In this article we will discuss how to select top or bottom N number of rows in a Dataframe using head() & tail() functions.
Select first N Rows from a Dataframe using head() function
pandas.DataFrame.head()
In Python’s Pandas module, the Dataframe class provides a head() function to fetch top rows from a Dataframe i.e.
DataFrame.head(self, n=5)
It returns the first n rows from a dataframe. If n is not provided then default value is 5.
Let’s see how to use this.
Suppose we have a dataframe i.e.
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# List of Tuples
empoyees = [('jack', 34, 'Sydney', 5) ,
('Riti', 31, 'Delhi' , 7) ,
('Aadi', 16, 'Tokyo', 9) ,
('Sunil', 41,'Delhi' , 12) ,
('Veena', 33, 'Delhi' , 4) ,
('Shaunak',35,'Mumbai', 5 ),
('Shaun', 35, 'Colombo', 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)
Contents of the Dataframe :
Contents of the Dataframe :
Name Age City Experience
a jack 34 Sydney 5
b Riti 31 Delhi 7
c Aadi 16 Tokyo 9
d Sunil 41 Delhi 12
e Veena 33 Delhi 4
f Shaunak 35 Mumbai 5
g Shaun 35 Colombo 11
Select top 5 rows from the dataframe
# Select the top 5 rows of the Dataframe
dfObj1 = empDfObj.head()
print("First 5 rows of the Dataframe : ")
print(dfObj1)
Output:
First 5 rows of the Dataframe :
Name Age City Experience
a jack 34 Sydney 5
b Riti 31 Delhi 7
c Aadi 16 Tokyo 9
d Sunil 41 Delhi 12
e Veena 33 Delhi 4
As we didn’t provide the argument n, whose default value is 5. Therefore head() function returned first 5 lines of the dataframe.
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Select top 2 rows from the dataframe
# Select the first 2 rows of the Dataframe
dfObj1 = empDfObj.head(2)
print("First 2 rows of the Dataframe : ")
print(dfObj1)
Output:
First 2 rows of the Dataframe : Name Age City Experience a jack 34 Sydney 5 b Riti 31 Delhi 7
As n=2 therefore head() function returned first 2 lines of the dataframe.
Select first N rows from the dataframe with specific columns
Instead of selecting all the columns while fetching first 3 rows, we can select specific columns too i.e.
# 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 jack Sydney b Riti Delhi c Aadi Tokyo
It will return the top 3 values of given columns only.
Select last N Rows from a Dataframe using tail() function
pandas.DataFrame.tail()
In Python’s Pandas module, the Dataframe class provides a tail() function to fetch bottom rows from a Dataframe i.e.
DataFrame.tail(self, n=5)
It returns the last n rows from a dataframe. If n is not provided then default value is 5.
Let’s see how to use this.
Suppose we have a dataframe i.e.
# List of Tuples
empoyees = [('jack', 34, 'Sydney', 5) ,
('Riti', 31, 'Delhi' , 7) ,
('Aadi', 16, 'Tokyo', 9) ,
('Sunil', 41,'Delhi' , 12) ,
('Veena', 33, 'Delhi' , 4) ,
('Shaunak',35,'Mumbai', 5 ),
('Shaun', 35, 'Colombo', 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)
Contents of the Dataframe :
Contents of the Dataframe :
Name Age City Experience
a jack 34 Sydney 5
b Riti 31 Delhi 7
c Aadi 16 Tokyo 9
d Sunil 41 Delhi 12
e Veena 33 Delhi 4
f Shaunak 35 Mumbai 5
g Shaun 35 Colombo 11
Select bottom 5 rows from the dataframe
# Select the top 5 rows of the Dataframe
dfObj1 = empDfObj.head()
print("First 5 rows of the Dataframe : ")
print(dfObj1)
Output:
Last 5 rows of the Dataframe :
Name Age City Experience
c Aadi 16 Tokyo 9
d Sunil 41 Delhi 12
e Veena 33 Delhi 4
f Shaunak 35 Mumbai 5
g Shaun 35 Colombo 11
As we didn’t provide the argument n, whose default value is 5. Therefore tail() function returned last 5 lines of the dataframe.
