Concatenate Three pandas DataFrames in Python – Append & Combine (Example Code)
This post explains how to concatenate three or more pandas DataFrames in the Python programming language.
Preparing the Example
import pandas as pd # Import pandas library |
import pandas as pd # Import pandas library
my_df1 = pd.DataFrame({"A":["foo", "bar", "bar", "foo"], # Construct three pandas DataFrames "B":range(1, 5), "C":["a", "b", "c", "d"]}) print(my_df1) # A B C # 0 foo 1 a # 1 bar 2 b # 2 bar 3 c # 3 foo 4 d |
my_df1 = pd.DataFrame({"A":["foo", "bar", "bar", "foo"], # Construct three pandas DataFrames "B":range(1, 5), "C":["a", "b", "c", "d"]}) print(my_df1) # A B C # 0 foo 1 a # 1 bar 2 b # 2 bar 3 c # 3 foo 4 d
my_df2 = pd.DataFrame({"A":["yes", "no", "no"], "B":range(1, 4), "C":["hey", "hi", "huhu"]}) print(my_df2) # A B C # 0 yes 1 hey # 1 no 2 hi # 2 no 3 huhu |
my_df2 = pd.DataFrame({"A":["yes", "no", "no"], "B":range(1, 4), "C":["hey", "hi", "huhu"]}) print(my_df2) # A B C # 0 yes 1 hey # 1 no 2 hi # 2 no 3 huhu
my_df3 = pd.DataFrame({"A":["x", "y", "x"], "B":range(10, 7, - 1), "C":["y", "x", "y"]}) print(my_df3) # A B C # 0 x 10 y # 1 y 9 x # 2 x 8 y |
my_df3 = pd.DataFrame({"A":["x", "y", "x"], "B":range(10, 7, - 1), "C":["y", "x", "y"]}) print(my_df3) # A B C # 0 x 10 y # 1 y 9 x # 2 x 8 y
Example: Appending Multiple pandas DataFrames
my_df_combined = pd.concat([my_df1, my_df2, my_df3]) print(my_df_combined) # Display concatenated DataFrames # A B C # 0 foo 1 a # 1 bar 2 b # 2 bar 3 c # 3 foo 4 d # 0 yes 1 hey # 1 no 2 hi # 2 no 3 huhu # 0 x 10 y # 1 y 9 x # 2 x 8 y |
my_df_combined = pd.concat([my_df1, my_df2, my_df3]) print(my_df_combined) # Display concatenated DataFrames # A B C # 0 foo 1 a # 1 bar 2 b # 2 bar 3 c # 3 foo 4 d # 0 yes 1 hey # 1 no 2 hi # 2 no 3 huhu # 0 x 10 y # 1 y 9 x # 2 x 8 y
Further Resources
In addition, you may want to read the related articles on my website. You can find a selection of tutorials below: