Materials for the pandas tutorial at PyData Chicago 2016
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data
figures
solutions
1-Basics.ipynb
2-Operations.ipynb
3-Indexing.ipynb
4-GroupbyAndReshaping.ipynb
5-TidyData.ipynb
6-StatsAndML.ipynb
LICENSE
README.md
check_environment.py
environment.yml
ph2t.py
requirements.txt

README.md

Pandas .head() to .tail()

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 United States License

Materials for the pandas tutorial at PyData Chicago 2016.

Setup

Change directory into the tutorial repo:

$ cd pydata-chi-h2t

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

Conda / Miniconda

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.

Pip / virtualenv

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.

Notebooks

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

Further Resources