Bin data using custom intervals with pandas (integers)

bin_integers.py

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


def bin_ages(age_series: pd.Series) -> pd.Series:
    age_labels = [f"[{i}, {i+10})" for i in range(0, 91, 10)]

    age_bins = pd.IntervalIndex.from_tuples(
        [(i, i+10) for i in range(0, 91, 10)],
        closed="left"
    )

    ages_binned = pd.cut(
        age_series,
        age_bins,
        labels=age_labels,
        precision=0,
        include_lowest=True
    )

    ages_binned.sort_values(ascending=True, inplace=True)
    # Change the values from categorical to string to be able to plot them
    ages_binned = ages_binned.astype("str")

    return ages_binned


def plot_histogram(
    data_series: pd.Series,
    nbins: int,
    title: str,
    axes_titles: List[Union[str, None]]
) -> None:
    fig = px.histogram(
        x=data_series,
        nbins=nbins,
        title=title
    )

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

    fig.update_layout(
        uniformtext_minsize=14,
        uniformtext_mode="hide",
        bargap=0,
        title_x=0.5
    )

    fig.show()