I’m exploring Pandas DataFrame capabilities; It makes sense to devote some time in understanding the commonly used capabilities well.

These are the topics covered in this post –

1. Ways to create a dataframe – using a dict, using an ndarray

2. Creating a dataframe with indexes

3. Slicing and selecting rows filtering the data, selecting rows/columns according to criteria

4. Using groupby and apply on dataframes.

All the code is contained in an Ipython Notebook here . It’s a very convenient tool for illustration as it seamlessly combines code, text, plots and even supports latex markup.

Note: The code uses Pandas version 0.12 – the stable version the time of writing.