Select Rows from DataFrame by Integer Location in Python Pandas

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