python - 我可以找到替代的 `.loc` 替代 Pandas 数据框中的替换功能吗

Question

这个问题已经有答案了:

How to deal with SettingWithCopyWarning in Pandas (21 个回答)

已关闭 5 年前。

之前，我问How to update series based on other pandas dataframe ，存在 3 个答案，但其中 3 个给出了警告，通常我会忽略这一点，但这是出于生产目的，所以我不能。这是答案和警告:

1

s = df2.set_index('Nation')['Capital City']
df1['Capital'] = df1['Country'].map(s).fillna(df1['Capital'])

警告

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

2

df1['Capital'] = df1['Country'].replace(s)

警告

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

3

s = df2.set_index('Nation')['Capital City']
df1['Capital'].update(df1['Country'].map(s))

警告

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  exec(code_obj, self.user_global_ns, self.user_ns)
/home/ubuntu/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:1: 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

如何减少警告

Answer 1

问题显然出在过滤之前的一行中。

解决方案是添加 copy像:

df1 = df[df['col'] == 10].copy()

说明:

如果稍后修改 df1 中的值，您会发现修改不会传播回原始数据 (df)，并且 Pandas 发出警告。