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https://github.com/gedeck/practical-statistics-for-data-scientists

Code repository for O'Reilly book
https://github.com/gedeck/practical-statistics-for-data-scientists

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Code repository for O'Reilly book

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README 

        
[![](https://img.shields.io/badge/python-3.8--3.12-blue.svg)](https://www.python.org/downloads/)

![Python](https://github.com/gedeck/dmba/actions/workflows/build.yml/badge.svg)



# Code repository



 

  

  

   
Practical Statistics for Data Scientists:



   
50+ Essential Concepts Using R and Python


by Peter Bruce, Andrew Bruce, and Peter Gedeck



   


    

  



## Online

View the notebooks online:

[![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.jupyter.org/github/gedeck/practical-statistics-for-data-scientists/tree/master/)



Excecute the notebooks in Binder:

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/gedeck/practical-statistics-for-data-scientists/HEAD)



 This can take some time if the binder environment needs to be rebuilt.



## Other language versions



  

    

    English:


     Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python


     2020: ISBN 149207294X


     Google books,

     Amazon

    

  



  

    

    Japanese (2020-06-11):


     データサイエンスのための統計学入門 第2版 ―予測、分類、統計モデリング、統計的機械学習とR/Pythonプログラミング 


     2020: ISBN 978-4-873-11926-7,

     Shinya Ohashi (supervised), Toshiaki Kurokawa (translated), O'Reilly Japan Inc.


     Google books,

     Amazon,

     Order here

    

  



  

    

    German (2021-03-29):


     Praktische Statistik für Data Scientists: 50+ essenzielle Konzepte mit R und Python 


     2021: ISBN 978-3-960-09153-0, Marcus Fraaß (Übersetzer), dpunkt.verlag GmbH


     Google books,

     Amazon

     Order here

    

  



  

    

    Korean (2021-05-07):


     Practical Statistics for Data Scientists: 데이터 과학을 위한 통계(2판)


     2021: ISBN 979-1-162-24418-0, Junyong Lee (translation), Hanbit Media, Inc.

     


     Google books,

     Order here

    

  



  

    

    Polish (2021-06-16):


     Statystyka praktyczna w data science. 50 kluczowych zagadnien w jezykach R i Python


     2021: ISBN 978-8-328-37427-0, Helion

     


     Google books,

     Amazon,

     Order here

    

  



  

    

    Russian (2021-05-31):


     Практическая статистика для специалистов Data Science, 2-е изд.


     2021: ISBN 978-5-9775-6705-3, BHV St Petersburg

     


     Google books,

     Order here

    

  



  

   

   Chinese complex (2021-07-29):


    Practical Statistics for Data Scientists: 資料科學家的實用統計學 第二版


    2021: ISBN 978-9-865-02841-1, Hong Weien (translation), GoTop Information Inc.

    


    

    Order here

  



  

   

    

    Chinese simplified (2021-10-15):


     Practical Statistics for Data Scientists: 数据科学中的实用统计学（第2版）


     2021: ISBN 978-7-115-56902-8, Chen Guangxin (translation), Posts & Telecom Press

     


     

     Order here

    

  

  

    

    English (Indian subcontinent & select countries only):


     Practical Statistics for Data Scientists: 50+ Essential Concepts Using R And Python, Second Edition


     2021: ISBN 978-8-194-43500-6, Shroff Publishers and Distributors Pvt. Ltd.

     


     

     Order here

    

  

  

    

    Spanish (2022-02-22):


     Estadística práctica para ciencia de datos con R y Python, Second Edition


     2022: ISBN 978-8-426-73443-3, Marcombo S.A.

     


     Google books,

     Amazon,

     Order here

    

  



## See also

- The code repository for the first edition is at: https://github.com/andrewgbruce/statistics-for-data-scientists



# Setup of R and Python environments



We recommend using a conda environment to run the Python and R code.



```

conda create -n sfds #Create the conda environment named sfds.

conda activate sfds #Activate the environment we created.

conda env update -n sfds -f environment.yml #Update the depencies of the environment from environment.yml 

```



The full list of Python and R dependencies from the [environment.yml](environment.yml) file:



```

python

jupyter

pandas

matplotlib

scipy

statsmodels

wquantiles

seaborn

scikit-learn

pygam

dmba

pydotplus

imbalanced-learn

prince

xgboost

graphviz

numpy

adjustText

r-essentials

r-base

r-vioplot

r-corrplot

r-gmodels

r-matrixstats

r-lmperm

r-pwr

r-fnn

r-klar

r-dmwr

r-xgboost

r-ellipse

r-mclust

r-ca

r-ggplot2

r-irkernel

r-boot

r-randomforest

```