the required R packages.
If you change the input source, i.e., input/r4ds-python-plotnine.ipynb.Rmd, you can:
- Run
make ipynbto re-create the Jupyter notebook output/r4ds-python-plotnine.ipynb. - Run
make rmdto re-create the R notebook output/r4ds-python-plotnine.Rmd.
This tutorial and the accompanying code has been written and tested on macOS. I suspect that it also works on other Unix and Linux distributions. I doubt that it works out of the box on Windows. The Makefile and requirements.txt files may provide useful hints on how to install the dependencies.
sessioninfo::session_info()─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 3.6.1 (2019-07-05)
os macOS Mojave 10.14.6
system x86_64, darwin15.6.0
ui X11
language en_US.UTF-8
collate en_US.UTF-8
ctype en_US.UTF-8
tz Europe/Amsterdam
date 2019-12-10
─ Packages ───────────────────────────────────────────────────────────────────
! package * version date lib source
P assertthat 0.2.1 2019-03-21 [?] CRAN (R 3.6.0)
P cli 2.0.0 2019-12-09 [?] CRAN (R 3.6.1)
P crayon 1.3.4 2017-09-16 [?] CRAN (R 3.6.0)
P digest 0.6.23 2019-11-23 [?] CRAN (R 3.6.0)
P evaluate 0.14 2019-05-28 [?] CRAN (R 3.6.0)
P fansi 0.4.0 2018-10-05 [?] CRAN (R 3.6.0)
P glue 1.3.1 2019-03-12 [?] CRAN (R 3.6.0)
P htmltools 0.4.0 2019-10-04 [?] CRAN (R 3.6.0)
P jsonlite 1.6 2018-12-07 [?] CRAN (R 3.6.0)
P knitr * 1.26 2019-11-12 [?] CRAN (R 3.6.0)
P lattice 0.20-38 2018-11-04 [?] CRAN (R 3.6.1)
P magrittr 1.5 2014-11-22 [?] CRAN (R 3.6.0)
P Matrix 1.2-18 2019-11-27 [?] CRAN (R 3.6.0)
P Rcpp 1.0.3 2019-11-08 [?] CRAN (R 3.6.0)
P renv 0.9.2 2019-12-09 [?] CRAN (R 3.6.1)
P reticulate * 1.13 2019-07-24 [?] CRAN (R 3.6.0)
P rlang 0.4.2 2019-11-23 [?] CRAN (R 3.6.0)
P rmarkdown 1.18 2019-11-27 [?] CRAN (R 3.6.0)
P sessioninfo 1.1.1 2018-11-05 [?] CRAN (R 3.6.0)
P stringi 1.4.3 2019-03-12 [?] CRAN (R 3.6.0)
P stringr 1.4.0 2019-02-10 [?] CRAN (R 3.6.0)
P withr 2.1.2 2018-03-15 [?] CRAN (R 3.6.0)
P xfun 0.11 2019-11-12 [?] CRAN (R 3.6.0)
P yaml 2.2.0 2018-07-25 [?] CRAN (R 3.6.0)
[1] /Users/jeroen/repos/datascienceworkshops/r4ds-python-plotnine/renv/library/R-3.6/x86_64-apple-darwin15.6.0
[2] /private/var/folders/8h/88ch3k996hb0t11db8bj9pzh0000gn/T/RtmpF8ov4T/renv-system-library
P ── Loaded and on-disk path mismatch.
. venv/bin/activate && pip freezeadjustText==0.7.3
appnope==0.1.0
attrs==19.3.0
backcall==0.1.0
bleach==3.1.0
cycler==0.10.0
decorator==4.4.1
defusedxml==0.6.0
descartes==1.1.0
entrypoints==0.3
importlib-metadata==1.2.0
ipykernel==5.1.3
ipython==7.10.1
ipython-genutils==0.2.0
ipywidgets==7.5.1
jedi==0.15.1
Jinja2==2.10.3
joblib==0.14.0
jsonschema==3.2.0
jupyter==1.0.0
jupyter-client==5.3.4
jupyter-console==6.0.0
jupyter-core==4.6.1
jupytext==1.3.0
kiwisolver==1.1.0
MarkupSafe==1.1.1
matplotlib==3.1.2
mistune==0.8.4
mizani==0.6.0
more-itertools==8.0.2
nbconvert==5.6.1
nbformat==4.4.0
notebook==6.0.2
numpy==1.17.4
palettable==3.3.0
pandas==0.25.3
pandocfilters==1.4.2
parso==0.5.1
patsy==0.5.1
pexpect==4.7.0
pickleshare==0.7.5
plotnine==0.6.0+23.g3eb58cd
prometheus-client==0.7.1
prompt-toolkit==2.0.10
ptyprocess==0.6.0
Pygments==2.5.2
pyparsing==2.4.5
pyrsistent==0.15.6
python-dateutil==2.8.1
pytz==2019.3
PyYAML==5.2
pyzmq==18.1.1
qtconsole==4.6.0
scikit-learn==0.22
scikit-misc==0.1.1
scipy==1.3.3
Send2Trash==1.5.0
six==1.13.0
statsmodels==0.10.2
terminado==0.8.3
testpath==0.4.4
tornado==6.0.3
traitlets==4.3.3
wcwidth==0.1.7
webencodings==0.5.1
widgetsnbextension==3.5.1
zipp==0.6.0
The tutorial, the Jupyter notebook and the R notebook are licenced, just like the original text, under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License while everything else is licensed under the MIT License.