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.rfloordiv() function perform the integer division of series and other, element-wise (binary operator rmul). 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.rfloordiv(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.rfloordiv() function to perform the integer 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.rfloordiv() function to perform the integer division of scalar with the series.
# find integer division of the given value with series result = sr.rfloordiv(2000) # Print the result print(result) |
Output :
As we can see in the output, the Series.rfloordiv() function has returned the result of integer division of the given scalar with the series object.
Example #2: Use Series.rfloordiv() function to perform the integer 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.rfloordiv() function to perform the integer division of scalar with the series. We will also fill 10 at the place of missing values.
# find integer division of the given value with series # fill 10 at the place of missing values result = sr.rfloordiv(2000, fill_value = 10) # Print the result print(result) |
Output :
As we can see in the output, the Series.rfloordiv() function has returned the result of integer division of the given scalar with the series object.
