Hello!
The goal of this cookbook is to give you handholds for using pandas, Wes McKinney's fantastic library for data analysis in Python. It explains how to use pandas with practical examples and real-world data.
This is an alpha cookbook! Chapters will be added here as I, you know, write them. Let me know if you have suggestions, or if there are bugs.
It comes with batteries (data) included, so you can try out all the examples right away.
- Chapter 1: Reading from a CSV
- Chapter 2: Selecting data & finding the most common complaint type
- Chapter 3: Which borough has the most noise complaints? (or, more selecting data)
- Chapter 4: Find out on which weekday people bike the most with groupby and aggregate
You'll need an up-to-date version of IPython Notebook (>= 1.0) and pandas (>=0.12) for this to work properly
You can get these using pip:
pip install ipython pandas numpy
Alternatively, I use and recommend Anaconda, which will give you everything you need. It's free and open source.
Once you have pandas and IPython, you can get going!
git clone https://github.com/jvns/pandas-cookbook.git
cd pandas-cookbook/cookbook
ipython notebook --pylab inline
A tab should open up in your browser at http://localhost:8888
Happy pandas!