Python | Pandas dataframe.rsub() - GeeksforGeeks

24 Nov, 2018
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.rsub() function is used for finding the subtraction 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.rsub(other, axis=’columns’, level=None, fill_value=None)Parameters :other : Series, DataFrame, or constantaxis : For Series input, axis to match Series index onlevel : Broadcast across a level, matching Index values on the passed MultiIndex levelfill_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 rsub() function to subtract each element of a series to a corresponding value in a dataframe over the column axis.
# importing pandas as pdimport 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 dataframedf
Let’s create the series
# importing pandas as pdimport pandas as pd  # Create the seriessr = pd.Series([12, 25, 64, 18], index =["A", "B", "C", "D"])  # Print the seriessr
Lets use the dataframe.rsub() function to subtract each element in a series with the corresponding element in the dataframe.
# equivalent to sr - dfdf.rsub(sr, axis = 1)
Output : Example #2: Use rsub() function to subtract each element in a dataframe with the corresponding element in other dataframe
# importing pandas as pdimport 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 dataframedf2 = 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"])  # Print the first dataframeprint(df1)  # Print the second dataframeprint(df2)
Lets perform df2 - df1
# subtract df1 from df2df1.rsub(df2)
Output :
Python pandas-dataFrame
Python pandas-dataFrame-methods
Python-pandas
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