Geocoding is the process of matching an address to its corresponding geographic coordinates. There's nothing inherent in the words "10 Downing Street, London, United Kingdom" that inherently conveys its location at the coordinates 51.503396, -0.12764. Instead this process [...].
Geocoding is the process of matching an address to its corresponding geographic coordinates. There's nothing inherent in the words "10 Downing Street, London, United Kingdom" that conveys its location at the coordinates `[ 51.503396, -0.12764 ]`. Instead this process [...].
Now that you've seen some examples of search, let's examine the results closer.
When requesting search results you will always get back `GeoJSON` results, unless something goes terribly wrong, in which case you'll get a really helpful error.
_You can go [here](link.to.geojson.spec.com) to learn more about the `GeoJSON` data format specification.
We'll assume you're familiar with the general layout and only point out some important details here._
You will find the following top-level structure to every response:
```
{
"geocoding":{...},
"type":"FeatureCollection",
"features":[...],
"bbox":[...]
}
```
For the purposes of getting started quickly, let's keep our focus on the **features** property of the result.
This is where you will find the list of results that best matched your input parameters.
Each item in this list will contain all the information needed to identify it in human-readable format in the `properties` block,
as well as computer friendly coordinates in the `geometry` property. Note the `label` property, which is a human-friendly
representation of the place, ready to be displayed to an end-user.
```
{
"type":"Feature",
"properties":{
"gid":"...",
"layer":"address",
"source":"osm",
"name":"30 West 26th Street",
"housenumber":"30",
"street":"West 26th Street",
"postalcode":"10010",
"country_a":"USA",
"country":"United States",
"region":"New York",
"region_a":"NY",
"county":"New York County",
"localadmin":"Manhattan",
"locality":"New York",
"neighbourhood":"Flatiron District",
"confidence":0.9624939994613662,
"label":"30 West 26th Street, Manhattan, NY"
},
"geometry":{
"type":"Point",
"coordinates":[
-73.990342,
40.744243
]
}
}
```
There is so much more to tell you about the plethora of data being returned for each search,
we had to split it out into its own document.
[Read more about the response format.](https://github.com/dianashk/pelias-doc/edit/master/getting-started/response.md)
#### Result count
You may have noticed that there were **10** places in the results for our **Stinky Beach** search.
That's the _default_ number of results the API will return, unless otherwise specified.
- The FeatureCollection is an ordered array, ranked in order of likleyhood
- Use directly in your application or test at GeoJSON.io
- Show + explain a response block
## Sizing Your Results
- Example: size=1 for batch geocoding
- Example: size=40 to store lots of results
## Looking in a Particular Place (Using Boundaries)
## Looking in a Particular Place (Using Boundaries)
[Means to limit the scope of where you're looking, and to look only within a particular area. This can be useful if you're looking for places in a particular region, or country, or only want to look in the immediate viscinity of a user with a known location.]
[Means to limit the scope of where you're looking, and to look only within a particular area. This can be useful if you're looking for places in a particular region, or country, or only want to look in the immediate viscinity of a user with a known location.]