updating documentation

docs/discussion/results.md

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+# Results
+
+The resulting output `.json` looks like (for the previous example using No. 1 `B90 3LA`):
+
+```json
+[
+  {
+    "property_id": "fe205bfe66bc7f18c50c8f3d77ec3e30",
+    "readable_address": "1 VERSTONE ROAD\nSHIRLEY\nSOLIHULL\nWEST MIDLANDS\nB90 3LA",
+    "flat_appartment": "",
+    "builing": "",
+    "number": "1",
+    "street": "VERSTONE ROAD",
+    "locality": "SHIRLEY",
+    "town": "SOLIHULL",
+    "district": "SOLIHULL",
+    "county": "WEST MIDLANDS",
+    "postcode": "B90 3LA",
+    "property_transactions": [
+      {
+        "price": 317500,
+        "transaction_date": "2020-11-13",
+        "year": 2020
+      }
+    ],
+    "latest_transaction_year": 2020
+  }
+]
+```
+
+The standard property information is included, we will briefly discuss the additional fields included in this output file.
+
+## readable_address
+
+The components that make up the address in the dataset are often repetitive, with the locality, town/city, district and county often sharing the same result. This can result in hard to read addresses if we just stacked all the components sequentially.
+
+The `readable_address` provides an easy to read address that strips this repetiveness out, by doing pairwise comparisons to each of the four components and applying a mask. The result is an address that could be served to the end user, or easily displayed on a page.
+
+This saves any user having to apply the same logic to simply display the address somewhere, the full address of a property should be easy to read and easily accessible.
+
+## property_transactions
+
+This array contains an object for each transaction for that property that has the price and year as an `int`, with the date having the `00:00` time stripped out.
+
+## latest_transaction_year
+
+The date of the latest transaction is extracted from the array of `property_transactions` and placed in the top level of the `json` object. This allows any end user to easily search for properties that haven't been sold in a period of time, without having to write this logic themselves.
+
+A consumer should be able to use this data to answer questions like:
+
+- Give me all properties in the town of Solihull that haven't been sold in the past 10 years.