Bar Chart based on Storytelling With Data - better bar chart visualization

barchart_stwd.py

from typing import Any
import pandas as pd

import plotly.graph_objects as go
import pandas as pd


def barchart(
    df: pd.DataFrame, x_col: str, y_col: str, 
    title: str | None = None, 
    latent_color : str = 'gray',
    prominent_color: str = 'orange',
    prominent_value: Any | None = None,
    **kwargs: dict,
    ) -> go.Figure:
    """_summary_

    Args:
        df (pd.DataFrame): Dataframe to plot
        x_col (str): Name of x coloumn
        y_col (str): Name of y coloumn
        title (str | None, optional): Chart title. Defaults to None.
        latent_color (str, optional): Color to use for the values we don't want to highlight. Defaults to 'gray'.
        prominent_color (str, optional): Color to use for the  value we want to highlight. Defaults to 'orange'.
        prominent_value (Any | None, optional): Value of the category we want to highlight. Defaults to None.

    Returns:
        go.Figure: Plotly figure object
    """
    
    colors =  (df[x_col] == prominent_value).replace(False, latent_color).replace(True, prominent_color).to_list()
    fig = go.Figure(data=[
        go.Bar(
            x=df[x_col],
            y=df[y_col],
            marker_color=colors
        )],
        layout=go.Layout(
            title=title,
            xaxis=dict(title=x_col, showgrid=False),
            yaxis=dict(title=y_col, showgrid=False),
            plot_bgcolor='white',
            paper_bgcolor='white'
        )
    )
    fig.update_layout(**kwargs)
    return fig


if __name__ == "__main__":
        
    data = {'categories': ['A', 'B', 'C', 'D', 'E'],
            'values': [23, 45, 56, 78, 90]}
    df = pd.DataFrame(data)
    fig = barchart(df, 'categories', 'values', prominent_value='C', title='My Chart', yaxis_showgrid=True)
    fig.show()