Python | Pandas Series.floordiv()
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.floordiv()
function returns the integer division of series and other, element-wise (binary operator floordiv). 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.floordiv(other, level=None, fill_value=None, axis=0)
Parameter :
other : Series or scalar value
fill_value : Fill existing missing (NaN) values, and any new element needed for successful Series alignment, with this value before computation.
level : Broadcast across a level, matching Index values on the passed MultiIndex levelReturns : result : Series
Example #1: Use Series.floordiv()
function to perform floor division operation of a series object with a scalar.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 10 , 25 , 3 , 25 , 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.floordiv()
function to perform the floor division of a given series object with a scalar.
# perform floor division result = sr.floordiv(other = 3 ) # Print the result print (result) |
Output :
As we can see in the output, the Series.floordiv()
function has successfully returned the result of floor division of the given series object with a scalar.
Example #2 : Use Series.floordiv()
function to perform floor division operation of a series object with a scalar. The given series object contains some missing values.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 11 , 21 , 8 , 18 , 65 , None , 32 , 10 , 5 , 24 , None ]) # Create the Index index_ = pd.date_range( '2010-10-09' , periods = 11 , freq = 'M' ) # set the index sr.index = index_ # Print the series print (sr) |
Output :
Now we will use Series.floordiv()
function to perform the floor division of a given series object with a scalar. We are going to fill 30 at the place of all the missing values.
# perform floor division result = sr.floordiv(other = 3 , fill_value = 30 ) # Print the result print (result) |
Output :
As we can see in the output, the Series.floordiv()
function has successfully returned the result of floor division of the given series object with a scalar.
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