In order to feel confident and successfully complete this course, we strongly recommend you **complete the following courses** beforehand (just click on them to start):

## Why Use Pandas?

`pandas` is a Python library designed for data processing and analysis. Mastering this library is beneficial for **data scientists** and **data analysts** alike. With `pandas`, you can sort, filter, modify, and visualize your data, as well as calculate useful statistics, allowing you to perform comprehensive analysis.

To utilize this library, you must **import** it.
```python
# Importing `pandas`
import pandas
```

For ease of use, it's common to import the library using an alias.
```python
# Importing `pandas` with an alias
import pandas as pd
```

In this case, `pd` serves as an alias. So, when invoking functions from this library in the future, you would do it as follows:
```python
# Importing `pandas` with an alias
import pandas as pd

# Using a function from `pandas`
pd.function()
```

Pandas is an extremely user-friendly library for data analysis. It's also designed to handle large datasets, using data structures like DataFrame and Series. This makes it an invaluable tool for Data Science. In this guide, you'll get acquainted with a range of statistical functions, including how to find correlations, modes, medians, and maximum and minimum values within a dataset. You'll also learn how to handle missing values and manipulate specific values, as well as how to remove them.

In this section, we'll explore the fundamentals of Series and DataFrame structures. You'll also learn about the distinctions between these two types of structures.

Data can be sourced in various formats, such as CSV, JSON, SQL, HTML, and more. With Pandas, you're not limited to a single format — you can work with data across a multitude of file types. In this chapter, we'll specifically focus on the CSV and TXT formats.

Here, you'll learn how to process raw data by removing extraneous information and managing null values in a dataset.

Pandas First Steps

What is pandas?

Why Use Pandas?

Solution

What is pandas?

Why Use Pandas?

Solution