altair.

There are many visualisation libraries in python out there and altair offers some original features. It offers a wide variety of charts, a grammar-like api, loads of interactivity features and the option of exporting directly to the browser.

Introduction Recipe Properties Line Chart Types Operators Json Downsides

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Notes

Don't forget to first have your dataframe ready.

import pathlib 
import pandas as pd
import altair as alt

df = pd.read_csv("content/data/birthdays.csv")

def clean_dataset(dataf):
    return (dataf
            .assign(date = lambda d: pd.to_datetime(d['date']))
            .assign(yday = lambda d: d['date'].dt.dayofyear)
            .drop(columns=['Unnamed: 0'])
            .groupby(['date', 'wday', 'yday'])
            .agg(births = ('births', 'sum'), month=('month', 'first'))
            .reset_index())

plot_df = df.pipe(clean_dataset)

The code for the plot is listed below;

(alt.Chart(plot_df)
  .mark_point(color='black')
  .encode(x='yday', y='births')
  .properties(width=600, height=300)
  .interactive())

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