Python Pandas SettingWithCopyWarning
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Pandas SettingWithCopyWarning
提问by ba_ul
Python 3.4 and Pandas 0.15.0
Python 3.4 和 Pandas 0.15.0
df is a dataframe and col1 is a column. With the code below, I'm checking for the presence of the value 10 and replacing such values with 1000.
df 是一个数据框， col1 是一列。使用下面的代码，我正在检查值 10 是否存在并将这些值替换为 1000。
df.col1[df.col1 == 10] = 1000
Here's another example. This time, I'm changing values in col2 based on index.
这是另一个例子。这一次，我根据索引更改 col2 中的值。
df.col2[df.index == 151] = 500
Both these produce the warning below:
这两者都会产生以下警告：
-c:1: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
Finally,
最后，
cols = ['col1', 'col2', 'col3']
df[cols] = df[cols].applymap(some_function)
This produces a similar warning, with an added suggestion:
这会产生一个类似的警告，并附加一个建议：
Try using .loc[row_indexer,col_indexer] = value instead
I'm not sure I understand the discussion pointed to in the warnings. What would be a better way to write these three lines of code?
我不确定我是否理解警告中指出的讨论。编写这三行代码的更好方法是什么？
Note that the operations worked.
请注意，这些操作有效。
采纳答案by Paul H
The issue here is that: df.col1[df.col1 == 10]returns a copy.
这里的问题是：df.col1[df.col1 == 10]返回一个副本。
So I would say:
所以我会说：
row_index = df.col1 == 10
# then with the form .loc[row_indexer,col_indexer]
df.loc[row_index, 'col1'] = 100
回答by koelemay
Agreed with Paul about 'loc' usage.
同意 Paul 关于 'loc' 的用法。
For your applymap case you should be able to do this:
对于您的 applymap 案例，您应该能够做到这一点：
cols = ['col1', 'col2', 'col3']
df.loc[:, cols] = df[cols].applymap(some_function)
