yanoak
commented
5 years ago Potential solution is that there is an official lookup table that matches LSOAs to Wards using a best fitting method that relies on population weighted centroids of OAs to see which Wards they fall under.
The GrantNav data is fairly well geotagged, at the district and ward level
At the district (LAD) level, these are the numbers of rows with valid data: non-blanks: 263,511 blanks: 38,225
At the ward level, these are the numbers of rows with valid data: non-blanks: 193,280 blanks: 108,456
This means
As for the deprivation index data, the level of disaggregation are at LADs and LSOAs. This means at the level of LADs, we can easily make 1-to-1 cross comparisons between deprivation and grant data.
However, wards and LSOAs don't usually map neatly into one another.
For example, the district of Hartlepool (E06000001) is divided into LSOAs as shown in this map, but is divided into wards as shown in this map. As you can see, they don't map onto each other at all.
However, there are some LADs for which wards and LSOAs do map neatly onto each other. Middlesburough (E06000002) is divided into LSOAs as shown in this map, but is divided into wards as shown in this map.
This presents a challenge in terms of presenting the detailed views in the visualisations. At the district level, we can have the map and the scatterplot correspond 1-to-1, but at a finer level of disaggregation, if we choose wards, then in some places, we won't be able to calculate the deprivation for that ward because the ward isn't neatly broken down into LSOAs.