Table of Contents
Appending two pandas DataFrames can be achieved in multiple ways, such as by using the append() or concat() functions. To append two DataFrames, you first need to create them and then use either of the two aforementioned functions. Both of these functions take a list of DataFrames as an argument and return a single DataFrame which contains the data from all the DataFrames in the list. Examples of appending two DataFrames using append() and concat() are provided in the documentation of the pandas library.
You can use the following basic syntax to append two pandas DataFrames into one DataFrame:
big_df = pd.concat([df1, df2], ignore_index=True)
The following examples show how to use this syntax in practice.
Example 1: Append Two Pandas DataFrames
The following code shows how to append two pandas DataFrames together into one DataFrame:
import pandas as pd #create two DataFrames df1 = pd.DataFrame({'x': [25, 14, 16, 27, 20, 12, 15, 14, 19], 'y': [5, 7, 7, 5, 7, 6, 9, 9, 5], 'z': [8, 8, 10, 6, 6, 9, 6, 9, 7]}) df2 = pd.DataFrame({'x': [58, 60, 65], 'y': [14, 22, 23], 'z': [9, 12, 19]}) #append two DataFrames together combined = pd.concat([df1, df2], ignore_index=True) #view final DataFrame combined x y z 0 25 5 8 1 14 7 8 2 16 7 10 3 27 5 6 4 20 7 6 5 12 6 9 6 15 9 6 7 14 9 9 8 19 5 7 9 58 14 9 10 60 22 12 11 65 23 19
Example 2: Append More Than Two Pandas DataFrames
Note that you can use the pd.concat() function to append more than two pandas DataFrames together:
import pandas as pd #create three DataFrames df1 = pd.DataFrame({'x': [25, 14, 16], 'y': [5, 7, 7]}) df2 = pd.DataFrame({'x': [58, 60, 65], 'y': [14, 22, 23]}) df3 = pd.DataFrame({'x': [58, 61, 77], 'y': [10, 12, 19]}) #append all three DataFrames together combined = pd.concat([df1, df2, df3], ignore_index=True) #view final DataFrame combined x y 0 25 5 1 14 7 2 16 7 3 58 14 4 60 22 5 65 23 6 58 10 7 61 12 8 77 19
Note that if we didn’t use the ignore_index argument, the index of the resulting DataFrame would retain the original index values for each individual DataFrame:
#append all three DataFrames together combined = pd.concat([df1, df2, df3]) #view final DataFrame combined x y 0 25 5 1 14 7 2 16 7 0 58 14 1 60 22 2 65 23 0 58 10 1 61 12 2 77 19
You can find the complete online documentation for the pandas.concat() function .
The following tutorials explain how to perform other common functions in pandas: