规范错误：使用 groupby（） 不支持嵌套重命名器

Question

你能帮我解决我的代码中的这个问题吗，因为使用pandas (groupby()、agg())的空间连接给了我下面的错误:

我有一个数据框 df，我使用它中的几列来分组：n 以下方式我几乎得到了我需要的表（数据框）。缺少的是包含每个组中的行数的附加列。换句话说，我有平均值，但我也想知道有多少数字被用来获得这些手段。

简而言之：如何获取数据帧的分组统计信息？

法典：

def bin_the_midpoints(bins, midpoints):
    b = bins.copy()
    m = midpoints.copy()
    reindexed = b.reset_index().rename(columns={'index':'bins_index'})
    joined = gpd.tools.sjoin(reindexed, m)
    bin_stats = joined.groupby('bins_index')['offset']\
                      .agg({'fold': len, 'min_offset': np.min})
    return gpd.GeoDataFrame(b.join(bin_stats))
bin_stats = bin_the_midpoints(bins, midpoints)

错误：

---------------------------------------------------------------------------
SpecificationError                        Traceback (most recent call last)
Input In [103], in <cell line: 9>()
      6     bin_stats = joined.groupby('bins_index')['offset']\
      7                       .agg({'fold': len, 'min_offset': np.min})
      8     return gpd.GeoDataFrame(b.join(bin_stats))
----> 9 bin_stats = bin_the_midpoints(bins, midpoints)

Input In [103], in bin_the_midpoints(bins, midpoints)
      4 reindexed = b.reset_index().rename(columns={'index':'bins_index'})
      5 joined = gpd.tools.sjoin(reindexed, m)
----> 6 bin_stats = joined.groupby('bins_index')['offset']\
      7                   .agg({'fold': len, 'min_offset': np.min})
      8 return gpd.GeoDataFrame(b.join(bin_stats))

File ~\anaconda3\envs\GeoSynapps\lib\site-packages\pandas\core\groupby\generic.py:271, in SeriesGroupBy.aggregate(self, func, engine, engine_kwargs, *args, **kwargs)
    267 elif isinstance(func, abc.Iterable):
    268     # Catch instances of lists / tuples
    269     # but not the class list / tuple itself.
    270     func = maybe_mangle_lambdas(func)
--> 271     ret = self._aggregate_multiple_funcs(func)
    272     if relabeling:
    273         # error: Incompatible types in assignment (expression has type
    274         # "Optional[List[str]]", variable has type "Index")
    275         ret.columns = columns  # type: ignore[assignment]

File ~\anaconda3\envs\GeoSynapps\lib\site-packages\pandas\core\groupby\generic.py:307, in SeriesGroupBy._aggregate_multiple_funcs(self, arg)
    301 def _aggregate_multiple_funcs(self, arg) -> DataFrame:
    302     if isinstance(arg, dict):
    303 
    304         # show the deprecation, but only if we
    305         # have not shown a higher level one
    306         # GH 15931
--> 307         raise SpecificationError("nested renamer is not supported")
    309     elif any(isinstance(x, (tuple, list)) for x in arg):
    310         arg = [(x, x) if not isinstance(x, (tuple, list)) else x for x in arg]

SpecificationError: nested renamer is not supported

Answer 1

你必须阅读更多关于熊猫中agg方法的信息。你可以很容易地在这个方法中添加许多计算。

例如，您可以写：

df.groupby(by=[...]).agg({'col1': ['count', 'sum', 'min']})