Manipulating Tabular Data Using Pandas
Wei-Meng Lee · 2019
This chapter helps the coders to witness the use of Pandas to represent tabular data. It focuses on how to work with Series and DataFrames in Pandas. A Pandas Series is a one-dimensional NumPy-like array, with each element having an index; a Series behaves very much like a dictionary that includes an index. The chapter shows the structure of a Series in Pandas. Accessing an element in a Series is similar to accessing an element in an array. A Pandas DataFrame is a two-dimensional NumPy-like array. A DataFrame is very useful in the world of data science and machine learning, as it closely mirrors how data are stored in real-life. A Pandas DataFrame is often used when representing data in machine learning. The chapter shows some of the most common operations that the coders would perform on the data structures. It also shows how to create date ranges using the date _range () function.