commute.correlaid.org An interactive dashboard about commuting in Germany 🚈

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# <a href='https://commute.correlaid.org' style='font-size: 1.2rem'>commute.correlaid.org</a> An interactive dashboard about commuting in Germany 🚈
## The what, the why, and the how
### Long Nguyen
### CorrelAidX Bremen
### 2020-11-06

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# What?

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# "Commuter" statistics

Source: German Federal Employment Agency

**commuters:**

> employees whose workplace is located in a different municipality from the one in which they live

> regardless of whether and how often they actually commute ¯\\\_(ツ)_/¯

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# Why?

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# Why commuter statistics?

- Identify regionally important industry/business locations

- Compare the relative importance of districts/states for work

- For Bremen especially interesting:  
  commuting between suburbs ("Speckgürtel") and urban area

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# Why a dashboard?

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# How?

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# Collecting commuter data with datenguidepy

- Ginormous collection of regional statistics at different administrative levels

- Querying data is straightforward
 
 - ... but may take some time with a large number of regions and/or indicators

- Regions can change their IDs at some point in time 😱

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# Creating a dashboard with flexdashboard & shiny

- `{flexdashboard}`: easier than `{shinydashboard}`

- `runtime: shiny_prerendered` for interactivity
 
 - and speed 🚀 (compared to `runtime: shiny`)

- `{reactable}`: default looks nicer than `{DT}`

- `{highcharter}`: default looks nicer than `{plotly}`

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# What we learned

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- A lot about "commuting" patterns in Germany
 
 - What about 2020?

- Python is cool, `pandas` is cool, `datenguidepy` is cool

- **Open, accessible data is important!** (Thanks [Datenguide](https://datengui.de/)!)

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👉 [**commute.correlaid.org**](https://commute.correlaid.org)

Source code: https://github.com/CorrelAid/correlaidx-challenge-bremen