The dot method in pandas takes the dot product of a dataframe with another dataframe, series, or array-like object. The dot product is also known as matrix multiplication.
The shapes of both objects should be compatible with each other to calculate the dot product.
The illustration below shows how the dot product is computed:
The syntax of the dot method is as follows:
Dataframe.dot(other)
The dot method has a single parameter: other.
Other refers to a dataframe, series, or array-like object with which the dot product is taken.
The dot method returns a series if the other parameter is a series object.
It returns a dataframe if the other parameter is a dataframe.
The code snippet below shows how we can use the dot operator in pandas:
import pandas as pdimport numpy as np# Dataframe with a seriesdf = pd.DataFrame([[0, 1, -2, -1], [1, 1, 1, 1]])s = pd.Series([1, 1, 2, 1])print("Dataframe with a series")print(df.dot(s))print('\n')# Dataframe with another Dataframeother = pd.DataFrame([[0, 1], [1, 2], [-1, -1], [2, 0]])print("Dataframe with another Dataframe")print(df.dot(other))print('\n')# Dataframe with an arrayarr = np.array([[0, 1], [1, 2], [-1, -1], [2, 0]])print("Dataframe with another array")print(df.dot(arr))print('\n')
The
dotmethod is the same as the@operator in pandas.
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