Pandas is a library originally developed by Wes McKinney, which was designed to analyze datasets in a seamless and performant way. In recent years, this powerful library has seen an incredible growth and huge adoption by the Python community. In this section, we will introduce the main concepts and tools provided in this library, and we will use it to increase performance of various usecases that can't otherwise be addressed with NumPy's vectorized operations and broadcasting.
Pandas
Pandas fundamentals
While NumPy deals mostly with arrays, Pandas main data structures are pandas.Series, pandas.DataFrame, and pandas.Panel. In the rest of this chapter, we will abbreviate pandas with pd.
The main difference between a pd.Series object and an np.array is that...
