Optimisation, organisation, rentability

Tag: 4D component

[Follow-Up] map of more IPs

This is a follow-up to Where is this IP from? There I explained how to find where a IP came from. Now the question is, where did the IPs of today come from. The answer is a couple lines of code

  • select the IPs
  • define the object-structure als template
  • set the selection to json and assign to the MaPagenda-subform

Draw more than one IP onto a map

The map is just another kind of display for data:

locations of many IPs drawn on the map

This map shows to much information. I need to dissect, subselect, analyse and understand what I’m seeing here. The very first enhancements will lead to a map like this:

different marker-colors

4D World Tour 2017 Maps

Where does the 4D World Tour 2017 host events? I’d like to see that on a map and read the sequence of events at a glance.

We had to first extract the data from the 4D-Website. Then, because website-data is hardly properly organised for a database, put them into a Numbers-spreadsheet and did some enhancements. Enhancing means putting addresses into separate columns, name the columns according to keywords, add empty columns for latitude and longitude, add a second table for the teams and reference that data into the first table.

Exporting from Numbers does not support JSON, so we used CSV. Then run through MaPagenda to convert CSV into JSON. Finally the JSON opend in MaPagenda and created the maps. Those maps are included in this page by iframes.

MaPagenda learned new tricks while building these maps.

Click a map-picture to open the interactive map in a new window. Select a marker and read hotel, city, date and team.


Australia and New Zealand

Australien und Neuseeland

South America

Germany and Austria


Every marker is numbered and crossing pathes maybe an optimization of the tour

Europe besides DE, AT and FR


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