text: 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.
  Notes
  For this video you'll need to install the following dependencies;
  python -m pip install jupyterlab pandas altair
  You'll also need the dataset, it can be fetched here or downloaded via;
  wget
  The python code in the beginning of this notebook is;
  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)
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