How to Append Two Pandas DataFrames (With Examples)

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 here.

Additional Resources

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

How to Use Pandas fillna() to Replace NaN Values
How to Merge Pandas DataFrames on Multiple Columns
How to Merge Two Pandas DataFrames on Index