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