Plotnine extension for likert-like plotting using divergent bar charts

gglikert.py

from plotnine import *
import pandas as pd

class geom_likert(geom_col):
    def __init__(self, **kwargs):
        super().__init__(**kwargs)
    def __radd__(self, other):
        if isinstance(other, ggplot):
            df = other.data
            mapping = other.mapping
            item = mapping["x"]
            response = mapping["fill"]
            df_counts = df.groupby(item)[response].value_counts().reset_index(name="count")
            likert_options = df[response].cat.categories.tolist()
            if len(likert_options)%2 == 1:
                neutral_option = likert_options[len(likert_options) // 2]
                neutral_mask = df_counts[response] == neutral_option
                df_counts["count"] = df_counts["count"].astype(float)
                df_counts.loc[neutral_mask, "count"] = df_counts.loc[neutral_mask, "count"] / 2
                df_counts = pd.concat([df_counts, df_counts[neutral_mask].assign(count=lambda d: -d["count"])], ignore_index=True)
            negative_threshold = likert_options[len(likert_options) // 2 -1]
            df_counts.loc[df_counts[response] <= negative_threshold, "count"] = -df_counts["count"]
            df_counts["prop"] = df_counts["count"] / df_counts.groupby(item)["count"].transform(lambda x: x.abs().sum())
            other += geom_col(aes(y="prop"),position=position_stack(reverse=True),
                           data=df_counts[df_counts["count"] > 0])
            other += geom_col(aes(y="prop"),position=position_stack(),
                            data=df_counts[df_counts["count"] < 0])
            other += scale_y_continuous(labels=lambda l: ["{:.0f}%".format(abs(v) * 100) for v in l], limits=(-1, 1)) 
            other +=  geom_hline(yintercept=0, color="gray", size=0.5, linetype="dashed")
            other +=  coord_flip()
            return other
        return NotImplemented