Code repository

Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python by Peter Bruce, Andrew Bruce, and Peter Gedeck Publisher: O'Reilly Media; 2 edition (June 9, 2020) ISBN-13: 978-1492072942 Errata: http://oreilly.com/catalog/errata.csp?isbn=9781492072942

Setup R and Python environments

R

Run the following commands in R to install all required packages

if (!require(vioplot)) install.packages('vioplot')
if (!require(corrplot)) install.packages('corrplot')
if (!require(gmodels)) install.packages('gmodels')
if (!require(matrixStats)) install.packages('matrixStats')

if (!require(lmPerm)) install.packages('lmPerm')
if (!require(pwr)) install.packages('pwr')

if (!require(FNN)) install.packages('FNN')
if (!require(klaR)) install.packages('klaR')
if (!require(DMwR)) install.packages('DMwR')

if (!require(xgboost)) install.packages('xgboost')

if (!require(ellipse)) install.packages('ellipse')
if (!require(mclust)) install.packages('mclust')
if (!require(ca)) install.packages('ca')

Python

We recommend to use a conda environment to run the Python code.

conda create -n sfds python
conda activate sfds
conda env update -n sfds -f environment.yml

출처

practical-statistics-for-data-scientists-master are copied from github-gedect.
All source code was written with reference to that book.