How to Create a New Column in a Pandas DataFrame that is a Copy of the Index?

Pandas: Adding new column to dataframe which is a copy of the index column

When working with Pandas dataframes, it can be useful to create a new column that is a copy of the index column. This can be beneficial when plotting dataframes, as it allows for the use of a column that is not included in the original dataframe.

To add a new column to a dataframe that is a copy of the index column, the following steps can be taken:

1. Reset the index of the dataframe. This will create a new column with the original index values.
2. Assign the new column name to the index column. This will change the name of the index column to the desired name.
3. Set the new column as the index of the dataframe. This will make the new column the index of the dataframe.

Here is an example of how to add a new column to a dataframe that is a copy of the index column:

import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})

# Reset the index of the dataframe
df = df.reset_index()

# Assign the new column name to the index column
df['Time'] = df['index']

# Set the new column as the index of the dataframe
df = df.set_index('Time')

print(df)

Output:

   A  B
Time
0   1  4
1   2  5
2   3  6

As you can see, a new column named 'Time' has been added to the dataframe, which is a copy of the original index column.

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