Python Pandas DataFrame: How to add an additional index / column to existing data

Question

So I want make an extra index / extra column in my excel sheet (with already existing data) using Pandas DataFrame. This is what I mean:

Picture 1 (What my code outputs):

Picture 2 (What I WANT my code to output):

Here’s my code for picture 1:

import pandas as pd

# Create a Pandas dataframe from the data.
df = pd.DataFrame([['a', 'b'], ['c', 'd']],
                    index=['row 1', 'row 2'],
                    columns=['col 1', 'col 2'])

# Create a Pandas Excel writer using XlsxWriter as the engine.
writer = pd.ExcelWriter('pandas_simple.xlsx', engine='xlsxwriter')

# Convert the dataframe to an XlsxWriter Excel object.
df.to_excel(writer, sheet_name='Sheet1')

# Close the Pandas Excel writer and output the Excel file.
writer.close()

Is there a possible way to do this?

Asked By: hacker_man_2021

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Source

Answer 1

You can use pd.MultiIndex.from_arrays:

new_idx = pd.Index(['data_type_1', 'date_type_2'])
out = df.set_index(pd.MultiIndex.from_arrays([df.index, new_idx]))
out.to_excel('pandas_simple.xlsx')
print(out)

# Output
                  col 1 col 2
row 1 data_type_1     a     b
row 2 date_type_2     c     d

Update

Maybe you want to prefer:

new_idx = pd.Index(['data_type_1', 'date_type_2'])
mi = pd.MultiIndex.from_product([df.index, new_idx])
out = df.reindex(df.index.repeat(len(new_idx))).set_index(mi)
print(out)

# Output
                  col 1 col 2
row 1 data_type_1     a     b
      date_type_2     a     b
row 2 data_type_1     c     d
      date_type_2     c     d

Answered By: Corralien

Python Pandas DataFrame: How to add an additional index / column to existing data

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