Pandas DataFrame - tail() function
The Pandas DataFrame tail() function returns the last n rows of the dataframe. The syntax for using this function is given below:
Syntax
DataFrame.tail(n)
Parameters
n |
Required. Specify number of rows to select. |
Return Value
Returns the last n rows of the dataframe.
Example:
In the example below, a DataFrame df is created. The tail() function returns last selected number of rows of the dataframe.
import pandas as pd
import numpy as np
df = pd.DataFrame({
"Bonus": [5, 3, 2, 4, 3, 4],
"Last Salary": [58, 60, 63, 57, 62, 59],
"Salary": [60, 62, 65, 59, 63, 62]},
index= ["John", "Marry", "Sam", "Jo", "Ramesh", "Kim"]
)
print("The DataFrame is:")
print(df)
#returning last two rows of the dataframe
print("\ndf.tail(2) returns:")
print(df.tail(2))
The output of the above code will be:
The DataFrame is:
Bonus Last Salary Salary
John 5 58 60
Marry 3 60 62
Sam 2 63 65
Jo 4 57 59
Ramesh 3 62 63
Kim 4 59 62
df.tail(2) returns:
Bonus Last Salary Salary
Ramesh 3 62 63
Kim 4 59 62
Example:
n can take negative values as Python supports negative indexing. Consider the following example.
import pandas as pd
import numpy as np
df = pd.DataFrame({
"Bonus": [5, 3, 2, 4, 3, 4],
"Last Salary": [58, 60, 63, 57, 62, 59],
"Salary": [60, 62, 65, 59, 63, 62]},
index= ["John", "Marry", "Sam", "Jo", "Ramesh", "Kim"]
)
print("The DataFrame is:")
print(df)
#using negative indexing with the dataframe
print("\ndf.tail(-2) returns:")
print(df.tail(-2))
The output of the above code will be:
The DataFrame is:
Bonus Last Salary Salary
John 5 58 60
Marry 3 60 62
Sam 2 63 65
Jo 4 57 59
Ramesh 3 62 63
Kim 4 59 62
df.tail(-2) returns:
Bonus Last Salary Salary
Sam 2 63 65
Jo 4 57 59
Ramesh 3 62 63
Kim 4 59 62
❮ Pandas DataFrame - Functions
