Pandas

Pandas complements the previously mentioned libraries with a special structure, called DataFrame, and also adds many statistical and data mangling methods, such as I/O, for many different formats, such as slicing, subsetting, handling missing data, merging, and reshaping, among others.

The DataFrame object is one of the most useful features of the whole library, providing a special 2D data structure with columns that can be of different data types. Its structure is very similar to a database table, but immersed in a flexible programming runtime and ecosystem, such as SciPy. These data structures are also compatible with NumPy matrices, so we can also apply high-performance operations to the data with minimal effort.