Data dashboard in Jupyter visualizing Covid-19 hospitalization data from remote source.

data_dashboard_covid19_remote.py

import pandas as pd
import numpy as np
from bokeh.plotting import figure, show, output_notebook
import ipywidgets as widgets
from IPython.display import display, clear_output
output_notebook()
 
"""Load Iris dataset and transform the pandas DataFrame"""
data = pd.read_csv("https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/hospitalizations/covid-hospitalizations.csv")
data['date'] = pd.to_datetime(data['date'])

"""Define callback function for the UI"""
def dropdown_cb(x):
    p = create_figure(
        country_dropdown.children[0].value,
        indicator_dropdown.children[0].value,
        data)
    fig[0] = p
    with output_figure:
        clear_output(True)
        show(fig[0])
    return x
    

def create_figure(country, indicator, data):
    """This is a helper function that creates a new figure and 
    plots values from all three species. x_var and y_var control
    the features on each axis."""
    data = data[(data['entity'] == country) & (data['indicator'] == indicator)].sort_values(by='date')
    p = figure(title="",
           x_axis_label="Days",
           y_axis_label=indicator,
            x_axis_type='datetime')
    line = p.line(data['date'], data['value'], line_width=2)

    return p

# The output widget is where we direct our figures
output_figure = widgets.Output()
 
# Create the default figure
fig = []  # Storing the figure in a singular list is a bit of a 
          # hack. We need it to properly mutate the current
          # figure in our callbacks.
p = create_figure(
    "Algeria",
    "Daily ICU occupancy",
    data)
fig.append(p)
with output_figure:
    show(fig[0])
 
# Dropdown menu for x-axis feature.
country_dropdown = widgets.interactive(dropdown_cb,
                                 x=data['entity'].unique());
country_dropdown.children[0].description = 'Country'
country_dropdown.children[0].value = data['entity'].unique()[0]
 
# Dropdown menu for y-axis feature.
indicator_dropdown = widgets.interactive(dropdown_cb,
                                 x=data['indicator'].unique());
indicator_dropdown.children[0].description = 'Indicator'
indicator_dropdown.children[0].value = data['indicator'].unique()[0]

# This creates the menu 
menu=widgets.VBox([country_dropdown, indicator_dropdown])
 
"""Create the full app with menu and output"""
# The Layout adds some styling to our app.
# You can add Layout to any widget.
app_layout = widgets.Layout(display='flex',
                flex_flow='row nowrap',
                align_items='center',
                border='none',
                width='100%',
                margin='5px 5px 5px 5px')
 
# The final app is just a box
app=widgets.Box([menu, output_figure], layout=app_layout)
 
# Display the app
display(app)