Python | Pandas dataframe.rfloordiv()
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.rfloordiv() function is used for Integer division of dataframe and other, element-wise (binary operator rfloordiv). This function is essentially same as doing other // dataframe but with a support to substitute for missing data in one of the inputs.
Syntax: DataFrame.rfloordiv(other, axis=’columns’, level=None, fill_value=None)
Parameters :
other : Series, DataFrame, or constant
axis : For Series input, axis to match Series index on
level : Broadcast across a level, matching Index values on the passed MultiIndex level
fill_value : Fill existing missing (NaN) values, and any new element needed for successful DataFrame alignment, with this value before computation. If data in both corresponding DataFrame locations is missing the result will be missing.
Returns : result : DataFrame
Example #1: Use rfloordiv() function to find the integer division of a series with a dataframe.
Python3
import pandas as pd
df = pd.DataFrame({ "A" :[ 1 , 5 , 3 , 4 , 2 ],
"B" :[ 3 , 2 , 4 , 3 , 4 ],
"C" :[ 2 , 2 , 7 , 3 , 4 ],
"D" :[ 4 , 3 , 6 , 12 , 7 ]},
index = [ "A1" , "A2" , "A3" , "A4" , "A5" ])
df
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Let’s create the series
Python3
import pandas as pd
sr = pd.Series([ 12 , 25 , 64 , 18 ],
index = [ "A" , "B" , "C" , "D" ])
sr
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Let’s use the dataframe.rfloordiv() function to find the integer division of the series with the dataframe.
Python3
df.rfloordiv(sr, axis = 1 )
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Output :
In the output, a dataframe has been returned, all the elements along the column axis in the dataframe divided the corresponding element in the series.
Example #2: Use rfloordiv() function to perform floor division of one dataframe with other.
Note : Here the input dataframe is divided by the dataframe that called the function dataframe.rfloordiv()
Python3
import pandas as pd
df1 = pd.DataFrame({ "A" :[ 1 , 5 , 3 , 4 , 2 ],
"B" :[ 3 , 2 , 4 , 3 , 4 ],
"C" :[ 2 , 2 , 7 , 3 , 4 ],
"D" :[ 4 , 3 , 6 , 12 , 7 ]},
index = [ "A1" , "A2" , "A3" , "A4" , "A5" ])
df2 = pd.DataFrame({ "A" :[ 10 , 11 , 7 , 8 , 5 ],
"B" :[ 21 , 5 , 32 , 4 , 6 ],
"C" :[ 11 , 21 , 23 , 7 , 9 ],
"D" :[ 1 , 5 , 3 , 8 , 6 ]},
index = [ "A1" , "A2" , "A3" , "A4" , "A5" ])
df1.rfloordiv(df2)
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Output :
Last Updated :
09 Sep, 2021
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