Data exploration using London Development Database [MapInfo/R]

Data exploration using London Development Database.

The LDD dataset is updated monthly and includes geospatial data (postcodes and geo-coordinate information) on all development projects in London completed since 2006. It also contains statistics about the number of residential units, non-residential units and parking spaces that these development projects planned to complete. Given the huge amount of information contained in the dataset, mapping softwares could be used to visualise these data.

Which boroughs are the most active in residential developments in the recent 5 years? [MapInfo]

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In order to answer this question, I summarise the dataset by each borough and obtain the aggregate residential development units for each of the past five years. Bar charts are used to show the differences in residential developments for each of the borough. Given that there are 33 boroughs, the 33 barcharts are difficult to visualise together. I used MapInfo to plot each of these 33 barcharts to the respective boroughs to visualise the difference across boroughs and time in one powerful picture.

It is not too surprising to see that city of london has in overall, the most number development projects completed. However, we can also see that boroughs like Croydon in the south and Barnet in the North are also generating a lot of residential housing.

How has each borough differed for the past few years in constructing residential, non-residential and parking spaces? [R/Shiny]

myapp.png

To add a few more variables for comparison, we can simply replot the MapInfo graph for the few more variables. This might be alright if we are looking at a few variables. However, if the list of variables gets too long, we might want to use a more dynamic form of visualisation to display the results. I then used R’s Shiny app to create a dynamic map to visualise this comparison across the boroughs for the past 11 years. The drop down menu can be used to select which variable and year you are interested in. This enables users to browse through the huge database in a very efficient manner.

WordPress has disabled the ability to enable iFrames so you can find the link for the app here: https://mapping4dev.shinyapps.io/myapp/ 

 

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