Python | Pandas Dataframe/Series.dot()

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.dot() works similarly like mul() method, but instead of returning multiplied separate values, Dot product is returned (Sum of multiplication of values at each index).

Syntax: Series.dot(other)
Parameters:
other: Other Series to be used to calculate DOT product

Return type: Series with updated values

Example #1:
In this example, two series are created from Python lists using Pandas Series() method. Method is then called on series1 and series2 is passed as parameter. The result is then stored in a variable and displayed.

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# importing pandas module  
import pandas as pd  
    
# importing numpy module 
import numpy as np 
    
# creating series 1 
series1 = pd.Series([7, 5, 6, 4, 9]) 
    
# creating series 2 
series2 = pd.Series([1, 2, 3, 10, 2]) 
  
# storing in new variable
# calling .dot() method
ans = series1.dot(series2)
  
# display
print('Dot product = {}'.format(ans))

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Output:

Dot product = 93

Explanation –
The elements in caller series are multiplied with the element at same index in passed series. All the multiplied values are then added to get the dot product.
As in above example, the series are:

[7, 5, 6, 4, 9]
[1, 2, 3, 10, 2]

Dot product = 7*1 + 5*2 + 6*3 + 4*10 + 9*2 = 7 + 10 + 18 + 40 + 18 = 93

Note: If there is any Null value in any of the series, the net result is NaN. NaN values should be removed/replaced using dropna() or fillna() methods respectively.



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Developer in day, Designer at night GSoC 2019 with Python Software Foundation (EOS Design system)

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