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Python | Pandas Series.rdiv()

  • Last Updated : 11 Feb, 2019

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.rdiv() function perform the floating division of series and other, element-wise. The operation is equivalent to other / series, but with support to substitute a fill_value for missing data in one of the inputs.

Syntax: Series.rdiv(other, level=None, fill_value=None, axis=0)

Parameter :
other : Series or scalar value
fill_value : Fill existing missing (NaN) value
level : Broadcast across a level,

Returns : result : Series

Example #1: Use Series.rdiv() function to perform the floating division of a scalar with the given series object.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([10, 25, 3, 11, 24, 6])
  
# Create the Index
index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp']
  
# set the index
sr.index = index_
  
# Print the series
print(sr)

Output :

Now we will use Series.rdiv() function to perform the floating division of scalar with the series.




# divide the given value with series
result = sr.rdiv(other = 100)
  
# Print the result
print(result)

Output :

As we can see in the output, the Series.rdiv() function has returned the result of floating division of the given scalar with the series object.

Example #2: Use Series.rdiv() function to perform the floating division of a scalar with the given series object. The given series object contains some missing values.




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([19.5, 16.8, None, 22.78, None, 20.124, None, 18.1002, None])
  
# Print the series
print(sr)

Output :

Now we will use Series.rdiv() function to perform the floating division of scalar with the series. We will fill 10 at the place of all the missing values in the series.




# divide the given value with series
result = sr.rdiv(other = 100, fill_value = 10)
  
# Print the result
print(result)

Output :

As we can see in the output, the Series.rdiv() function has returned the result of floating division of the given scalar with the series object.


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