You can change DataFrame' indexes likewise Series' indexes (by assigning necessary list to the `.index` attribute of DataFrame).

# Importing library
import pandas as pd

# Creating DataFrame
df = pd.DataFrame([[1, 2], [3, 4], [5, 6]])
# Set indexes
df.index = ['first', 'second', 'third']
print(df)

You can set indexes when defining the DataFrame by specifying the `index` parameter. For instance,

# Importing library
import pandas as pd

# Creating DataFrame with indexes
df = pd.DataFrame([[1, 2], [3, 4], [5, 6]], index = ['first', 'second', 'third'])
print(df)

Also there are two ways to set the columns names: by assigning list of names to the `columns` attribute, or specifying the `columns` parameter.

# Importing library
import pandas as pd

# Creating DataFrame with indexes
df = pd.DataFrame([[1, 2], [3, 4], [5, 6]], columns = ['col1', 'col2'], index = ['first', 'second', 'third'])
print(df)

# Changing columns' names
df.columns = ['Column1', 'Column2']
print(df)

> If you need to change columns' names or indexes of existing dataframe, use the approach with reassigning (`.index`, `.columns` attributes).

This course is designed to teach you the very basics of pandas - a must-have  Python library for every data analyst or data scientist (and not only). You will start from defining the basic objects, learn how to read data from files, and how to manipulate and aggregate loaded data.

In the first section of the course you will learn two basic objects provided by pandas - Series and DataFrame. You will learn how to create them and change their indexes or column names.

Often the necessary data are stored in some files. You need to be able to load these data and gain the first insights.

Once you have loaded the data as Series/DataFrame, you need to be able to get certain data based on needs. You will learn how to access rows, columns, and filter observations by conditions.

In the last section of the course, you will get to know how to calculate some aggregate statistics of your data, such as mean, median, sum, product. Also you will learn how to count values and get only unique observations.

Introduction to pandas [track]

Indexes and Columns