The pandas library provides many sophisticated tools for high-performance data analysis in Python. Many of the useful features that numpy offers for pure numerical work, pandas extends to other datatypes such as dates. Pandas also makes sharing data with SQL databases, Excel spreadsheets, CSV files and other formats extremely easy.
Another great library that I wanted to try out is xlwings. xlwings brings the power and ease of Python to Excel spreadsheets and allows you manipulate data live as well as to add updatable matplotlib figures to your spreadsheets.
In this example, we are going to use a combination of both libraries to analyse (ficticious) data from a bank account to analyse earnings and spendings.