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.