使用Pandas.remove_duplicates()时出错

Question

我试图通过只考虑某个子集来使用Pandas.drop_duplicates()，但得到了错误的KeyError: Index(['days'], dtype='object')

索引如下：id, event_description, attribute1, attribute 2, attribute 3, days, days_supply, days_equivalent

我想忽略属性2和属性3，所以我运行了以下命令

df = df.drop_duplicates(subset=['id', 'event_description', 'attribute1', 'days', 'days_supply', 'days_equivalent'])

它返回：

eyError                                  Traceback (most recent call last)
<ipython-input-4-3f7da32b380f> in <module>
      7 
      8 df = df.drop_duplicates(subset=['id', 'event_description', 'attribute1', 'days', 
->    9 'days_supply', 'days_equivalent'])
     10 
     11 print(df)

/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py in drop_duplicates(self, subset, keep, inplace)
   4892 
   4893         inplace = validate_bool_kwarg(inplace, "inplace")
-> 4894         duplicated = self.duplicated(subset, keep=keep)
   4895 
   4896         if inplace:

/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py in duplicated(self, subset, keep)
   4949         diff = Index(subset).difference(self.columns)
   4950         if not diff.empty:
-> 4951             raise KeyError(diff)
   4952 
   4953         vals = (col.values for name, col in self.items() if name in subset)

KeyError: Index(['days'], dtype='object')

一旦我删除了days，删除重复项就没有问题了，但是我确实需要确保我考虑到了days。这个错误需要我修复什么？

Answer 1

必须重新检查列名。Days vs days

Answer 2

尝试使用

df.drop_duplicates(subset=['id', 'event_description', 'attribute1', 'days', 'days_supply', 'days_equivalent'],inplace=True)

来自：https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop_duplicates.html

尝试使用

也许你的df格式不正确，不管怎样，如果你认为问题与dtype有关，你可以使用应用函数来检查df‘’date‘的整个数据，如下所示：

def checkType(someDate):
    ##Do verification
    return dateCorrected

df['date'] = df['date'].apply(checkType)