The Dataframe.iloc[] is used to select a row of Series/Dataframe by a given integer index in Python.
Creating DataFrame to Select a Row by Index
Here, we are creating a Pandas Dataframe with ID, Product, Price, Color, and Discount with there some values in it.
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:
Select the first row only
Here, we are selecting the first rows using iloc, Dataframe.iloc[] method is used when the index label of a data frame is something other than numeric series.
Python3
# select first row # from the dataframe df.iloc[ 0 ] |
Output:
Selecting 0, 1, 2 rows.
Here, we are selecting the first second, and third rows using iloc[0:3], starting with 0 indexes and ending with (3-1=2) index.
Python3
# select 0, 1, 2 rows #from the dataframe df.iloc[ 0 : 3 ] |
Output:
Select rows from 0 to 2 and columns from 0 to 1
Here, we are selecting the first second third rows, and the first and second columns using iloc[0:3].
Python3
# selecting rows from 0 to # 2 and columns 0 to 1 df.iloc[ 0 : 3 , 0 : 2 ] |
Output:
Select all rows and 2nd column
Selecting all the rows and only the second columns from the Dataframe.
Python3
# selecting all rows and # 3rd column df.iloc[ : , 2 ] |
Output:
Select all rows and columns from 0 to 3.
Selecting all rows and columns.
Python3
# selecting all rows and # columns from 0 to 3 df.iloc[ : , 0 : 4 ] |
Output: