You can use the following basic syntax to append multiple pandas DataFrames at once:
import pandas as pd #append multiple DataFrames df_big = pd.concat([df1,df2, df3], ignore_index=True)
This particular syntax will append df1, df2, and df3 into a single pandas DataFrame called df_big.
The following example shows how to use this syntax in practice.
Example 1: Append Multiple Pandas DataFrames at Once
The following code shows how to append multiple pandas DataFrames at once:
import pandas as pd #create three DataFrames df1 = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E'], 'points':[12, 5, 13, 17, 27]}) df2 = pd.DataFrame({'player': ['F', 'G', 'H', 'I', 'J'], 'points':[24, 26, 27, 27, 12]}) df3 = pd.DataFrame({'player': ['K', 'L', 'M', 'N', 'O'], 'points':[9, 5, 5, 13, 17]}) #append all DataFrames into one DataFrame df_big = pd.concat([df1,df2, df3], ignore_index=True) #view resulting DataFrame print(df_big) player points 0 A 12 1 B 5 2 C 13 3 D 17 4 E 27 5 F 24 6 G 26 7 H 27 8 I 27 9 J 12 10 K 9 11 L 5 12 M 5 13 N 13 14 O 17
The result is one big DataFrame that contains all of the rows from each of the three individual DataFrames.
The argument ignore_index=True tells pandas to ignore the original index numbers in each DataFrame and to create a new index that starts at 0 for the new DataFrame.
For example, consider what happens when we don’t use ignore_index=True when stacking the following two DataFrames:
import pandas as pd #create two DataFrames with indices df1 = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E'], 'points':[12, 5, 13, 17, 27]}, index=[0, 1, 2, 3, 4]) df2 = pd.DataFrame({'player': ['F', 'G', 'H', 'I', 'J'], 'points':[24, 26, 27, 27, 12]}, index=[2, 4, 5, 6, 9]) #stack the two DataFrames together df_big = pd.concat([df1,df2]) #view resulting DataFrame print(df_big) player points 0 A 12 1 B 5 2 C 13 3 D 17 4 E 27 2 F 24 4 G 26 5 H 27 6 I 27 9 J 12
The resulting DataFrame kept its original index values from the two DataFrames.
In general, you should use ignore_index=True when appending multiple DataFrames unless you have a specific reason for keeping the original index values.
Additional Resources
How to Add an Empty Column to a Pandas DataFrame
How to Insert a Column Into a Pandas DataFrame
How to Export a Pandas DataFrame to Excel