How to Rename the Index Name in Pandas DataFrames?

Renaming Index in Pandas DataFrame

When working with Pandas DataFrames, it's often necessary to modify the index or column names to better suit the data analysis task. The rename method provides a convenient way to rename columns, but what about the index?

Issue:

Consider a DataFrame with a DateTime index and unlabeled columns. Attempting to rename both the index and column name using the rename method results in only the column name being renamed.

Solution:

The rename method operates on the index values, not the index name. To change the index name, use the following:

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

Understanding the Difference:

The index and columns in a DataFrame are similar in nature, as they both represent an ordered collection of values. However, the naming convention is different. Index names refer to the levels of the index (e.g., 'Date'), while column names refer to the specific columns (e.g., 'SM').

Examples:

To clarify the distinction, consider the following examples:

<code class="python"># Renaming index values:
df.rename(index={0: 'a'})

# Renaming index name:
df.index.names = ['index']

# Renaming column name:
df.rename(columns={'old_name': 'new_name'})</code>

By understanding this difference, you can effectively manipulate the index and column names of your DataFrames to facilitate data analysis tasks.

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