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python - ValueError：无法从 Pandas 中的重复轴错误重新索引

问题描述

我有最后一列，我试图获得 15 分钟的最大值和最小值。通过执行此代码。但我无法为此代码包含类型。因为我在 Type 列中有很多类型。我得到这个错误。

Timestamp        Last           Max            Type
1/20/19 12:15    3071.56                       Ada
1/20/19 12:17    3097.82                       Btc
1/20/19 12:17    3097.82                       Ada
1/20/19 12:18    3095.25                       Ada
1/20/19 12:19    3087.42                       Btc
1/20/19 12:20    3095.29                       Btc
1/20/19 12:21    3095.25                       Btc
1/20/19 12:22    3093.11                       Btc
1/20/19 12:23    3103                          Btc
1/20/19 12:24    3095                          Btc
1/20/19 12:25    3100.6                        Btc
1/20/19 12:26    3099.84                       Ada
1/20/19 12:27    3098.77                       Ada
1/20/19 12:29    3097.24                       Ada
1/20/19 12:29    3090          3103            Ada
1/20/19 12:30    3090          3103            Ada
1/20/19 12:31    3094.29       3103            Ada

我想得到一个包含 Ada_max 和 Btc_max 的列

这是我必须在 15 分钟内计算最后一列的最大值的代码。

df['Prev15minMax'] = df['Last'].rolling('15min', min_periods=16).max()
df['Prev15minMin'] = df['Last'].rolling('15min', min_periods=16).min()

代码尝试：

for v in df['Type'].unique():
    df['Prev15minMax_{v}'] = df.loc[df['Type'].eq(v), 'Last_new'].rolling('15min', min_periods=15).max()

我得到的错误：

ValueError                                Traceback (most recent call last)
<ipython-input-6-43ab5f7d0bc2> in <module>()
      1 
      2 for v in df['Type'].unique():
----> 3     df['Prev60minMax_{v}'] = df.loc[df['Type'].eq(v), 'Last'].rolling('60min', min_periods=60).max()

/usr/local/lib/python3.6/site-packages/pandas/core/frame.py in __setitem__(self, key, value)
   3114         else:
   3115             # set column
-> 3116             self._set_item(key, value)
   3117 
   3118     def _setitem_slice(self, key, value):

/usr/local/lib/python3.6/site-packages/pandas/core/frame.py in _set_item(self, key, value)
   3189 
   3190         self._ensure_valid_index(value)
-> 3191         value = self._sanitize_column(key, value)
   3192         NDFrame._set_item(self, key, value)
   3193 

/usr/local/lib/python3.6/site-packages/pandas/core/frame.py in _sanitize_column(self, key, value, broadcast)
   3361 
   3362         if isinstance(value, Series):
-> 3363             value = reindexer(value)
   3364 
   3365         elif isinstance(value, DataFrame):

/usr/local/lib/python3.6/site-packages/pandas/core/frame.py in reindexer(value)
   3353                     # duplicate axis
   3354                     if not value.index.is_unique:
-> 3355                         raise e
   3356 
   3357                     # other

/usr/local/lib/python3.6/site-packages/pandas/core/frame.py in reindexer(value)
   3348                 # GH 4107
   3349                 try:
-> 3350                     value = value.reindex(self.index)._values
   3351                 except Exception as e:
   3352 

/usr/local/lib/python3.6/site-packages/pandas/core/series.py in reindex(self, index, **kwargs)
   3320     @Appender(generic._shared_docs['reindex'] % _shared_doc_kwargs)
   3321     def reindex(self, index=None, **kwargs):
-> 3322         return super(Series, self).reindex(index=index, **kwargs)
   3323 
   3324     def drop(self, labels=None, axis=0, index=None, columns=None,

/usr/local/lib/python3.6/site-packages/pandas/core/generic.py in reindex(self, *args, **kwargs)
   3683         # perform the reindex on the axes
   3684         return self._reindex_axes(axes, level, limit, tolerance, method,
-> 3685                                   fill_value, copy).__finalize__(self)
   3686 
   3687     def _reindex_axes(self, axes, level, limit, tolerance, method, fill_value,

/usr/local/lib/python3.6/site-packages/pandas/core/generic.py in _reindex_axes(self, axes, level, limit, tolerance, method, fill_value, copy)
   3701             obj = obj._reindex_with_indexers({axis: [new_index, indexer]},
   3702                                              fill_value=fill_value,
-> 3703                                              copy=copy, allow_dups=False)
   3704 
   3705         return obj

/usr/local/lib/python3.6/site-packages/pandas/core/generic.py in _reindex_with_indexers(self, reindexers, fill_value, copy, allow_dups)
   3804                                                 fill_value=fill_value,
   3805                                                 allow_dups=allow_dups,
-> 3806                                                 copy=copy)
   3807 
   3808         if copy and new_data is self._data:

/usr/local/lib/python3.6/site-packages/pandas/core/internals.py in reindex_indexer(self, new_axis, indexer, axis, fill_value, allow_dups, copy)
   4412         # some axes don't allow reindexing with dups
   4413         if not allow_dups:
-> 4414             self.axes[axis]._can_reindex(indexer)
   4415 
   4416         if axis >= self.ndim:

/usr/local/lib/python3.6/site-packages/pandas/core/indexes/base.py in _can_reindex(self, indexer)
   3557         # trying to reindex on an axis with duplicates
   3558         if not self.is_unique and len(indexer):
-> 3559             raise ValueError("cannot reindex from a duplicate axis")
   3560 
   3561     def reindex(self, target, method=None, level=None, limit=None,

ValueError: cannot reindex from a duplicate axis

标签： pythonpandas

解决方案

两边逐行拟合：

for v in df['Type'].unique():
    mask = df['Type'].eq(v)
    df.loc[mask, f'Prev15minMax_{v}'] = (df.loc[mask,'Last_new']
                                           .rolling('15min',min_periods=15)
                                           .max())

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