Python 2.7 将数据帧传递给函数时，在pandas中设置CopyWarning

我有以下处理数据帧的代码：

header_updated = self.schemata.get_header_from_schema_id(df.at[0, 'schema_id'])
for col in (col for col in df.columns.values if df[col].dtype == 'object' and col not in [col_name[0] for col_name in self.header + header_updated if col_name[1] == 'string']):
    df.loc[:, col] = df.loc[:, col].apply(lambda x: is_nan(x))
    df.columns = ['timestamp_create', 'schema_id'] + [item[0] for item in header_updated] + df.columns.tolist()[len(header_updated)+2:]
for column in [column for column in df.columns.values if column not in [elem[0] for elem in self.header] and column not in ('timestamp_create', 'schema_id')]:
    del df[column]
for elem in [elem for elem in self.header if elem[0] not in df.columns.values]:
    df[elem[0]] = 0 if elem[1] == 'uint64' else ''
df = df[['timestamp_create', 'schema_id'] + [elem[0] for elem in self.header]]
if 'rat' in df.columns.values:
    df['rat'].fillna('unclassified', inplace=True)
for el in (col_name[0] for col_name in self.header if col_name[1] == 'string' and col_name[0] not in self.numeric_columns):
    df[el].fillna('', inplace=True)
df.fillna(0, inplace=True, downcast='infer')
df[self.numeric_columns].astype('int64')

如果我把它放在一个函数上，比如：

def进程\框架\过时\模式（self，df）：…

我收到错误消息：

/usr/lib64/python2.7/site-packages/pandas/core/generic.py:2862: 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
self._update_inplace(new_data)

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为什么要在使用函数时抱怨？

因为您正在处理从原始数据帧复制的数据帧片段。如果您对整个数据帧而不是副本进行操作，应该可以。警告您未更改原始数据帧。这行是否导致问题：

df.loc[：，col]=df.loc[：，col]。应用（lambda x:is_nan（x））

？

data=df.copy（deep=True）

然后返回深度副本解决了问题