More example for the tool introduced in the previous blog.
In this blog we will introduce one more tool
There are a lot of calculation can be done through this tool, so in this blog we will demonstrate one use for the calculation.
First we will setup the initial steps as in the previous blog, where we will create a TradeArea of radius 1km around each school, then we will Spatial Match the road within each school catchment area.
Since we didn't filter to a specific postcode in this example, we will over 6000 row of matching results, let's attempt this problem without view on the map since it will be too dense to view.
Once we have the output, we can attach a Spatial Info tool
The tool is very easy to config, once a spatial object is selected, we can use the tool find all kinds of information about that spatial object, in this particular example, we will use it to find the length (in km) of the roads that is matched with school trade area circle.
Among the results, we see the length for each line segment has been calculated. Armed with this information, we can ask the following question:
Which schools has the most amount of road (by length) in London?
We can use other tools to calculated the results.
First we can find the total length covered by each school area, to do it we can use a Summarize tool.
We can see the school that has more road near it has more than 10km in length, that is a lot. From this results, we will just select the top 3 for visualization.
Once we have found the three schools with more road (in length) nearby, we could use them as a filter on the original data set, we would either manually type into a Filter tool (not robust) or use a Join tool (more robust).
We use the top 3 school as a filter in the inner join (J anchor).
Now we have filter the roads are around the 3 schools, we can visualize them better on the map with a Browse tool.
We can see from the view above, the schools with most amount of roads (in length) are in central London, where there is the highest density of roads, hence the total length within the area is high even if they do not have a single long road within.
The same principle can to applied when counting population within the target area rather than the length of roads, or any other numerical measure.
Note: We used setting in TradeArea to avoid overlap to prevent double counting.
Now we have covered quite a few tools within Spatial tools in Alteryx, feel free to try out more problems in the Alteryx Weekly Challenge or use it in the actual work to get a better result.
Looking for more guides, tips and tricks in Tableau or Alteryx? Go check out the other blog posts from the Data School.