Pandas

Pandas is an open source library that is built on top of NumPy. Pandas allows for quick data analysis and data preparation. It excels in performance and productivity.

In this section, we will discuss the following topics:

• Series
• DataFrames
• Missing data handling
• GroupBy
• Operations

Depending on the environment, you may need to install Pandas first by going to your command line or terminal and running the following commands:

conda install pandas
pip install pandas

We will start by looking at the Series data type.

Series

Series is the first main data type that we will be using with Pandas. Series is almost the same as the NumPy array. The difference is that with Series, a series of axis labels can be indexed by a label.

We are going to make four different Python objects and form a list:

import numpy as np
import pandas as pd
labels = ['A', 'B','C']
my_data = [100,200,300]
array = np.array...