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 .

Additional Resources

The following tutorials explain how to perform other common operations in pandas: