pandas 尝试使用 .loc[row_indexer,col_indexer] = value 代替警告，即使在使用正式
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Try using .loc[row_indexer,col_indexer] = value instead warning even after using the formal
提问by Pragnya Srinivasan
This is one of the lines in my code where I get the SettingWithCopyWarning:
这是我的代码中获得 SettingWithCopyWarning 的行之一：
value1['Total Population']=value1['Total Population'].replace(to_replace='*', value=4)
Which I then changed to :
然后我改为：
row_index= value1['Total Population']=='*'
value1.loc[row_index,'Total Population'] = 4
This still gives the same warning. How do I get rid of it?
这仍然给出相同的警告。我该如何摆脱它？
Also, I get the same warning for a convert_objects(convert_numeric=True)function that I've used, is there any way to avoid that.
另外，我收到了与我使用过的convert_objects(convert_numeric=True)函数相同的警告，有什么办法可以避免这种情况。
value1['Total Population'] = value1['Total Population'].astype(str).convert_objects(convert_numeric=True)
This is the warning megsage that I get:
这是我收到的警告消息：
A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead
试图在来自 DataFrame 的切片副本上设置值。尝试使用 .loc[row_indexer,col_indexer] = value 代替
See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
请参阅文档中的警告：http: //pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
回答by Alexander
Have you tried setting directly?:
您是否尝试过直接设置？：
value1.loc[value1['Total Population'] == '*', 'Total Population'] = 4
回答by Pragnya Srinivasan
Got the solution:
得到了解决方案：
I created a new DataFrame and stored the value of only the columns that I needed to work on, it gives me no errors now!
我创建了一个新的 DataFrame 并仅存储了我需要处理的列的值，现在它没有给我任何错误！
Strange, but worked.
奇怪，但有效。
回答by abstrakkt
I was able to avoid the same warning message with syntax like this:
我能够避免使用以下语法出现相同的警告消息：
value1.loc[:, 'Total Population'].replace('*', 4)
Note that the dataframe doesn't need to be re-assigned to itself, i.e. value1['Total Population']=value1['Total Population']...
请注意，不需要将数据帧重新分配给自身，即value1['Total Population']=value1['Total Population']...
