Pandas Cheat Sheet for Data Science in Python
Originally published at www.datacamp.com/community/blog/python-pandas-cheat-sheet
The Pandas library is one of the most preferred tools for data scientists to do data manipulation and analysis, next to matplotlib for data visualization and NumPy, the fundamental library for scientific computing in Python on which Pandas was built.
The fast, flexible, and expressive Pandas data structures are designed to make real-world data analysis significantly easier, but this might not be immediately the case for those who are just getting started with it. Exactly because there is so much functionality built into this package that the options are overwhelming.
That’s where this cheat sheet might come in handy.
It’s a quick guide through the basics of Pandas that you will need to get started on wrangling your data with Python.
As such, you can use it as a quick reference if you are just beginning their data science journey with Pandas or, for those of you who already haven’t started yet, you can just use it as a guide to make it easier to learn about and use it.
Get your cheat sheet here.
The cheat sheet will guide you through the basics of Pandas, going from the data structures to I/O, selection, dropping indices or columns, sorting and ranking, retrieving basic information of the data structures you’re working with to applying functions and data alignment.
In short, everything that you need to kickstart your data science learning with Python!
Do you want to learn more? Start the Intermediate Python For Data Science course for free now!
Originally published at www.datacamp.com.
