Python | Pandas dataframe.floordiv()

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas dataframe.floordiv() function is used for integer division of the dataframe with either a constant, series or any other dataframe. 
If other is a series then, the dimension of series must match with the division axis of the dataframe. If other is a data frame then, both the dataframes should have the same dimension.
Equivalent to dataframe/other, but with support to substitute a fill_value for missing data in one of the inputs.

Syntax: DataFrame.floordiv(other, axis=’columns’, level=None, fill_value=None)
Parameters:
other : Series, DataFrame, or constant 
axis : For Series input, axis to match Series index on 
fill_value : Fill missing (NaN) values with this value. If both DataFrame locations are missing, the result will be missing 
level : Broadcast across a level, matching Index values on the passed MultiIndex level
Returns : result : DataFrame 

Example #1: Use floordiv() function to find the integer division of a dataframe with a constant. Dataframe contains NA value.

Python3

# importing pandas as pd
import pandas as pd

# Creating the dataframe
df = pd.DataFrame({"A":[5, 3, 6, 4],
                   "B":[11, None, 4, 3],
                   "C":[4, 3, 8, None],
                   "D":[5, 4, 2, 8]})

# Print the dataframe
df

Now apply the floordiv() function. In our dataframe we are having NA values. We fill all such values with 50.

Python3

# applying floordiv() function
df.floordiv(2, fill_value = 50)

Output :

Notice, all the non-Na value in the dataframe has been filled with 50 before performing the integer division. 

Example #2: Use floordiv() function to find the integer division of a dataframe with a Series. 

Python3

# importing pandas as pd
import pandas as pd

# Creating the dataframe
df = pd.DataFrame({"A":[5, 3, 6, 4],
                   "B":[11, 2, 4, 3],
                   "C":[4, 3, 8, 5],
                   "D":[5, 4, 2, 8]})

# creating series
sr = pd.Series([2, 1, 3, 1])

# applying floordiv() function
df.floordiv(sr, axis = 0)

Output :

Each row of the dataframe is divided by the corresponding value in the series object.