4 Important pandas Library Operations You Should Know

4 Important pandas Library Operations You Should Know

4 Important pandas Library Operations You Should Know. Make your exploratory data analysis task easier. If there's one show you shouldn't miss it's here.

Boost your exploratory data analysis process

Pandas is a highly popular data analysis and manipulation library. It provides numerous functions to perform efficient data analysis. Furthermore, its syntax is simple and easy-to-understand.

In this article, we focus on a particular function of Pandas, the groupby. It is used to group the data points (i.e. rows) based on the categories or distinct values in a column. We can then calculate a statistic or apply a function on a numerical column with regards to the grouped categories.

The process will be clear as we go through the examples. Let’s start by importing the libraries.

import numpy as np
import pandas as pd

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