Handle Categorical data with pandas (str)

cat_strings.py

import pandas as pd
import numpy as np
import plotly.express as px
from typing import List, Union


def create_evaluations(
    categories: List[str],
    mapping_values: List[str],
    length: int
) -> pd.Categorical:
    evaluations = pd.Categorical(
        np.random.choice(categories, (length,)),
        categories=categories
    )

    # The values are sorted from "terrible" to "excellent", just like in the\
    # `options` list
    evaluations.sort_values(inplace=True)

    # Map the categorical nominal values to categorical numerical values
    evaluations = evaluations.map({
        category: map_value for category, map_value in zip(categories, mapping_values)
    })

    return evaluations


def plot_column_chart(
    data_series: pd.Categorical,
    x_labels: List[str],
    title: str,
    axes_titles: List[Union[str, None]]
) -> None:
    # Change the categories' names to the desired X axis labels
    data_series = data_series.map({
        series_value: x_label for series_value, x_label in zip(data_series.unique(), x_labels)
    })

    fig = px.bar(
        x=data_series.unique(),
        y=data_series.value_counts(),
        title=title
    )

    fig.update_layout(
        xaxis_title=axes_titles[0],
        yaxis_title=axes_titles[1]
    )

    fig.update_layout(
        uniformtext_minsize=14,
        uniformtext_mode="hide",
        title_x=0.5
    )

    fig.show()