Python | Pandas Series.divide()
Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas Series.divide()
function performs floating division of series and other, element-wise (binary operator truediv). It is equivalent to series / other
, but with support to substitute a fill_value for missing data in one of the inputs.
Syntax: Series.divide(other, level=None, fill_value=None, axis=0)
Parameter :
other : Series or scalar value
fill_value : Fill existing missing (NaN) values.
level : Broadcast across a level, matching Index values on the passed MultiIndex level
Returns : result : Series
Example #1: Use Series.divide()
function to perform floating division of the given series object with a scalar.
import pandas as pd
sr = pd.Series([ 80 , 25 , 3 , 25 , 24 , 6 ])
index_ = [ 'Coca Cola' , 'Sprite' , 'Coke' , 'Fanta' , 'Dew' , 'ThumbsUp' ]
sr.index = index_
print (sr)
|
Output :
Now we will use Series.divide()
function to perform floating division of the given series object with a scalar.
result = sr.divide(other = 2 )
print (result)
|
Output :
As we can see in the output, the Series.divide()
function has successfully performed the floating division of the given series object with a scalar.
Example #2 : Use Series.divide()
function to perform floating division of the given series object with a scalar. The given series object contains some missing values.
import pandas as pd
sr = pd.Series([ 100 , None , None , 18 , 65 , None , 32 , 10 , 5 , 24 , None ])
index_ = pd.date_range( '2010-10-09' , periods = 11 , freq = 'M' )
sr.index = index_
print (sr)
|
Output :
Now we will use Series.divide()
function to perform floating division of the given series object with a scalar. We are going to fill 50 at the place of all the missing values.
result = sr.divide(other = 2 , fill_value = 50 )
print (result)
|
Output :
As we can see in the output, the Series.divide()
function has successfully performed the floating division of the given series object with a scalar.
Last Updated :
15 Feb, 2019
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