How to Drop First Row in Pandas DataFrame (2 Methods)


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:

How to Drop Duplicate Columns in Pandas
How to Drop Rows by Index in Pandas
How to Drop Columns by Index in Pandas
How to Drop Rows that Contain Specific Value in Pandas

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