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Select a row of series or dataframe by given integer index
  • Last Updated : 28 Jul, 2020

Dataframe.iloc[]  is used to select a row of series/dataframe by given integer index. Let’s Create a Data Frame:

Code:

Python3




# import pandas library
import pandas as pd 
  
# Create the dataframe 
df = pd.DataFrame({'ID': ['114', '345',
                         '157788', '5626'], 
                'Product': ['shirt', 'trousers',
                           'tie', 'belt'], 
                'Price': [1200, 1500,
                         600, 352], 
                'Color': ['White','Black'
                         'Red', 'Brown'], 
                'Discount': [10, 10,
                            10, 10]}) 
  
# Show the dataframe
df

Output:

Dataframe



Now, Selecting a row of series/dataframe by a given integer index:
Example 1: Selecting the first row only.

Python3




# select first row 
# from the dataframe
df.iloc[0]

Output: 
 

first row of dataframe

Example 2: Selecting  0,1,2  rows.

Python3




# select 0, 1, 2 rows
#from the dataframe
df.iloc[0 : 3]

Output:
 

extract rows of dataframe



Example 3: Selecting rows from 0 to 2 and columns 0 to 1.

Python3




# selecting rows from 0 to
# 2 and columns 0 to 1
df.iloc[0 : 3, 0 : 2]

Output: 
 

Dataframe subset

Example 4: Selecting all rows and columns from 0 to 3. 

Python3




# selecting all rows and 
# columns from 0 to 3
df.iloc[ : , 0 : 4]

Output:
 

Example 5: Selecting all rows and 2nd column.

Python3




# selecting all rows and 
# 3rd column
df.iloc[ : , 2]

Output:
 

dataframe with 2nd column only

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