The specific implementation of pandas DataFrame mul

Pandas2.2 DataFrame

Binary operator functions

()

()Methods are used to perform element-by-element multiplication operations. This method can be used to multiply between two DataFrames, or multiply between a DataFrame and a scalar. The following is a detailed description of the parameters:

• other: Can be another DataFrame, Series, Index, constant, or an array that can be broadcast to the same shape.
• axis: Specifies which axis to operate along.0or'index'Indicates operation along the line,1or'columns'Indicates operation along the column.
• level: If the index is a multi-index, you can specify which level to operate along.
• fill_value: If a missing value (NaN) is encountered, you can use this value to fill it.

Example

Suppose we have two DataFrames:

import pandas as pd

df1 = ({
    'A': [1, 2, 3],
    'B': [4, 5, 6]
})

df2 = ({
    'A': [1, 1, 1],
    'B': [2, 2, 2]
})

Example 1: Multiplication between DataFrame and DataFrame

result = (df2)
print(result)

Output:

   A  B
0  1  8
1  2 10
2  3 12

Example 2: Multiplication between DataFrame and scalar

result = (2)
print(result)

Output:

   A  B
0  2  8
1  4 10
2  6 12

Example 3: Use fill_value to handle missing values

Assumptiondf2There is a missing value:

[0, 0] = None  # Set a value in df2 to NaNresult = (df2, fill_value=1)
print(result)

Output:

     A  B
0  1.0  8
1  2.0 10
2  3.0 12

In this example,df2The first element in it isNaN,usefill_value=1back,df1Corresponding elements in1Multiply by1, the result is still1。

These examples show()Basic usage of the method and some common situations.

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