Advanced Dashboarding#

This exercise is entirely freeform. Get into groups of 3-4 people (if available!) and start building a dashboard, with everything you have learned in this tutorial. By the end of the exercise you should have a dashboard that:

  • Uses datashading to render the whole dataset

  • Builds a pipeline using the .interactive method

  • Uses a widget to filter the data either using linked selections or using a widget (e.g. a RangeSlider)

  • Uses a widget to control some aspect of the styling of the plot (e.g. to select a colormap, color, or size)

  • Is servable by running panel serve Advanced_Dashboarding.ipynb in the exercise directory

import pathlib
import colorcet as cc # noqa
import holoviews as hv # noqa
import numpy as np # noqa
import pandas as pd
import panel as pn
import xarray as xr

import hvplot.pandas # noqa: API import
import hvplot.xarray # noqa: API import


As a starting point we will load the data; everything else is up to you:

df = pd.read_parquet(pathlib.Path('../../data/earthquakes-projected.parq'))
df = df.set_index(df.time)
CPU times: user 3.02 s, sys: 408 ms, total: 3.43 s
Wall time: 1.83 s
ds = xr.open_dataarray(pathlib.Path('../../data/raster/'))
cleaned_ds = ds.where(ds.values != ds.nodatavals).sel(band=1) = 'population'

You don’t really know what to build? Here are some ideas:

  • Build a dashboard with a pipeline that filters the data on one or more of the columns (e.g. magnitude using a RangeSlider or time using a DateRangeSlider) and then datashades it

  • Build a dashboard with multiple views of the data (e.g. longitude vs. latitude, magnitude vs. depth etc.) and cross-filters the data (see the Glaciers notebook for reference)

  • Build a dashboard that allows you to select multiple earthquakes and compute (and display) statistics on them.

This web page was generated from a Jupyter notebook and not all interactivity will work on this website. Right click to download and run locally for full Python-backed interactivity.

Right click to download this notebook from GitHub.