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Materials for the pandas tutorial at PyData Chicago 2016.

Change directory into the tutorial repo:

$ cd pydata-chi-h2t

And proceed with the installation, depending on whether you're using conda or pip.

Create a new environment using the provided environment.yml

$ conda env create

This will make a new environment called ph2t. Once it's created, make sure to run source activate ph2t or activate ph2t (depending on your platform) to activate it.

Check the install with

$ python check_environment.py

Then run

$ jupyter notebook

and open the first notebook 1-Basics.ipynb.

Hopefully you know what you're doing. I believe the current recommended way of creating virtualenvs is either

$ pyvenv /path/to/new/virtual/environment

or

$ python3 -m venv myenv

Make sure that you're creating a python3 environment. The notebooks should mostly work with python2, but no promises. If you call the environment ph2t, then activate it and install the requirements.

$ source /path/to/ph2t/bin/activate
$ python -m pip install -r requirments.txt

Check the install with

$ python check_environment.py

Then run

$ jupyter notebook

and open the first notebook 1-Basics.ipynb.

1. Basics
2. Operations
3. Indexing
4. Groupby and Reshaping
5. Tidy Data
6. For Stats & ML

• Wes McKinney's Python for Data Analysis
• The official docs
• Brandon Rhodes PyCon Tutorial
• Joris Van den Bossche's Introductory Tutorial
• My series of articles