Skip to content
Data Science Cross Reference Notes: R and Python
HTML
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
Getting_and_Cleaning_Data_cache/html
SGP_adm
Visualization_cache/html
Visualization_files/figure-html
.Rhistory
Getting and Cleaning Data.Rmd
Getting_and_Cleaning_Data.html
Getting_and_Cleaning_Data.md
Linear Algebra.Rmd
Linear_Algebra.html
Linear_Algebra.md
README.md
Random Number Generation.Rmd
Random_Number_Generation.html
Random_Number_Generation.md
SGP_adm.zip
Visualization.Rmd
Visualization.html
Visualization.md
Working with R workspace.Rmd
Working_with_R_workspace.html
Working_with_R_workspace.md
airquality.csv
iris.csv
iris.xlsx
mtcars.csv

README.md

Data Science Cross Reference Notes

Read Me

This is a set of notes compiled during my data science learning journey.

Many times, I find myself attempting to search and answer the questions below during data collection, analysis and visualization.

  • How do I perform (an action) in (a language)?
  • I know how to implement (an action) in (language A), now how do I implement this in (language B)?

The same process repeats when I am implementing the action in another language. This set of notes thus attempts to be a cross reference between language implementations. At this stage, I will be compiling notes pertaining to R and Python.

The notes follow a certain format for each action:

  1. How do I (action)?
  2. Sample Implementation in R
  3. Sample Implementation in Python

Initial collection includes:

  • Linear Algebra
  • Random Number Generation

Roadmap:

  • Getting and Cleaning Data
  • Data Manipulation
  • Plotting graphs
  • Statistical Functions
  • Regression Models
  • Machine Learning
  • Natural Language Processing
You can’t perform that action at this time.