### What is pandas? 


`pandas` is a library in Python for data processing and analysis.

### Why Use pandas?


The skill of working with this library will be useful for data scientists or data analysts. Using pandas, these professionals can group and visualize data, create pivot tables, and make selections based on specific criteria.

We must *import* this library in order to use it. Let's look at how to do so.

The alias should be used to simplify the use of this library. Let's look at how to do so.

Here, `pd` is an alias. Therefore, when using functions from this library in the future, we will do it like this:

# Importing pandas
import pandas as pd

# Using a function from pandas
pd.function()

In this section, we will introduce the basics of the series and dataframe  data structures. We will also learn the difference between these structures.

Raw data comes in many forms: CSV, JSON, SQL, HTML, and so on. With pandas, we can work with data in a variety of formats. In this chapter, we will take a closer look at the CSV and TXT formats.

In this section, we will learn how to work with raw data, how to remove unwanted data, and how to work with null values in a dataset.