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 dot()
Pandas Series.dot() works similarly to pd.mul() method, but instead of returning multiplied separate values, the Dot product is returned (Sum of multiplication of values at each index).
Pandas Series dot() Syntax
Syntax: Series.dot(other)
Parameters:
- other: Other Series to be used to calculate DOT product
Return type: Series with updated values
Pandas Series dot() Method
In this example, two series are created from Python lists using Pandas Series() method. The method is then called on series1 and series2 is passed as a parameter. The result is then stored in a variable and displayed.
Python3
# importing pandas moduleimport pandas as pd # importing numpy moduleimport numpy as np # creating series 1series1 = pd.Series([7, 5, 6, 4, 9]) # creating series 2series2 = pd.Series([1, 2, 3, 10, 2])# storing in new variable# calling .dot() methodans = series1.dot(series2)# displayprint('Dot product = {}'.format(ans)) |
Output:
Dot product = 93
Deep Code Explanation
The elements in the caller series are multiplied by the element at the same index in the past series. All the multiplied values are then added to get the dot product. As in the 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.
Pandas Dataframe dot()
We can also use Pandas Dataframe for using the dot() method. The dot() method multiplies each value from one DataFrame with the values from another DataFrame, and adds them together.
Pandas Dataframe dot() Syntax
Syntax: dataframe.dot(other)
Parameters:
- other: Other Dataframe to be used to calculate DOT product
Return type: Dataframe with updated values
Example
All the multiplied values are then added to get the dot product.
Python3
# import DataFrameimport pandas as pd# using DataFrame.dot() methodgfg1 = pd.DataFrame([[1, 4], [9, 5]])gfg2 = pd.DataFrame([[4, 3, 2, 1], [21, -3, -4, 1]])print(gfg1.dot(gfg2)) |
Output:
0 1 2 3 0 88 -9 -14 5 1 141 12 -2 14
