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There are two methods to drop the first row in Pandas DataFrame. The first method is to use the DataFrame.drop() method with the parameter index set to 0. This will delete the row with index 0 from the DataFrame. The second method is to use the DataFrame.iloc() method with the parameter index set to 1. This will return a DataFrame object that excludes the first row of the original DataFrame.
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.