Pandas- Select first or last N rows in a Dataframe using head() & tail()

Pandas: Select first or last N rows in a Dataframe using head() & tail()

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In this tutorial, we are going to discuss how to select the first or last N rows in a Dataframe using head() & tail() functions. This guide describes the following contents.

Select first N Rows from a Dataframe using head() function

pandas.DataFrame.head()

In Python’s Pandas module, the Dataframe class gives the head() function to fetch top rows from it.

Syntax:

DataFrame.head(self, n=5)

If we give some value to n it will return n number of rows otherwise default is 5.

Let’s create a dataframe first,

import pandas as pd
# List of Tuples
empoyees = [('Ram', 34, 'Sunderpur', 5) ,
           ('Riti', 31, 'Delhi' , 7) ,
           ('Aman', 16, 'Thane', 9) ,
           ('Shishir', 41,'Delhi' , 12) ,
           ('Veeru', 33, 'Delhi' , 4) ,
           ('Shan',35,'Mumbai', 5 ),
           ('Shikha', 35, 'kolkata', 11)
            ]
# Create a DataFrame object
empDfObj = pd.DataFrame(empoyees, columns=['Name', 'Age', 'City', 'Experience'], index=['a', 'b', 'c', 'd', 'e', 'f', 'g'])
print("Contents of the Dataframe : ")
print(empDfObj)

Output:

Contents of the Dataframe :
     Name  Age  City           Experience
a   Ram     34   Sunderpur 5
b   Riti       31  Delhi          7
c   Aman   16  Thane         9
d  Shishir   41 Delhi          12
e  Veeru     33 Delhi          4
f   Shan      35 Mumbai     5
g  Shikha   35 kolkata      11

So if we want to select the top 4 rows from the dataframe,

import pandas as pd
# List of Tuples
empoyees = [('Ram', 34, 'Sunderpur', 5) ,
           ('Riti', 31, 'Delhi' , 7) ,
           ('Aman', 16, 'Thane', 9) ,
           ('Shishir', 41,'Delhi' , 12) ,
           ('Veeru', 33, 'Delhi' , 4) ,
           ('Shan',35,'Mumbai', 5 ),
           ('Shikha', 35, 'kolkata', 11)
            ]
# Create a DataFrame object
empDfObj = pd.DataFrame(empoyees, columns=['Name', 'Age', 'City', 'Experience'], index=['a', 'b', 'c', 'd', 'e', 'f', 'g'])

dfObj1 = empDfObj.head(4)
print("First 4 rows of the Dataframe : ")
print(dfObj1)

Output:

First 4 rows of the Dataframe :
  Name    Age   City         Experience
a Ram      34     Sunderpur 5
b Riti        31    Delhi          7
c Aman    16    Thane        9
d Shishir   41   Delhi         12

So in the above example, you can see that we have given n value 4 so it returned the top 4 rows from the dataframe.

Do Check:

Select first N rows from the dataframe with specific columns

In this, while selecting the first 3 rows, we can select specific columns too,

import pandas as pd
# List of Tuples
empoyees = [('Ram', 34, 'Sunderpur', 5) ,
           ('Riti', 31, 'Delhi' , 7) ,
           ('Aman', 16, 'Thane', 9) ,
           ('Shishir', 41,'Delhi' , 12) ,
           ('Veeru', 33, 'Delhi' , 4) ,
           ('Shan',35,'Mumbai', 5 ),
           ('Shikha', 35, 'kolkata', 11)
            ]
# Create a DataFrame object
empDfObj = pd.DataFrame(empoyees, columns=['Name', 'Age', 'City', 'Experience'], index=['a', 'b', 'c', 'd', 'e', 'f', 'g'])

# Select the top 3 rows of the Dataframe for 2 columns only
dfObj1 = empDfObj[['Name', 'City']].head(3)
print("First 3 rows of the Dataframe for 2 columns : ")
print(dfObj1)

Output:

First 3 rows of the Dataframe for 2 columns :
   Name  City
a Ram    Sunderpur
b Riti      Delhi
c Aman  Thane

Select last N Rows from a Dataframe using tail() function

In the Pandas module, the Dataframe class provides a tail() function to select bottom rows from a Dataframe.

Syntax:

DataFrame.tail(self, n=5)

It will return the last n rows from a dataframe. If n is not provided then the default value is 5. So for this, we are going to use the above dataframe as an example,

import pandas as pd
# List of Tuples
empoyees = [('Ram', 34, 'Sunderpur', 5) ,
           ('Riti', 31, 'Delhi' , 7) ,
           ('Aman', 16, 'Thane', 9) ,
           ('Shishir', 41,'Delhi' , 12) ,
           ('Veeru', 33, 'Delhi' , 4) ,
           ('Shan',35,'Mumbai', 5 ),
           ('Shikha', 35, 'kolkata', 11)
            ]
# Create a DataFrame object
empDfObj = pd.DataFrame(empoyees, columns=['Name', 'Age', 'City', 'Experience'], index=['a', 'b', 'c', 'd', 'e', 'f', 'g'])

# Select the last 4 rows of the Dataframe
dfObj1 = empDfObj.tail(4)
print("Last 4 rows of the Dataframe : ")
print(dfObj1)

Output:

Last 5 rows of the Dataframe :
  Name     Age City    Experience
d Shishir   41   Delhi      12
e Veeru    33   Delhi       4
f Shan      35   Mumbai  5
g Shikha  35   kolkata    11

So in above example, you can see that we are given n value 4 so tail() function return last 4 data value.

Select bottom N rows from the dataframe with specific columns

In this, while selecting the last 4 rows, we can select specific columns too,

import pandas as pd
# List of Tuples
empoyees = [('Ram', 34, 'Sunderpur', 5) ,
           ('Riti', 31, 'Delhi' , 7) ,
           ('Aman', 16, 'Thane', 9) ,
           ('Shishir', 41,'Delhi' , 12) ,
           ('Veeru', 33, 'Delhi' , 4) ,
           ('Shan',35,'Mumbai', 5 ),
           ('Shikha', 35, 'kolkata', 11)
            ]
# Create a DataFrame object
empDfObj = pd.DataFrame(empoyees, columns=['Name', 'Age', 'City', 'Experience'], index=['a', 'b', 'c', 'd', 'e', 'f', 'g'])

# Select the bottom 4 rows of the Dataframe for 2 columns only
dfObj1 = empDfObj[['Name', 'City']].tail(4)
print("Last 4 rows of the Dataframe for 2 columns : ")
print(dfObj1)

Output:

Last 4 rows of the Dataframe for 2 columns :
     Name   City
d  Shishir  Delhi
e  Veeru    Delhi
f   Shan     Mumbai
g  Shikha   kolkata

Conclusion:

In this article, you have seen how to select first or last N  rows in a Dataframe using head() & tail() functions. Thank you!

Want to expert in the python programming language? Exploring Python Data Analysis using Pandas tutorial changes your knowledge from basic to advance level in python concepts.

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