인프런 커뮤니티 질문&답변

강의 회차 : [20/20] 지역별 분양가를 시각화하고 정리하기

질문 : 마지막 시각화 단계에서, boxplot, boxenplot, violinplot 다 잘 구현되는데 swarmplot만 계속 에러가 납니다. 구글에서 에러메시지 검색도 해 봤는데, 잘 해결이 안되네요.. 확인해 주실 수 있으신가요.

* 에러메시지도 함께 첨부드립니다.

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[307], line 2
      1 plt.figure(figsize=(24, 7))
----> 2 sns.swarmplot(df, x='지역명', y='평당분양가격')

File ~/anaconda3/lib/python3.10/site-packages/seaborn/categorical.py:2664, in swarmplot(data, x, y, hue, order, hue_order, dodge, orient, color, palette, size, edgecolor, linewidth, hue_norm, native_scale, formatter, legend, warn_thresh, ax, **kwargs)
   2657     linewidth = size / 10
   2659 kwargs.update(dict(
   2660     s=size ** 2,
   2661     linewidth=linewidth,
   2662 ))
-> 2664 p.plot_swarms(
   2665     dodge=dodge,
   2666     color=color,
   2667     edgecolor=edgecolor,
   2668     warn_thresh=warn_thresh,
   2669     plot_kws=kwargs,
   2670 )
   2672 p._add_axis_labels(ax)
   2673 p._adjust_cat_axis(ax, axis=p.cat_axis)

File ~/anaconda3/lib/python3.10/site-packages/seaborn/categorical.py:330, in _CategoricalPlotterNew.plot_swarms(self, dodge, color, edgecolor, warn_thresh, plot_kws)
    321 def plot_swarms(
    322     self,
    323     dodge,
   (...)
    327     plot_kws,
    328 ):
--> 330     width = .8 * self._native_width
    331     offsets = self._nested_offsets(width, dodge)
    333     iter_vars = [self.cat_axis]

File ~/anaconda3/lib/python3.10/site-packages/seaborn/categorical.py:229, in _CategoricalPlotterNew._native_width(self)
    226 @property
    227 def _native_width(self):
    228     """Return unit of width separating categories on native numeric scale."""
--> 229     unique_values = np.unique(self.comp_data[self.cat_axis])
    230     if len(unique_values) > 1:
    231         native_width = np.nanmin(np.diff(unique_values))

File ~/anaconda3/lib/python3.10/site-packages/seaborn/_oldcore.py:1134, in VectorPlotter.comp_data(self)
   1132         else:
   1133             comp_col = pd.Series(dtype=float, name=var)
-> 1134         comp_data.insert(0, var, comp_col)
   1136     self._comp_data = comp_data
   1138 return self._comp_data

File ~/anaconda3/lib/python3.10/site-packages/pandas/core/frame.py:4786, in DataFrame.insert(self, loc, column, value, allow_duplicates)
   4783 if not isinstance(loc, int):
   4784     raise TypeError("loc must be int")
-> 4786 value = self._sanitize_column(value)
   4787 self._mgr.insert(loc, column, value)

File ~/anaconda3/lib/python3.10/site-packages/pandas/core/frame.py:4877, in DataFrame._sanitize_column(self, value)
   4875     return _reindex_for_setitem(value, self.index)
   4876 elif is_dict_like(value):
-> 4877     return _reindex_for_setitem(Series(value), self.index)
   4879 if is_list_like(value):
   4880     com.require_length_match(value, self.index)

File ~/anaconda3/lib/python3.10/site-packages/pandas/core/frame.py:11620, in _reindex_for_setitem(value, index)
  11616 except ValueError as err:
  11617     # raised in MultiIndex.from_tuples, see test_insert_error_msmgs
  11618     if not value.index.is_unique:
  11619         # duplicate axis
> 11620         raise err
  11622     raise TypeError(
  11623         "incompatible index of inserted column with frame index"
  11624     ) from err
  11625 return reindexed_value

File ~/anaconda3/lib/python3.10/site-packages/pandas/core/frame.py:11615, in _reindex_for_setitem(value, index)
  11613 # GH#4107
  11614 try:
> 11615     reindexed_value = value.reindex(index)._values
  11616 except ValueError as err:
  11617     # raised in MultiIndex.from_tuples, see test_insert_error_msmgs
  11618     if not value.index.is_unique:
  11619         # duplicate axis

File ~/anaconda3/lib/python3.10/site-packages/pandas/core/series.py:4914, in Series.reindex(self, index, axis, method, copy, level, fill_value, limit, tolerance)
   4897 @doc(
   4898     NDFrame.reindex,  # type: ignore[has-type]
   4899     klass=_shared_doc_kwargs["klass"],
   (...)
   4912     tolerance=None,
   4913 ) -> Series:
-> 4914     return super().reindex(
   4915         index=index,
   4916         method=method,
   4917         copy=copy,
   4918         level=level,
   4919         fill_value=fill_value,
   4920         limit=limit,
   4921         tolerance=tolerance,
   4922     )

File ~/anaconda3/lib/python3.10/site-packages/pandas/core/generic.py:5360, in NDFrame.reindex(self, labels, index, columns, axis, method, copy, level, fill_value, limit, tolerance)
   5357     return self._reindex_multi(axes, copy, fill_value)
   5359 # perform the reindex on the axes
-> 5360 return self._reindex_axes(
   5361     axes, level, limit, tolerance, method, fill_value, copy
   5362 ).__finalize__(self, method="reindex")

File ~/anaconda3/lib/python3.10/site-packages/pandas/core/generic.py:5375, in NDFrame._reindex_axes(self, axes, level, limit, tolerance, method, fill_value, copy)
   5372     continue
   5374 ax = self._get_axis(a)
-> 5375 new_index, indexer = ax.reindex(
   5376     labels, level=level, limit=limit, tolerance=tolerance, method=method
   5377 )
   5379 axis = self._get_axis_number(a)
   5380 obj = obj._reindex_with_indexers(
   5381     {axis: [new_index, indexer]},
   5382     fill_value=fill_value,
   5383     copy=copy,
   5384     allow_dups=False,
   5385 )

File ~/anaconda3/lib/python3.10/site-packages/pandas/core/indexes/base.py:4274, in Index.reindex(self, target, method, level, limit, tolerance)
   4271     raise ValueError("cannot handle a non-unique multi-index!")
   4272 elif not self.is_unique:
   4273     # GH#42568
-> 4274     raise ValueError("cannot reindex on an axis with duplicate labels")
   4275 else:
   4276     indexer, _ = self.get_indexer_non_unique(target)

ValueError: cannot reindex on an axis with duplicate labels