Plotting error after creating new category: 'Float64Index' object has no attribute 'add_categories'

• [x ] I have checked that this issue has not already been reported.
• [x ] I have confirmed this bug exists on the latest version of scanpy.
• (optional) I have confirmed this bug exists on the master branch of scanpy.

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When updating a category or creating a new one, it is not possible to plot the associated umap with the new category.

pbmc = sc.datasets.pbmc68k_reduced()
sc.pl.umap(pbmc, color = 'phase')
new_cluster_names = [
    'A', 'B', 'C']
pbmc.obs['cell_types'] = pbmc.obs['phase']
pbmc.obs['cell_types'].cat.categories = new_cluster_names
sc.pl.umap(pbmc, color=['cell_types'])

pbmc.rename_categories('phase', new_cluster_names)
sc.pl.umap(pbmc, color=['phase'])

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-82-890b788bf078> in <module>
----> 1 sc.pl.umap(pbmc, color=['phase'])

~/miniconda3/envs/single_cell_181/lib/python3.7/site-packages/scanpy/plotting/_tools/scatterplots.py in umap(adata, **kwargs)
    657     tl.umap
    658     """
--> 659     return embedding(adata, 'umap', **kwargs)
    660 
    661 

~/miniconda3/envs/single_cell_181/lib/python3.7/site-packages/scanpy/plotting/_tools/scatterplots.py in embedding(adata, basis, color, gene_symbols, use_raw, sort_order, edges, edges_width, edges_color, neighbors_key, arrows, arrows_kwds, groups, components, layer, projection, scale_factor, color_map, cmap, palette, na_color, na_in_legend, size, frameon, legend_fontsize, legend_fontweight, legend_loc, legend_fontoutline, vmax, vmin, vcenter, norm, add_outline, outline_width, outline_color, ncols, hspace, wspace, title, show, save, ax, return_fig, **kwargs)
    255             color_source_vector,
    256             palette=palette,
--> 257             na_color=na_color,
    258         )
    259 

~/miniconda3/envs/single_cell_181/lib/python3.7/site-packages/scanpy/plotting/_tools/scatterplots.py in _color_vector(adata, values_key, values, palette, na_color)
   1275         # Set color to 'missing color' for all missing values
   1276         if color_vector.isna().any():
-> 1277             color_vector = color_vector.add_categories([to_hex(na_color)])
   1278             color_vector = color_vector.fillna(to_hex(na_color))
   1279         return color_vector, True

AttributeError: 'Float64Index' object has no attribute 'add_categories'

Versions

scanpy==1.8.1 anndata==0.7.6 umap==0.5.1 numpy==1.21.1 scipy==1.7.0 pandas==1.3.1 scikit-learn==0.24.2 statsmodels==0.12.2 python-igraph==0.9.6 pynndescent==0.5.4

[YitengDang]

This might be due to updates in pandas >1.3.0. The command pbmc.rename_categories('phase', new_cluster_names) seems to be deprecated. In particular, the “inplace” option is no longer valid, so it seems that one can only create a copy of the renamed categories and store it. Hence, the new command should be pbmc.obs['phase'] = pbmc.obs['phase'].cat.rename_categories(new_cluster_names). I checked that this works on a different data set, but haven’t checked for pbmc. If this fully fixes the problem, only the tutorial needs to be updated (the command for renaming the clusters) and scanpy doesn’t need to be modified.

Reference: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.rename_categories.html

[sirrommit]

This might be due to updates in pandas >1.3.0. The command pbmc.rename_categories('phase', new_cluster_names) seems to be deprecated. In particular, the “inplace” option is no longer valid, so it seems that one can only create a copy of the renamed categories and store it. Hence, the new command should be pbmc.obs['phase'] = pbmc.obs['phase'].cat.rename_categories(new_cluster_names). I checked that this works on a different data set, but haven’t checked for pbmc. If this fully fixes the problem, only the tutorial needs to be updated (the command for renaming the clusters) and scanpy doesn’t need to be modified.

Reference: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.cat.rename_categories.html

I have verified that this change works in the scanpy clustering tutorial. The exact change I made was adata.rename_categories('leiden', new_cluster_names) became adata.obs['leiden'] =adata.obs['leiden'].cat.rename_categories(new_cluster_names)