Analyzing Census Data with Pandas
Materials for my Analyzing Census Data with Pandas workshop for PyCon 2019.
This tutorial is meant to be followed using mybinder.org but if you choose to download the materials and follow along these are the instructions.
Getting the materials
The easiest way to get a copy of this repository is to clone it if you know git
git clone https://github.com/chekos/analyzing-census-data.git
But you can also download it straight from GitHub:
Setting up your environment
Only 2 packages are essential for this workshop:
- Jupyter (notebooks or lab)
You can either
pip install them:
pip install pandas jupyterlab
or use conda to install them
conda install -c conda-forge pandas jupyterlab
Once you have the materials and
python packages necessary, head over to the exercises directory and launch Jupyter Lab
cd analyzing-census-data cd exercises jupyter lab
This tutorial will guide you through a typical data analysis project utilizing Census data acquired from IPUMS. It's split into 2 notebooks:
In the first notebook you will:
- Work with compressed data with pandas.
- Retrieve high-level descriptive analytics of your data.
- Drop columns.
- Slice data (boolean indexing).
- Work with categorical data.
- Work with weighted data.
- Use python's
pathliblibrary, making your code more reproducible across platforms.
- Develop a reproducible data prep workflow for future projects.
On top of that, in the second notebook you will:
- Aggregate data.
- Learn about
- Learn about cross-sections
- Learn about
- Develop a reproducible data analysis workflow for future projects.