Ceil and floor of the dataframe in Pandas Python – Round up and Truncate
Last Updated :
08 Oct, 2021
In this article, we will discuss getting the ceil and floor values of the Pandas Dataframe. First, Let’s create a dataframe.
Example:
Python3
import pandas as pd
import numpy as np
df = pd.DataFrame({ 'Student Name' : [ 'Anuj' , 'Ajay' , 'Vivek' ,
'suraj' , 'tanishq' , 'vishal' ],
'Marks' : [ 55.3 , 82.76 , 95.23 , 98.12 ,
95.78 , 90.56 ]})
df
|
Output:
Getting the Ceil Value
We can get the ceil value using the ceil() function. Ceil() is basically used to round up the values specified in it. It rounds up the value to the nearest greater integer.
Example:
Python3
df[ 'Marks' ] = df[ 'Marks' ]. apply (np.ceil)
df
|
Output:
Getting the floor value
We can get the floor value using the floor() function. Floor() is basically used to truncate the values. Basically, it truncates the values to their nearest smaller integer.
Example:
Python3
df[ 'Marks' ] = df[ 'Marks' ]. apply (np.floor)
df
|
Output:
Getting the round off value
round() is also used in this purpose only as it rounds off the value according to their decimal digits. Here we can give that to how many decimal places we have to round off our data.
Example:
Python3
df[ 'Marks' ] = df[ 'Marks' ]. round (decimals = 1 )
df
|
Output:
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