This is a guide to many pandas tutorials, geared mainly for new users.
pandas’ own 10 Minutes to pandas.
More complex recipes are in the Cookbook.
A handy pandas cheat sheet.
pandas Cookbook by Julia Evans
The goal of this 2015 cookbook (by Julia Evans) is to give you some concrete examples for getting started with pandas. These are examples with real-world data, and all the bugs and weirdness that entails. For the table of contents, see the pandas-cookbook GitHub repository.
Learn Pandas by Hernan Rojas
A set of lesson for new pandas users: https://bitbucket.org/hrojas/learn-pandas
Practical data analysis with Python
This guide is an introduction to the data analysis process using the Python data ecosystem and an interesting open dataset. There are four sections covering selected topics as munging data, aggregating data, visualizing data and time series.
Exercises for new users
Practice your skills with real data sets and exercises. For more resources, please visit the main repository.
Tutorial series written in 2016 by Tom Augspurger. The source may be found in the GitHub repository TomAugspurger/effective-pandas.
Excel charts with pandas, vincent and xlsxwriter
- Pandas From The Ground Up (2015) (2:24) GitHub repo
- Introduction Into Pandas (2016) (1:28) GitHub repo
- Pandas: .head() to .tail() (2016) (1:26) GitHub repo
- Data analysis in Python with pandas (2016-2018) GitHub repo and Jupyter Notebook
- Best practices with pandas (2018) GitHub repo and Jupyter Notebook
- Wes McKinney’s (pandas BDFL) blog
- Statistical analysis made easy in Python with SciPy and pandas DataFrames, by Randal Olson
- Statistical Data Analysis in Python, tutorial videos, by Christopher Fonnesbeck from SciPy 2013
- Financial analysis in Python, by Thomas Wiecki
- Intro to pandas data structures, by Greg Reda
- Pandas and Python: Top 10, by Manish Amde
- Pandas DataFrames Tutorial, by Karlijn Willems
- A concise tutorial with real life examples