How do I merge multiple dataframes in Python

Question

I have 3 dataFrames and all 3 have different columns. How do I make 1 big dataFrame of it?

Example of df1:

 type - country 0 001 - US 1 002 - DE 2 003 - ES 3 004 - FR

Example of df2:

 Model 0 Clio 1 Q5 2 RS6 3 AMG

Example of df3:

 Name 0 Richard 1 Paul 2 Juan 3 Del Castillo

This is the code I'm using:

df123 = pd.concat([df1, df2, df3])

The output is:

 type - country - Model - Name 0 001 - US - NaN - NaN 1 002 - DE - NaN - NaN 2 003 - ES - NaN - NaN 3 004 - FR - NaN - NaN

Expected output:

 type - country- Model - Name 0 001 - US - Clio - Richard 1 002 - DE - Q5 - Paul 2 003 - ES - RS6 - Juan 3 004 - FR - AMG - Del Castillo

What is the difference between your answer and the answers below? — Mediterráneo
– Mediterráneo, Commented Aug 27, 2020 at 8:51

Maciałek · Accepted Answer · 2020-08-27 08:36:49Z

1

Try

out = df1.join([df2, df3])

answered Aug 27, 2020 at 8:36

Maciałek

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2 Comments

Mediterráneo Over a year ago

This one looks great. Its the same as Roxy. Is this called a left join?

Maciałek Over a year ago

Yes, by pandas default its left join on dataframes indexes. Read the docs here: pandas.pydata.org/pandas-docs/stable/reference/api/… :)

Roxy · Accepted Answer · 2020-08-27 08:42:10Z

import pandas as pd df1 = pd.DataFrame(data={'Type': ['001', '002'], 'country': ['US', 'DE']}) df2 = pd.DataFrame(data={'Model': ['Clio', 'Q5']}) df3 = pd.DataFrame(data={'Name': ['John', 'Mary']}) df = df1.join([df2, df3]) print(df)

The output would be:

 Type country Model Name 0 001 US Clio John 1 002 DE Q5 Mary

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