Data Munging With Python and pandas

Notebook for an 18F tech talk about solving common data munging challenges with Pandas.

Overview

Nothing fancy here...this talk is a brief tour of the Pandas library and its role in basic (smallish) data exploration and munging tasks.

Goals:

provide a quick overview for potential new Pandas users
give a basic refresher (with links to resources for more advanced tasks) to people who already use Pandas

To run the code samples in the Jupyer notebook interactively:

Install the miniconda Python package manager
From a terminal, clone this project repository to your local machine: git@github.com:bsweger/pandas-munging.git
If you don't have a GitHub account and want to get a read-only version of the code, use this command instead: git://github.com/bsweger/pandas-munging.git
Change to the project directory:
```
 cd pandas-munging
```
Install Python and dependencies into a conda virtual environment called pandas-munging.
```
 conda env create
```
Activate the conda environment:
```
 source activate pandas-munging
```
Start up the Jupyter notebook server:
```
 jupyter notebook
```
The notebook startup process should have opened a Jupyter web page at localhost:8888 (if not, point your browser there).
On the Files tab of the Jupyter home page, click pandas_data_munging.ipynb.
The Jupyter notebook with the slides and code from the presentation should open.