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 level

Returns : 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.