Python | Pandas dataframe.rmod()
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.rmod() function is used for finding the modulo 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.rmod(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 rmod() function to find the modulo of a series with a dataframe.
Python3
# importing pandas as pd import pandas as pd # Creating the dataframe 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" ]) # Print the dataframe df |
Let’s create the series
Python3
# importing pandas as pd import pandas as pd # Create the series sr = pd.Series([ 12 , 25 , 64 , 18 ], index = [ "A" , "B" , "C" , "D" ]) # Print the series sr |
Let’s use the dataframe.rmod() function to find the modulo of a series with dataframe
Python3
df.rmod(sr, axis = 1 ) |
Output :
Example #2: Use rmod() function to perform modulo division of a dataframe with other.
Python3
# importing pandas as pd import pandas as pd # Creating the first dataframe 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" ]) # Creating the second dataframe 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" ]) # perform modulus of df2 by df1 df1.rmod(df2) |
Output :
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