如何将函数应用于 Pandas 中的多个列？

让我们看看如何将函数应用于 Pandas DataFrame 中的多个列。要执行此任务将使用apply()函数。

pandas.DataFrame.apply

此函数沿 DataFrame 的轴应用函数。

Syntax : DataFrame.apply(parameters)
Parameters : 
 

• func : Function to apply to each column or row.
• axis : Axis along which the function is applied
• raw : Determines if row or column is passed as a Series or ndarray object.
• result_type : ‘expand’, ‘reduce’, ‘broadcast’, None; default None
• args : Positional arguments to pass to func in addition to the array/series.
• **kwds : Additional keyword arguments to pass as keywords arguments to func.

Returns : Series or DataFrame 
 

示例 1：在两列中的每个元素之前添加“Geek”。

Python3

# import the module
import pandas as pd
 
# creating a DataFrame
df = pd.DataFrame({'String 1' :['Tom', 'Nick', 'Krish', 'Jack'],
                   'String 2' :['Jane', 'John', 'Doe', 'Mohan']})
 
# displaying the DataFrame
display(df)
 
# function for prepending 'Geek'
def prepend_geek(name):
    return 'Geek ' + name
 
# executing the function
df[["String 1", "String 2"]] = df[["String 1", "String 2"]].apply(prepend_geek)
 
# displaying the DataFrame
display(df)

输出 ：

示例 2：将每个元素的值乘以 2

Python3

# import the module
import pandas as pd
 
# creating a DataFrame
df = pd.DataFrame({'Integers' :[1, 2, 3, 4, 5],
                   'Float' :[1.1, 2.2, 3.3, 4.4 ,5.5]})
 
# displaying the DataFrame
display(df)
 
# function for prepending 'Geek'
def multiply_by_2(number):
    return 2 * number
 
# executing the function
df[["Integers", "Float"]] = df[["Integers", "Float"]].apply(multiply_by_2)
 
# displaying the DataFrame
display(df)

输出 ：