使用 pandas 将函数应用于数据框中的每一行或每一列。apply()
原文:https://www . geesforgeks . org/apply-a-function-to-每行或每列-in-data frame-use-pandas-apply/
对数据框中的每一行或每一列应用函数有不同的方法。我们将在这篇文章中了解各种方法。让我们先创建一个小的数据帧，看看这个。
Python 3
# import pandas and numpy library
import pandas as pd
import numpy as np
# list of tuples
matrix = [(1,2,3,4),
(5,6,7,8,),
(9,10,11,12),
(13,14,15,16)
]
# Create a Dataframe object
df = pd.DataFrame(matrix, columns = list('abcd'))
# Output
df
输出:
方法 1: 对每行/每列应用 lambda 函数。 例 1: 为列
Python 3
# import pandas and numpy library
import pandas as pd
import numpy as np
# list of tuples
matrix = [(1,2,3,4),
(5,6,7,8,),
(9,10,11,12),
(13,14,15,16)
]
# Create a Dataframe object
df = pd.DataFrame(matrix, columns = list('abcd'))
# Applying a lambda function to each
# column which will add 10 to the value
new_df = df.apply(lambda x : x + 10)
# Output
new_df
输出:
示例 2: 对于行
Python 3
# import pandas and numpy library
import pandas as pd
import numpy as np
# list of tuples
matrix = [(1,2,3,4),
(5,6,7,8,),
(9,10,11,12),
(13,14,15,16)
]
# Creating a Dataframe object
df = pd.DataFrame(matrix, columns = list('abcd'))
# Applying a lambda function to each
# row which will add 5 to the value
new_df = df.apply(lambda x: x + 5, axis = 1)
# Output
new_df
输出:
方法 2: 将用户定义的函数应用于每一行/列 示例 1: 用于列
Python 3
# function to returns x*x
def squareData(x):
return x * x
# import pandas and numpy packages
import pandas as pd
import numpy as np
# list of tuples
matrix = [(1,2,3,4),
(5,6,7,8,),
(9,10,11,12),
(13,14,15,16)
]
# Creating a Dataframe object
df = pd.DataFrame(matrix, columns = list('abcd'))
# Applying a user defined function to
# each column that will square the given
# value
new_df = df.apply(squareData)
# Output
new_df
输出:
示例 2: 对于行
Python 3
# function to returns x*X
def squareData(x):
return x * x
# import pandas and numpy library
import pandas as pd
import numpy as np
# List of tuples
matrix = [(1,2,3,4),
(5,6,7,8,),
(9,10,11,12),
(13,14,15,16)
]
# Creating a Dataframe object
df = pd.DataFrame(matrix, columns = list('abcd'))
# Applying a user defined function
# to each row that will square the given value
new_df = df.apply(squareData, axis = 1)
# Output
new_df
输出:
在上面的示例中，我们看到了如何将用户定义的函数应用于每一行和每一列。我们还可以应用带有两个参数的用户定义函数。
实施例 1: 对于柱
Python 3
# function to returns x+y
def addData(x, y):
return x + y
# import pandas and numpy library
import pandas as pd
import numpy as np
# list of tuples
matrix = [(1,2,3,4),
(5,6,7,8,),
(9,10,11,12),
(13,14,15,16)
]
# Creating a Dataframe object
df = pd.DataFrame(matrix, columns = list('abcd'))
# Applying a user defined function to each
# column which will add value in each
# column by given number
new_df = df.apply(addData, args = [1])
# Output
print(new_df)
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