You can use one of the following methods to drop the first row in a pandas DataFrame:

Method 1: Use drop

df.drop(index=df.index[0], axis=0, inplace=True)

Method 2: Use iloc

df = df.iloc[1: , :]

Each method produces the same result.

The following examples show how to use each method in practice with the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],
                   'position': ['G', 'G', 'F', 'F', 'G', 'G', 'F', 'F'],
                   'assists': [5, 7, 7, 9, 12, 9, 9, 4],
                   'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]})

#view DataFrame
df

	team	position assists rebounds
0	A	G	 5	 11
1	A	G	 7	 8
2	A	F	 7	 10
3	A	F	 9	 6
4	B	G	 12	 6
5	B	G	 9	 5
6	B	F	 9	 9
7	B	F	 4	 12

Method 1: Use drop

The following code shows how to use the drop() function to drop the first row of the pandas DataFrame:

#drop first row of DataFrame
df.drop(index=df.index[0], axis=0, inplace=True) 

#view updated DataFrame
df

	team	position assists rebounds
1	A	G	 7	 8
2	A	F	 7	 10
3	A	F	 9	 6
4	B	G	 12	 6
5	B	G	 9	 5
6	B	F	 9	 9
7	B	F	 4	 12

Notice that the first row has been removed from the DataFrame.

Also note that we must use inplace=True for the row to be removed in the original DataFrame.

Method 2: Use iloc

The following code shows how to use the iloc function to drop the first row of the pandas DataFrame:

#drop first row of DataFrame
df = df.iloc[1: , :]

#view updated DataFrame
df

	team	position assists rebounds
1	A	G	 7	 8
2	A	F	 7	 10
3	A	F	 9	 6
4	B	G	 12	 6
5	B	G	 9	 5
6	B	F	 9	 9
7	B	F	 4	 12

Notice that the first row has been removed from the DataFrame.

Additional Resources

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