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Tutorials

This is a guide to many pandas tutorials, geared mainly for new users.

Internal Guides

Pandas own :ref:`10 Minutes to Pandas<10min>`

More complex recipes are in the :ref:`Cookbook<cookbook>`

Pandas Cookbook

The goal of this 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 that entails.

Here are links to the v0.1 release. For an up-to-date table of contents, see the pandas-cookbook GitHub repository.

  • Shows off IPython's awesome tab completion and magic functions.
  • Chapter 1: Reading your data into pandas is pretty much the easiest thing. Even when the encoding is wrong!
  • Chapter 2: It's not totally obvious how to select data from a pandas dataframe. Here we explain the basics (how to take slices and get columns)
  • Chapter 3: Here we get into serious slicing and dicing and learn how to filter dataframes in complicated ways, really fast.
  • Chapter 4: Groupby/aggregate is seriously my favorite thing about pandas and I use it all the time. You should probably read this.
  • Chapter 5: Here you get to find out if it's cold in Montreal in the winter (spoiler: yes). Web scraping with pandas is fun! Here we combine dataframes.
  • Chapter 6: Strings with pandas are great. It has all these vectorized string operations and they're the best. We will turn a bunch of strings containing "Snow" into vectors of numbers in a trice.
  • Chapter 7: Cleaning up messy data is never a joy, but with pandas it's easier.
  • Chapter 8: Parsing Unix timestamps is confusing at first but it turns out to be really easy.

Lessons for New Pandas Users

For more resources, please visit the main repository.

    • Importing libraries
    • Creating data sets
    • Creating data frames
    • Reading from CSV
    • Exporting to CSV
    • Finding maximums
    • Plotting data
    • Reading from TXT
    • Exporting to TXT
    • Selecting top/bottom records
    • Descriptive statistics
    • Grouping/sorting data
    • Creating functions
    • Reading from EXCEL
    • Exporting to EXCEL
    • Outliers
    • Lambda functions
    • Slice and dice data
    • Adding/deleting columns
    • Index operations
    • Stack/Unstack/Transpose functions
    • GroupBy function
    • Ways to calculate outliers
    • Read from Microsoft SQL databases
    • Export to CSV/EXCEL/TXT
    • Converting between different kinds of formats
    • Combining data from various sources