https://github.com/pierrotsmnrd/earthquakes
A dashboard to visualize earthquakes around the world between 2000 and 2020.
https://github.com/pierrotsmnrd/earthquakes
data-visualization earthquakes python
Last synced: 5 months ago
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A dashboard to visualize earthquakes around the world between 2000 and 2020.
- Host: GitHub
- URL: https://github.com/pierrotsmnrd/earthquakes
- Owner: pierrotsmnrd
- License: agpl-3.0
- Created: 2020-12-08T17:36:55.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2024-04-14T01:29:59.000Z (about 2 years ago)
- Last Synced: 2024-04-14T02:10:50.608Z (about 2 years ago)
- Topics: data-visualization, earthquakes, python
- Language: Python
- Homepage:
- Size: 2.37 GB
- Stars: 16
- Watchers: 2
- Forks: 5
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Earthquakes
A dashboard to visualise earthquakes worldwide since 2000.
## Context
A abnormal seismic activity has been recorded in late 2020 near my city, Strasbourg, France.
These unusual earthquakes may have been caused by boreholes made during the exploration phase of a geothermal energy project.
This gave me the idea of making a dashboard to display the earthquakes worldwide and learn more about this phenomenon.
## Data source
To make a good dashboard, you need good data.
I used the webservices of www.seismicportal.eu.
The dataset is updated automatically every hour, leveraging Github's Flat Data, with scripts under `scripts/flatdata`.
**File `data/viz/dataset.csv` is then always up to date` .**
If you wish to rebuild the whole dataset from scratch, there are 2 steps :
- collect the raw data from the webservice : `python scripts/scrapping/download_json.py`
- aggregate the json files into a csv file : `python scripts/scrapping/build_dataset.py`
## Data Engineering
The data engineering is done using pandas.
## Dashboard
The dashboard is made with Holoviz (using Holoviews, Geoviews and Panel) with the Bokeh backend.
## Questions ?
- If you have any question on how to use this dashboard
- If you have suggestions on how to improve it
Then please contact me on LinkedIn or on Twitter.
Pull requests are appreciated !
Also have a look to open issues for the next tasks I intend on tackle.
## Thanks
Thanks to @kcpevey and @tonyfast for their help and encouragements.