The document outlines a presentation by Bence Kiss-Dobronyi from Cambridge Econometrics on visualizing natural gas trade flows in the EU-28, emphasizing the need for better energy dependency analysis. It compares previous methods using Excel with a new Python-based approach that allows for reproducible and flexible research while maintaining comprehensive data visualization. The presentation highlights energy dependency issues in the EU and the advancements made in integrating data processing and visualization tools.

1. Visualising natural gas trade flows in the EU-28
BI Forum, Budapest
Bence Kiss-Dobronyi
14/11/2018
Utilising Python for reproducible and flexible research

2. Who we are?
• Cambridge Econometrics is an
economic research consultancy
spin-off of the
University of Cambridge
• Three offices in Europe:
– Cambridge
– Brussels
– Budapest
• Our Budapest office opened in
September 2018
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Visualising natural gas trade flows in the EU-28 // Bence Kiss-Dobronyi

3. What we do?
• We work in three thematic areas:
– Economy
– Social
– Environment
including
• Energy
• Climate change
• Circular economy
• Natural resources
– + Training courses
• Our clients include:
– European Commission
– European Climate Foundation
– CEDEFOP
– Mayor of London
– New Climate Economy
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Visualising natural gas trade flows in the EU-28 // Bence Kiss-Dobronyi

4. A note on reproducible research
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Visualising natural gas trade flows in the EU-28 // Bence Kiss-Dobronyi
Source: Cambridge Econometrics (2018)
Jupyter notebooks with
references to the pages
where data is used

5. Energy dependency in the EU
• In fossil fuels increasing
dependency on imports
• EU strategy: to strengthen
energy security
• T&E commissioned a report in
2016 and again this year, to
look at oil imports and to
develop a tool to support
understanding
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Visualising natural gas trade flows in the EU-28 // Bence Kiss-Dobronyi
Crude oil dependency in the EU-28,
Source: T&E (2016), https://www.transportenvironment.org/

6. Natural gas dependency
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Visualising natural gas trade flows in the EU-28 // Bence Kiss-Dobronyi
Top-right: Energy consumption trends by energy source in EU-28,
Source: Cambridge Econometrics (2018)
Left: Import routes for natural gas to the EU, Source: Vattenfall
(2013), https://corporate.vattenfall.com/
Figure 1.1 Energy consumption trends by energy source in EU-28
Notes: MTOE is ‘million tonnes of oil equivalent’.
Source: Eurostat.

7. Oil dependency tool
• Original process:
– Calculations were done in Excel
– Excel macros were used to convert data to
csv
– Csv was used as source for
advanced D3.js visualisation
• Pro
– Custom visualisation
– Low-scale infrastructure setup
• Contra
– Hardly reproducible, hard to update
– Not flexible in terms of vis
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Visualising natural gas trade flows in the EU-28 // Bence Kiss-Dobronyi
Source: Cambridge Econometrics (2016)

8. Natural gas dependency tool
Switch to a Python based integrated approach
• New process:
– Eurostat data is processed with
pandas (jupyter → hydrogen)
– Visualisation is done with
Plot.ly’s Dash
– Fully integrated process, can be
updated with new source files + a
single command
– Flexible, easy to refine
– Cross-filtering / reactive
interactions
• Contra
– Limited customisation / number
of visualisation types
– Can be slow
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Visualising natural gas trade flows in the EU-28 // Bence Kiss-Dobronyi
Source: Cambridge Econometrics (2018)

9. Questions / comments are welcome
Contact
Email
bkd@camecon.com
Twitter
@bencekd
@CambridgeEcon
https://www.camecon.com