**Series** is the simplest data type in pandas. Let's talk about a more complex data type: **dataframe**. This is a two-dimensional object that is more commonly used.

Think of a **dataframe** as a spreadsheet that can contain large amounts of data. Similar to a spreadsheet, a **dataframe** has an index and columns.

To create a **dataframe** object, use a `dictionary` and the `.DataFrame()` function. Let’s take a look at how the coding is done.

import pandas as pd
dataset = {'name' : ['Ann', 'Alex', 'Kevin', 'Kate'], 
          'age' : [35, 12, 24, 45]}

data_frame = pd.DataFrame(dataset)
print(data_frame)

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.