Select bottom 2 rows from the dataframe
# Select the bottom 2 rows of the Dataframe
dfObj1 = empDfObj.tail(2)
print("Last 2 rows of the Dataframe : ")
print(dfObj1)
Output:
Last 2 rows of the Dataframe :
Name Age City Experience
f Shaunak 35 Mumbai 5
g Shaun 35 Colombo 11
As n=2 therefore tail() function returned last 2 lines of the dataframe.
Select bottom N rows from the dataframe with specific columns
Instead of selecting all the columns while fetching last 3 rows, we can select specific columns too i.e.
# Select the bottom 3 rows of the Dataframe for 2 columns only
dfObj1 = empDfObj[['Name', 'City']].tail(3)
print("Last 3 rows of the Dataframe for 2 columns : ")
print(dfObj1)
Output:
Last 3 rows of the Dataframe for 2 columns :
Name City
e Veena Delhi
f Shaunak Mumbai
g Shaun Colombo
It returns the bottom 2 values of given columns only.
Complete example is as follows,
import pandas as pd
def main():
# List of Tuples
empoyees = [('jack', 34, 'Sydney', 5) ,
('Riti', 31, 'Delhi' , 7) ,
('Aadi', 16, 'Tokyo', 9) ,
('Sunil', 41,'Delhi' , 12) ,
('Veena', 33, 'Delhi' , 4) ,
('Shaunak',35,'Mumbai', 5 ),
('Shaun', 35, 'Colombo', 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)
print('**** Select first n Rows from a Dataframe using head() function ****')
# Select the top 5 rows of the Dataframe
dfObj1 = empDfObj.head()
print("First 5 rows of the Dataframe : ")
print(dfObj1)
# Select the first 2 rows of the Dataframe
dfObj1 = empDfObj.head(2)
print("First 2 rows of the Dataframe : ")
print(dfObj1)
# 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)
print('**** Select last n Rows from a Dataframe using tail() function ****')
# Select the bottom 5 rows of the Dataframe
dfObj1 = empDfObj.tail()
print("Last 5 rows of the Dataframe : ")
print(dfObj1)
# Select the bottom 2 rows of the Dataframe
dfObj1 = empDfObj.tail(2)
print("Last 2 rows of the Dataframe : ")
print(dfObj1)
# Select the bottom 3 rows of the Dataframe for 2 columns only
dfObj1 = empDfObj[['Name', 'City']].tail(3)
print("Last 3 rows of the Dataframe for 2 columns : ")
print(dfObj1)
if __name__ == '__main__':
main()
Output:
Contents of the Dataframe :
Name Age City Experience
a jack 34 Sydney 5
b Riti 31 Delhi 7
c Aadi 16 Tokyo 9
d Sunil 41 Delhi 12
e Veena 33 Delhi 4
f Shaunak 35 Mumbai 5
g Shaun 35 Colombo 11
**** Select first n Rows from a Dataframe using head() function ****
First 5 rows of the Dataframe :
Name Age City Experience
a jack 34 Sydney 5
b Riti 31 Delhi 7
c Aadi 16 Tokyo 9
d Sunil 41 Delhi 12
e Veena 33 Delhi 4
First 2 rows of the Dataframe :
Name Age City Experience
a jack 34 Sydney 5
b Riti 31 Delhi 7
First 3 rows of the Dataframe for 2 columns :
Name City
a jack Sydney
b Riti Delhi
c Aadi Tokyo
**** Select last n Rows from a Dataframe using tail() function ****
Last 5 rows of the Dataframe :
Name Age City Experience
c Aadi 16 Tokyo 9
d Sunil 41 Delhi 12
e Veena 33 Delhi 4
f Shaunak 35 Mumbai 5
g Shaun 35 Colombo 11
Last 2 rows of the Dataframe :
Name Age City Experience
f Shaunak 35 Mumbai 5
g Shaun 35 Colombo 11
Last 3 rows of the Dataframe for 2 columns :
Name City
e Veena Delhi
f Shaunak Mumbai
g Shaun Colombo
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