Python | Pandas Series.combine()
Last Updated :
26 Mar, 2024
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
Series.combine()
is a series mathematical operation method. This is used to combine two series into one. The shape of output series is same as the caller series. The elements are decided by a function passed as parameter to
combine()
method. The shape of both series has to be same otherwise it will throw an error.
Syntax: Series.combine(other, func, fill_value=nan) Parameters: other: other series or list type to be combined with caller series func: Function passed as parameter which will decide from which series the element should be put at that index fill_value: integer value of level in case of multi index Return: Combined series with same shape as caller series
Example #1:
In this example, two lists are made and converted into pandas series using .Series() method. A function is made using lambda which checks which values is smaller in both series and returns whichever is the smaller.
Python3
# importing pandas module
import pandas as pd
# creating first series
first =[1, 2, 5, 6, 3, 7, 11, 0, 4]
# creating second series
second =[5, 3, 2, 1, 3, 9, 21, 3, 1]
# making series
first = pd.Series(first)
# making seriesa
second = pd.Series(second)
# calling .combine() method
result = first.combine(second, (lambda x1, x2: x1 if x1 < x2 else x2))
# display
result
Output:
As shown in the output image, the returned series is having smaller values from both series.
Example #2:
In this example, Null values are passed too using
Numpy.nan
method. Since series contains null values, 5 is passed to fill_value parameter to replace null values by 5. A lambda function is passed which will compare values in both series and will return the greater one.
Python3
# importing pandas module
import pandas as pd
# importing numpy module
import numpy as np
# creating first series
first =[1, 2, np.nan, 5, 6, 3, np.nan, 7, 11, 0, 4, 8]
# creating second series
second =[5, 3, 2, np.nan, 1, 3, 9, 21, 3, np.nan, 1, np.nan]
# making series
first = pd.Series(first)
# making seriesa
second = pd.Series(second)
# calling .combine() method
result = first.combine(second, func =(lambda x1, x2: x1 if x1 > x2 else x2), fill_value = 5)
# display
result