Table of Contents
Pandas DataFrames can be concatenated using the concat function. This function takes a list of DataFrames and combines them into a single DataFrame by stacking them on top of each other. For example, two DataFrames can be concatenated by passing them to the concat function as a list, e.g. pd.concat([df1, df2]). The resulting DataFrame will contain the data from both the input DataFrames. Additionally, the axis argument of the concat function can be used to specify whether the DataFrames should be stacked on top of each other (axis=0) or side by side (axis=1).
You can use the following basic syntax to concatenate two pandas DataFrames:
df3 = pd.concat([df1, df2], ignore_index=True)
The following example shows how to use this syntax in practice.
Example: How to Concatenate Two Pandas DataFrames
Suppose we have the following two pandas DataFrames:
import pandas as pd #define DataFrames df1 = pd.DataFrame({'team': ['A', 'A', 'A', 'A'], 'assists': [5, 7, 7, 9], 'points': [11, 8, 10, 6]}) df2 = pd.DataFrame({'team': ['B', 'B', 'B', 'B'], 'assists': [4, 4, 3, 7], 'points': [14, 11, 7, 6]}) #view DataFrames print(df1) team assists points 0 A 5 11 1 A 7 8 2 A 7 10 3 A 9 6 print(df2) team assists points 0 B 4 14 1 B 4 11 2 B 3 7 3 B 7 6
We can use the following syntax to concatenate the two DataFrames:
#concatenate the DataFrames
df3 = pd.concat([df1, df2])
#view resulting DataFrame
print(df3)
team assists points
0 A 5 11
1 A 7 8
2 A 7 10
3 A 9 6
0 B 4 14
1 B 4 11
2 B 3 7
3 B 7 6
The result is one DataFrame that contains the data from both DataFrames.
If you’d like to create a new index when concatenating the DataFrames, you must use the ignore_index argument:
#concatenate the DataFrames and ignore index
df3 = pd.concat([df1, df2], ignore_index=True)
#view resulting DataFrame
print(df3)
team assists points
0 A 5 11
1 A 7 8
2 A 7 10
3 A 9 6
4 B 4 14
5 B 4 11
6 B 3 7
7 B 7 6
Notice that the index of the resulting DataFrame ranges from 0 to 7.
Note #1: In this example we concatenated two pandas DataFrames, but you can use this exact syntax to concatenate any number of DataFrames that you’d like.
Note #2: You can find the complete documentation for the pandas concat() function .