Analyze and Transform Financial Market Data with pandas

The pandas library was invented by Wes McKinney while at the investment management firm AQR Capital Management, where he researched macro and credit trading strategies. He built pandas to provide flexible, easy-to-use data structures for data analysis. Since it was open sourced in 2009, pandas has become the standard tool to analyze and transform data using Python.

pandas is well-suited for working with tabular data, like that stored in spreadsheets or databases, and it integrates well with many other data analysis libraries in the Python ecosystem. Its capabilities extend to handling missing data, reshaping datasets, and merging and joining datasets, and it also provides robust tools for loading data from flat files, Excel files, databases, and HDF5 file formats. It’s widely used in academia, finance, and many areas of business due to its rich features and ease of use.

This chapter will begin by covering recipes...