How to Rename the Index of a Pandas DataFrame?

Renaming Index of a Pandas DataFrame

Renaming the columns of a DataFrame is straightforward using the df.rename() method. However, users may encounter issues when attempting to rename the index. This article will address this problem and provide a solution for renaming the index.

The df.rename() method is designed to accept a dictionary specifying the new column names. However, this approach is not applicable when renaming the index. Instead, to rename the index, one must modify the index.names attribute, which is a list of the index level names.

For example, consider a DataFrame with a DateTime index and no header:

<code class="python">import pandas as pd

df = pd.read_csv('data.csv', header=None, parse_dates=[[0]], index_col=[0])

# Attempt to rename the column using df.rename()
df.rename(columns={'1': 'SM'}, inplace=True)

# Print the resulting DataFrame
print(df.head())</code>

This code will successfully rename the column to 'SM' but will leave the index unchanged. To rename the index, we can use the following code:

<code class="python">df.index.names = ['Date']

# Print the resulting DataFrame
print(df.head())</code>

This code will result in the index being renamed to 'Date':

                  SM
Date                  
2002-06-18  0.112000
2002-06-22  0.190333
2002-06-26  0.134000
2002-06-30  0.093000
2002-07-04  0.098667

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