SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame

解决：SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame

在使用pandas时遇到了一个问题：SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame
翻译：（你）试图改变DataFrame（类似于一个pandas向量）中的一个副本中的值
解决方法就是使用loc
执行代码如下：

import pandas as pd
import numpy as npaa=np.array([1,2,3,4])
bb=pd.DataFrame(aa.T,columns=['first'])
print(bb,'\n***********')
bb['two']=0
print(bb,'\n***********')
bb['first'][0]=3
print(bb)

输出如下：

first
0 1
1 2
2 3
3 4

first two
0 1 0
1 2 0
2 3 0
3 4 0

Warning (from warnings module):
File “D:/pProject/mlRegression/meaningless.py”, line 9
bb[‘first’][0]=3
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
first two
0 3 0
1 2 0
2 3 0
3 4 0

我们看Warning 提出的帮助文档：

也就是说，这就类似于C++中传入函数的参数只是形参，在这里是__getitem__()函数，如果你在函数中尝试改变形参是毫无意义的，python 就会发出警告。

解决方案
方案就是用它提示的loc函数

import pandas as pd
import numpy as npaa=np.array([1,2,3,4])
bb=pd.DataFrame(aa.T,columns=['first'])
print(bb,'\n***********')
bb['two']=0
print(bb,'\n***********')
#bb['first'][0]=3
bb.loc['first',0]=3#改用loc
print(bb)

loc函数保证返回的是bb本身（类似于C++的引用，而不是bb的一个副本）

再举类似一个例子

import pandas as pd
import numpy as npaa=np.array([1,2,3,4])
bb=pd.DataFrame(aa.T,columns=['first'])
bb['two']=0cc=bb.iloc[:,0]
cc[3]=13
print(bb)
print(cc)

输出结果：

Warning (from warnings module):File "D:\pProject\mlRegression\meaningless.py", line 9cc[3]=13
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrameSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copyfirst  two
0      1    0
1      2    0
2      3    0
3     13    0
0     1
1     2
2     3
3    13
Name: first, dtype: int32

可以看到，警告的事情发生了！
bb的值连带着cc的值发生了改变！说明cc是bb的一个引用，cc值改变会引起bb 改变
正确做法：用深copy（而不是浅copy）

import pandas as pd
import numpy as npaa=np.array([1,2,3,4])
bb=pd.DataFrame(aa.T,columns=['first'])
bb['two']=0cc=bb.iloc[:,0]
cc=cc.copy()#加上这么一句
cc[3]=13
print(bb)
print(cc)

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SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame

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