How to add a row to mention the names of the dataframes after we concatenate them?

Question

I have 3 dataframes with the same format.

Then I combine them horizontally and get

I would like to add a row to denote the name of each dataframe, i.e.,

I get above form by copying the data to MS Excel and manually adding the row. Is there anyway to directly do so for displaying in Python?

import pandas as pd

data = {'Name': ['Tom', 'Joseph'], 'Age': [20, 21]}  
df1 = pd.DataFrame(data) 

data = {'Name': ['John', 'Kim'], 'Age': [15, 17]}  
df2 = pd.DataFrame(data)

data = {'Name': ['Paul', 'Dood'], 'Age': [10, 5]}  
df3 = pd.DataFrame(data) 

pd.concat([df1, df2, df3], axis = 1)

Answer 1

The row is actually a first-level column. You can have it by adding this level to each dataframe before concatenating:

for df_name, df in zip(("df1", "df2", "df3"), (df1, df2, df3)):
    df.columns = pd.MultiIndex.from_tuples(((df_name, col) for col in df))

pd.concat([df1, df2, df3], axis = 1)

Answer 2

Very nich case, but you can use Multindex objects in order to be able to build want you want.

Consider that what you need is a "two level headers" to display the information as you want. Multindex at a columns level can accomplish that. To understand more the code, read about Multindex objects in pandas. You basically create the labels (called levels) and then use indexes to point to those labels (called codes) to build the object.

Here how to do it:

data = {'Name': ['Tom', 'Joseph'], 'Age': [20, 21]}  
df1 = pd.DataFrame(data) 

data = {'Name': ['John', 'Kim'], 'Age': [15, 17]}  
df2 = pd.DataFrame(data)

data = {'Name': ['Paul', 'Dood'], 'Age': [10, 5]}  
df3 = pd.DataFrame(data) 

df1.columns = pd.MultiIndex(levels=[['df1', 'df2', 'df3'], ['Name', 'Age']], codes=[[0, 0], [0, 1]])
df2.columns = pd.MultiIndex(levels=[['df1', 'df2', 'df3'], ['Name', 'Age']], codes=[[1, 1], [0, 1]])
df3.columns = pd.MultiIndex(levels=[['df1', 'df2', 'df3'], ['Name', 'Age']], codes=[[2, 2], [0, 1]])

And after the concatenation, you will have:

pd.concat([df1, df2, df3], axis = 1)