geocode | Geocode plugin for CakePHP | Web Framework library

Here's the solution that comes to mind for me. Create a new table that combines information from all 3 of the tables provided. It will be formatted like your Table 1 or Table 2, but with two new columns, Type and Slicer Store.

Type will specify whether the row is your own store or a competitor. Slicer Store will specify which rows should be displayed when that store's name is selected in the dropdown slicer.

Each row from your Table 3 will have 4 rows in the new table, one for each of the columns. The Slicer Store column in your new table will contain the Store Number from each row in Table 3. The Type column in your new table is self-explanatory.

You will end up with something like the following.

Number Name Address Latitude Longitude Type Slicer Store JL123 ... ... ... ... Store JL123 C1 ... ... ... ... Competitor JL123 C2 ... ... ... ... Competitor JL123 C3 ... ... ... ... Competitor JL123 JL456 ... ... ... ... Store JL456 C2 ... ... ... ... Competitor JL456 C3 ... ... ... ... Competitor JL456 C4 ... ... ... ... Competitor JL456

Now for how to use it in Power BI. Create a single-select dropdown slicer using your new Slicer Store column. Then create your map visual using the rows in your new table. Use your new Type column as the Legend/Category. This allows you to color stores vs competitors differently in the visual.

Bing bang boom, you're done. Note that you may have "duplicate" rows for competitors in your new table. For example, if JL123 and JL456 were physically located right next to each other, then rows for C1, C2, and C3 would each appear twice in your new table. The Slicer Store would be different (JL123 or JL456) for these rows, though.

How you create the new table, either manually or with some sort of script, is the hard part.

Precision of 6 decimal places gives you ~10 centimeter accuracy. Mapbox is using GeoJSON specification which has following recommendation about precision:

The size of a GeoJSON text in bytes is a major interoperability consideration, and precision of coordinate values has a large impact on the size of texts. A GeoJSON text containing many detailed Polygons can be inflated almost by a factor of two by increasing coordinate precision from 6 to 15 decimal places. For geographic coordinates with units of degrees, 6 decimal places (a default common in, e.g., sprintf) amounts to about 10 centimeters, a precision well within that of current GPS systems. Implementations should consider the cost of using a greater precision than necessary.

GPS-enabled smartphones are typically accurate to within a 4.9 m (16 ft.) radius under open sky. However, their accuracy worsens near buildings, bridges, and trees.ref

Here is a demo of distance accuracy when precision of 6 decimal places is used:

You are issuing multiple calls to the API and thus creating multiple promises. What you are seeing in the console is an array of those promise objects. You need to write code like below to wait for all of them to complete.

You're not having trouble with the lat or lon, what you're doing is passing in unnamed parameters to reverse_geo() that are not in the correct position. You should only pass in parameters positionally if you are certain they will be in the correct position.

You have:

Because async functions return a promise, calling one will give you back the promise, not the result.

Here you are calling getAddress directly:

As discussed in the comments you should update your webpack configuration to handle loading svg files. inside the module.rules array you should add the following:

You should not mix the type Number with number.

Type Number is not assignable to type number. number is a primitive, but Number is a wrapper object. Prefer using number when possible.

{geometry: {location: {lat: number; lng: number}}} (N -> n)

I have tested it. It works. You should always use the primitive types (lowercase). No cast necessary anymore. You could also just use as number behind your assignment if you want. But I recommend to change your type from Number to number.

Solution A (recommended):

The problem is here, when handling the Change message from onInput:

Disclaimer

Never really worked with sf and friends before, but after reading the docs I could imagine a solution like this to fulfill your needs.

Idea

Since sf are in fact extended data.frames they naturally come with an rbind functionality. Having said that, the whole task should be as easy as rbind'ing all the relevant paths together. As for the waiting time, simply repeat the last row in the sf a couple of times, which would give you the impression of the vehicle stopping at B (and A on the way back).

Code