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Python | Pandas Series.multiply()
  • 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.multiply() function perform the multiplication of series and other, element-wise. The operation is equivalent to series * other, but with support to substitute a fill_value for missing data in one of the inputs.

Syntax: Series.multiply(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.multiply() function to perform the multiplication 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.multiply() function to perform the multiplication of scalar with the series.




# multiply the given value with series
result = sr.multiply(other = 10)
  
# Print the result
print(result)

Output :

As we can see in the output, the Series.multiply() function has returned the result of multiplication of the given scalar with the series object.
 
Example #2: Use Series.multiply() function to perform the multiplication 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.multiply() function to perform the multiplication of scalar with the series.




# multiply the given value with series
# fill 5 at the place of all the missing values
result = sr.multiply(other = 10, fill_value = 5)
  
# Print the result
print(result)

Output :

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

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