pandas 混淆：数据帧警告切片的熊猫副本
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Confusion re: pandas copy of slice of dataframe warning
提问by Sam Lilienfeld
I've looked through a bunch of questions and answers related to this issue, but I'm still finding that I'm getting this copy of slice warning in places where I don't expect it. Also, it's cropping up in code that was running fine for me previously, leading me to wonder if some sort of update may be the culprit.
我已经浏览了一堆与此问题相关的问题和答案，但我仍然发现我在我不期望的地方收到了切片警告的副本。此外，它出现在之前对我来说运行良好的代码中，让我怀疑是否某种更新可能是罪魁祸首。
For example, this is a set of code where all I'm doing is reading in an Excel file into a pandas DataFrame, and cutting down the set of columns included with the df[[]]syntax.
例如，这是一组代码，其中我所做的只是将 Excel 文件读入 pandas DataFrame，并减少df[[]]语法中包含的列集。
izmir = pd.read_excel(filepath)
izmir_lim = izmir[['Gender','Age','MC_OLD_M>=60','MC_OLD_F>=60','MC_OLD_M>18','MC_OLD_F>18','MC_OLD_18>M>5','MC_OLD_18>F>5',
'MC_OLD_M_Child<5','MC_OLD_F_Child<5','MC_OLD_M>0<=1','MC_OLD_F>0<=1','Date to Delivery','Date to insert','Date of Entery']]
Now, any further changes I make to this izmir_limfile raise the copy of slice warning.
现在，我对此izmir_lim文件所做的任何进一步更改都会引发切片警告的副本。
izmir_lim['Age'] = izmir_lim.Age.fillna(0)
izmir_lim['Age'] = izmir_lim.Age.astype(int)
/Users/samlilienfeld/anaconda/lib/python3.5/site-packages/ipykernel/main.py:2: SettingWithCopyWarning: 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
/Users/samliienfeld/anaconda/lib/python3.5/site-packages/ipykernel/ main.py:2: SettingWithCopyWarning: 试图在 DataFrame 的切片副本上设置一个值。尝试使用 .loc[row_indexer,col_indexer] = value 代替
I'm confused because I thought the df[[]]column subsetting returned a copy by default. The only way I've found to suppress the errors is by explicitly adding df[[]].copy(). I could have sworn that in the past I did not have to do that and did not raise the copy of slice error.
我很困惑，因为我认为df[[]]列子集默认返回一个副本。我发现抑制错误的唯一方法是显式添加df[[]].copy(). 我可以发誓，过去我不必这样做，也没有引发切片错误的副本。
Similarly, I have some other code that runs a function on a dataframe to filter it in certain ways:
同样，我还有一些其他代码在数据帧上运行一个函数，以某些方式对其进行过滤：
def lim(df):
if (geography == "All"):
df_geo = df
else:
df_geo = df[df.center_JO == geography]
df_date = df_geo[(df_geo.date_survey >= start_date) & (df_geo.date_survey <= end_date)]
return df_date
df_lim = lim(df)
From this point forward, any changes I make to any of the values of df_limraise the copy of slice error. The only way around it that i've found is to change the function call to:
从现在开始，我对任何值所做的任何更改都会df_lim引发切片错误的副本。我发现的唯一解决方法是将函数调用更改为：
df_lim = lim(df).copy()
This just seems wrong to me. What am I missing? It seems like these use cases should return copies by default, and I could have sworn that the last time I ran these scripts I was not running in to these errors.
Do I just need to start adding .copy()all over the place? Seems like there should be a cleaner way to do this. Any insight or help is much appreciated.
这对我来说似乎是错误的。我错过了什么？似乎这些用例在默认情况下应该返回副本，我可以发誓，上次运行这些脚本时，我没有遇到这些错误。
我只需要开始.copy()到处添加吗？似乎应该有一种更清洁的方法来做到这一点。非常感谢任何见解或帮助。
回答by piRSquared
izmir = pd.read_excel(filepath)
izmir_lim = izmir[['Gender','Age','MC_OLD_M>=60','MC_OLD_F>=60',
'MC_OLD_M>18','MC_OLD_F>18','MC_OLD_18>M>5',
'MC_OLD_18>F>5','MC_OLD_M_Child<5','MC_OLD_F_Child<5',
'MC_OLD_M>0<=1','MC_OLD_F>0<=1','Date to Delivery',
'Date to insert','Date of Entery']]
izmir_limis a view/copy of izmir. You subsequently attempt to assign to it. This is what is throwing the error. Use this instead:
izmir_lim是 的视图/副本izmir。您随后尝试分配给它。这就是抛出错误的原因。改用这个：
izmir_lim = izmir[['Gender','Age','MC_OLD_M>=60','MC_OLD_F>=60',
'MC_OLD_M>18','MC_OLD_F>18','MC_OLD_18>M>5',
'MC_OLD_18>F>5','MC_OLD_M_Child<5','MC_OLD_F_Child<5',
'MC_OLD_M>0<=1','MC_OLD_F>0<=1','Date to Delivery',
'Date to insert','Date of Entery']].copy()
Whenever you 'create' a new dataframe from another in the following fashion:
每当您以以下方式从另一个数据帧“创建”一个新数据帧时：
new_df = old_df[list_of_columns_names]
new_dfwill have a truthy value in it's is_copyattribute. When you attempt to assign to it, pandas throws the SettingWithCopyWarning.
new_df将在其is_copy属性中具有真实值。当您尝试分配给它时，pandas 会抛出SettingWithCopyWarning.
new_df.iloc[0, 0] = 1 # Should throw an error
You can overcome this in several ways.
您可以通过多种方式克服这一点。
Option #1
选项1
new_df = old_df[list_of_columns_names].copy()
Option #2 (as @ayhan suggested in comments)
选项#2（如@ayhan 在评论中建议的那样）
new_df = old_df[list_of_columns_names]
new_df.is_copy = None
Option #3
选项#3
new_df = old_df.loc[:, list_of_columns_names]
