Python2019-02-22

Pandas for Production: Data Analysis Skills That Ship Real Projects

Tapan ParmarAuthor

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TL;DR

Pandas is essential for any data work in Python, but production code requires specific patterns. Always use: .copy() to avoid SettingWithCopyWarning, .loc/.iloc for explicit indexing, chunked reading for large files. For analysis: groupby().agg() for summaries, merge() with validate parameter for joins, and always check dtypes after reading CSVs. Master these patterns—they prevent 90% of pandas bugs.

Here’s are some best resources to master pandas step by step

What is pandas?

pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

If you are in Machine Learning and using Python as the main language then you must have been heard about pandas. During my journey of learning, I have checked many things and here is the opinionated guide that might help you out.

Start with the Basics of pandas

Start with the basics of pandas explained very well in these tutorials.

Full playlist for pandas (Must watch)

Kevin Markham explained almost every use cases by giving answers in each video related to pandas. I am pretty impressed with his teaching style and it is indeed so helpful.

Here is the GitHub repository for the same video series here

Also, check out his web site where he posts blogs about awesome features related to pandas and ML here

pandas Best Practices

Then check out best practices with pandas from the same guy.

Actually, I have seen pycon talk of this, but the above playlist has been divided the same talk into small topics which someone might find more helpful.

SQL vs Pandas

This video explains how to relate SQL and Pandas.

Although pandas functionalities are not limited and no one can explain in one video or playlist, these are some of the material I found useful especially for beginners like me.

Also If you are interested in reading then this book about data analysis is very famous in the community. Although I have never read it, many people advice to read it.

Python for Data Analysis

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python…

If you get really good at pandas, this is the place you can practice and hone your skills in pandas.

guipsamora/pandas_exercises

Practice your pandas skills! Contribute to guipsamora/pandas_exercises development by creating an account on GitHub.

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