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.rsub() function return the subtraction of series and other, element-wise (binary operator rsub). It is equivalent to other - series, but with support to substitute a fill_value for missing data in one of the inputs.
Syntax: Series.rsub(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 levelReturns : result : Series
Example #1: Use Series.rsub() function to perform reverse subtraction of the given Series object with a scalar element-wise.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([100, 25, 32, 118, 24, 65]) # 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.rsub() function to perform element-wise reverse subtraction of the given Series object with a scalar.
# perform reverse subtraction with 1000 selected_items = sr.rsub(other = 1000) # Print the returned Series object print(selected_items) |
Output :
As we can see in the output, the Series.rsub() function has successfully returned the reverse subtraction of the given Series object with the scalar.
Example #2 : Use Series.rsub() function to perform reverse subtraction of the given Series object with a scalar element-wise. The given Series object also 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.rsub() function to perform element-wise reverse subtraction of the given Series object with a scalar. We will also substitute 100 at the place of all the missing values in the given Series object.
# perform reverse subtraction with 1000 # fill 100 at the place of all missing values selected_items = sr.rsub(other = 1000, fill_value = 100) # Print the returned Series object print(selected_items) |
Output :
As we can see in the output, the Series.rsub() function has successfully returned the reverse subtraction of the given Series object with the scalar.
