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[英]Python Pandas Warning: A value is trying to be set on a copy of a slice from a DataFrame
[英]Setting a value to a pandas DataFrame: Warning A value is trying to be set on a copy of a slice from a DataFrame
為什么是這樣? 我將在熊貓中制作4個數據框:
>>> df = pd.DataFrame({"A": ["One","Two","Three"], "B": ["Two","Three","Four"], "C": ["Three","Four","Five"], "D": ["Four","Five","Six"]})
>>> df
A B C D
0 One Two Three Four
1 Two Three Four Five
2 Three Four Five Six
>>> df["C"][1] = "One Hundred"
一切正常。 現在讓我們先做兩列,然后添加兩列,一列用“”,另一列用NaN
>>> df = pd.DataFrame({"A": [1,2,3], "B": [2,3,4]})
>>> df
A B
0 1 2
1 2 3
2 3 4
>>> df["C"] = ""
>>> df["D"] = pd.np.nan
>>> df
A B C D
0 1 2 NaN
1 2 3 NaN
2 3 4 NaN
>>> df["C"][1] = "hello"
Warning (from warnings module):
File "__main__", line 1
SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
出現警告! 好的:(這是問題:警告的含義是什么?)但讓我們繼續:
現在我這樣做:
>>> df = pd.DataFrame({"A": [1,2,3], "B": [2,3,4], "C": [3,4,5], "D": [4,5,6]})
>>> df
A B C D
0 1 2 3 4
1 2 3 4 5
2 3 4 5 6
>>> df["C"][1] = 100
並且沒有警告出現。 好。
現在,讓我們再次觸發警告:
>>> df = pd.DataFrame({"A": [1,2,3], "B": [2,3,4]})
>>> df["C"] = ""
>>> df["D"] = pd.np.nan
>>> df
A B C D
0 1 2 NaN
1 2 3 NaN
2 3 4 NaN
>>> df["C"][1] = "hello"
>>>
這次沒有警告!?
我正在使用IDLE 3.5.2,Python版本:3.5.2 ...
這是錯誤嗎? 我不能說,因為我正在學習。
我是否應該用所有列編寫一個新的單獨的DataFrame,然后每次將其等於df的列?
我應該列出一個python列表嗎?...
有沒有辦法在沒有警告的情況下遍歷和編輯原始數據框?
為什么沒有每次都彈出該警告?
謝謝你的時間。
您可以使用loc
或iloc
df
Out[1445]:
A A_1 B
0 1.0 1.0 A
1 NaN NaN A
2 3.0 3.0 NaN
3 4.0 4.0 B
df.iloc[1,1]='Yourvalue1'
df
Out[1447]:
A A_1 B
0 1.0 1 A
1 NaN Yourvalue1 A
2 3.0 3 NaN
3 4.0 4 B
df.loc[1,'A']
Out[1448]: nan
df.loc[1,'A']='Yourvalue2'
df
Out[1450]:
A A_1 B
0 1 1 A
1 Yourvalue2 Yourvalue1 A
2 3 3 NaN
3 4 4 B
正確的方法是:
df["column_name"][0] = "hello"
如果使用點column_name方式,則顯然是在選擇切片。 如果您使用這種(正確的)方法,那么您就是在“觸摸單元格”。
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