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Python Pandas - How to select rows from a DataFrame by integer location
To select rows by integer location, use the iloc() function. Mention the index number of the row you want to select.
Create a DataFrame −
dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35]],index=['x', 'y', 'z'],columns=['a', 'b'])
Select rows with integer location using iloc() −
dataFrame.iloc[1]
Example
Following is the code −
import pandas as pd # Create DataFrame dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35]],index=['x', 'y', 'z'],columns=['a', 'b']) # DataFrame print"DataFrame...\n",dataFrame # select rows with loc print"\nSelect rows by passing label..." print(dataFrame.loc['z']) # select rows with integer location using iloc print"\nSelect rows by passing integer location..." print(dataFrame.iloc[1])
Output
This will produce the following output −
DataFrame... a b x 10 15 y 20 25 z 30 35 Select rows by passing label... a 30 b 35 Name: z, dtype: int64 Select rows by passing integer location... a 20 b 25 Name: y, dtype: int64
Updated on: 16-Sep-2021
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