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.radd() function performs the addition of the dataframe and other object element-wise. Other object could be a constant, series or a dataframe. The function essentially performs other + dataframe but with an additional support of fill_value, which fills all the missing value in one of the inputs.
For series input, the index must match.
Note : This is different from dataframe.add() function. As in this function we add the dataframe to the other object.
Syntax: DataFrame.radd(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 radd() function to perform addition of a dataframe with a series
Python3
# 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]})# Print the dataframedf |
Let’s create a series with matching index as that of the dataframe column axis
Python3
# importing pandas as pdimport pandas as pd# Create a Seriessr = pd.Series([5, 10, 15, 20], index =["A", "B", "C", "D"])# Print the seriessr |
Now, use the dataframe.radd() function to perform addition.
Python3
# add dataframe to the series over the column axisdf.radd(sr, axis = 1) |
Output :
Example #2: Use radd() function to add two dataframes element- wise
Python3
# 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]})# Creating the second dataframedf2 = pd.DataFrame({"A":[14, 5, None, 4, 12], "B":[7, 6, 4, 5, None], "C":[2, 11, 4, 3, 6], "D":[4, None, 6, 2, 4]})# add two dataframesdf1.radd(df2, fill_value = 100) |
Output :
