There are many great websites online which offer courses to start with Python or R from scratch or just brush up on a few topics. Thereof, I can wholeheartedly recommend DataCamp.com. But of course you don’t need to spend money to learn either Python nor R. Below you can find a list of great free resources and there is a ton more out there.
Python
Working with data
For reading the most common files to manipulating tabular data, there is no way around knowing pandas. Below are two links, which should get you up and running with the package.
Visualization
There are many great visualization libraries for Python. Among them, matplotlib is certainly the most famous one, even if it is not always the easiest one to use. Next to matplotlib, I personally really prefer a library called altair, which offers a more intuitive and straight forward way to visualizing your data. You can find tutorials on both in the links below:
- An Introduction to Altair - vallandingham.me
- Jupyter Notebooks for Altair - github.com <- Click on the “launch binder” button to try the examples live in your browser! (If you want to know how this works, check out the section on mybinder and repo2docker.)
- Jake VanderPlas - Exploratory Data Visualization with Vega, Vega-Lite, and Altair - PyCon 2018 - youtube.com
- Matplotlib Beginner’s Guide - matplotlib.org
- Python Plotting With Matplotlib (Guide) - realpython.com
R
If you want to work with R, you should definitely take a look at the tidyverse, which is an “opinionated collection of R packages designed for data science.” It offers a consistent grammar and helps you with everything from reading in files, manipulating them, to visualizing it. For the later it includes the famous ggplot2 library, which is really powerful to create all kind of plots. A great tutorial on the tidyverse can be found in the freely available book R for Data Science.