altair:
introduction
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 https://calmcode.io/datasets/birthdays.csv
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()
.head(1000))
plot_df = df.pipe(clean_dataset)
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