The passenger data in the tableau dashboard has been updated with the latest data from Eurostat (avia_par_xx).
and for cargo too - see the cargo dashboard.
What can you do with public data and publicly available statistics tools? My current project is about analysing road traffic data made available by BANES & BathHacked. Earlier posts look at cycling, aviation and household energy. See the Tableau dashboards:
Links to my Tableau public dashboards:
Saturday, 14 March 2015
Sunday, 8 February 2015
Plotting GPS routes
I wanted to try something different in Tableau - its ability to plot geographical routes.
So I've loaded up some routes from a bike GPS, using R to manipulate multiple files and add speed calculations - though I'm sure the haversine formula could also easily have been implemented in tableau to get the distances.
It took me a while to realise the return journey from home is longer by several minutes. Check out the speed and you can guess where the incline is with me, or against.
So I've loaded up some routes from a bike GPS, using R to manipulate multiple files and add speed calculations - though I'm sure the haversine formula could also easily have been implemented in tableau to get the distances.
It took me a while to realise the return journey from home is longer by several minutes. Check out the speed and you can guess where the incline is with me, or against.
Sunday, 18 January 2015
European Cargo airports (2003-2013)
Finally, I have extended the data that's available in the cargo dashboard to cover 2003-2013, where underlying monthly data are available from Eurostat.
Check it out!
Seems to be some missing data for Sweden 2005-2007 - the data availability tab gives a clear account of which years are available for which States.
Check it out!
Seems to be some missing data for Sweden 2005-2007 - the data availability tab gives a clear account of which years are available for which States.
Sunday, 7 December 2014
European Cargo airports - new dashboard. (2010-2012)
Turned out to be quite easy to adapt the passenger dashboard to do the same for the freight & mail data from Eurostat (avia_gor_xx). So see the link to the new dashboard above.
Flights: are commercial freight & mail flight departures (FRM_CAF_DEP in Eurostat terms)
Tonnes: are tonnes of freight & mail on board on departure (including direct transit cargo that stayed on the aircraft - FRM_BRD_DEP)
Flights: are commercial freight & mail flight departures (FRM_CAF_DEP in Eurostat terms)
Tonnes: are tonnes of freight & mail on board on departure (including direct transit cargo that stayed on the aircraft - FRM_BRD_DEP)
Friday, 5 December 2014
European airport departures - 2013 & 2014 data updated.
A delay in new posts, while I work on extracting a new dataset and turning it into some useful dashboards. Watch this space.
But meanwhile, the good news is that Eurostat have published updated data for 2013 and 2014, sorting out some earlier problems and adding more months. Check out the data in the 'production version' - link is at the top of the page: I've renamed the two dashboards into something more meaningful (I hope):
But meanwhile, the good news is that Eurostat have published updated data for 2013 and 2014, sorting out some earlier problems and adding more months. Check out the data in the 'production version' - link is at the top of the page: I've renamed the two dashboards into something more meaningful (I hope):
- Departure Patterns shows departures from the selected EU28 airport in terms of destinations, load factors, distances, aircraft sizes, pax, flights.
- Departure Points lets you select any airport (including those outside Europe) and see details of where flights leave EU28 airports to reach that point.
I've also re-size so it fits on the ipad better - but discovered Tableau menus work better in Safari than Chrome on the ipad.
Sunday, 16 November 2014
Tableau - More on Top N
In my posts of 3 & 5 Nov, I was looking at how to plot monthly graphs for just the top N airports out of many. Originally I achieved this through a complicated method (3/11) creating a combined dimension, but it's rather easier than that.
This is for graphs of main departure airports to a single destination.
- As before, create a graph by putting month in the column shelf, and one or more measures in the row shelf (eg passengers and flights).
- Filter by year (I only want to show a single year's seasonal cycle) and destination airport.
- Create a calculated field which is just Index() - I named it Rank (which is more or less what it is). Check that it's discrete.
- Filter on Rank, and from the drop-down select 'edit table calculation'.
- Choose sort by departing pax descending (so rank 1 is the biggest) - or whatever you want to rank by.
- In partitioning, select airport of departure.
- When you click OK you get the description something like: Results are computed along ADEP (sorted descending by Sum of Departing Pax) for each Month of Month. In your case, in place of ADEP (=airport of departure) you will see the dimension for each value of which you want a line on your graph.
- From the drop-down on rank in the filter pane, select filter and select the top N boxes, however many you want.
So, it still has quite a few steps, but it avoids calculating combo dimensions.
You can see the results in the 'seasonality at main departure airports' graph in the DepFromAP dashboard. I decided not to make N user selectable, just adds complication for the user.
Tuesday, 11 November 2014
From EU to you: new flight dashboard
I've added a second dashboard 'DepFromAP' that looks at the Eurostat data.
For destination airports (intended to be outside the EU, but I think you can still select inside) you can see which are the main EU28 departure points, the nature of the traffic (passengers, flights, load factors, aircraft size) and how these rankings have changed with time.
For example, you can see how in 2014 YTD, both Gatwick and Manchester have overtaken Frankfurt ranked in terms of passenger departures to Dubai.
The new dashboard is in the development and full versions (still with a caveat on 2013 & 2014 data). See links at the top of the page.
I did work out that there's an easier way to pick the top N for the seasonality graph - but I'll explain that in a later post.
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