Same issue with this : pandas-dev/pandas#54485
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self.plot_data(ax=ax, plot_total_sales=plot_total_sales) |
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# plot posterior predictive distribution of sales for each of the existing products |
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x = cast(pd.DataFrame, self.X).index.values |
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existing_products = self.coords["existing_product"] |
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for i, existing_product in enumerate(existing_products): |
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az.plot_hdi( |
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x, |
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self.predictions[variable] # type: ignore |
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.transpose(..., "time") |
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.sel(existing_product=existing_product), |
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fill_kwargs={ |
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"alpha": HDI_ALPHA, |
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"color": f"C{i}", |
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"label": "Posterior predictive (HDI)", |
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}, |
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smooth=False, |
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) |
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By not using the plot method of pandas, we can get away from this as shown in the linked pandas issue
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data.plot(ax=ax) |
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if plot_total_sales: |
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data.sum(axis=1).plot(label="total sales", color="black", ax=ax) |
