Select Multiple Rows from a DataFrame in Python Pandas

To select multiple rows from a DataFrame, set the range using the : operator. At first, import the require pandas library with alias −

import pandas as pd

Now, create a new Pandas DataFrame −

dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35], [40, 45]],index=['w', 'x', 'y', 'z'],columns=['a', 'b'])

Select multiple rows using the : operator −

dataFrame[0:2]

Example

Following is the code −

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame([[10, 15], [20, 25], [30, 35], [40, 45]],index=['w', '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])

# selecting multiple rows
print"\nSelect multiple rows..."
print(dataFrame[0:2])

Output

This will produce the following output −

DataFrame...
     a    b
w   10   15
x   20   25
y   30   35
z   40   45

Select rows by passing label...
a   40
b   45
Name: z, dtype: int64

Select rows by passing integer location...
a   20
b   25
Name: x, dtype: int64

Select multiple rows...
     a    b
w   10   15
x   20   25