# Bikeshare stations within a San Francisco buffer

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In this example we are going to showcase how easily we can compute buffers around geometries using the Analytics Toolbox.

## Creating a buffer of a neighborhood <a href="#creating-a-buffer-of-a-neighborhood" id="creating-a-buffer-of-a-neighborhood"></a>

The following query creates a buffer with a radius of 50 meters around San Francisco’s Financial District neighborhood using the `ST_BUFFER` function. The number of steps could be modified in order to make the lines smoother if needed.

{% tabs %}
{% tab title="carto-un" %}

```sql
SELECT `carto-un`.carto.ST_BUFFER(neighborhood_geom, 50, 'meters', 5) AS geo FROM `bigquery-public-data`.san_francisco_neighborhoods.boundaries WHERE neighborhood = "Financial District";
```

{% endtab %}

{% tab title="carto-un-eu" %}

```sql
SELECT `carto-un-eu`.carto.ST_BUFFER(neighborhood_geom, 50, 'meters', 5) AS geo FROM `bigquery-public-data`.san_francisco_neighborhoods.boundaries WHERE neighborhood = "Financial District";
```

{% endtab %}

{% tab title="manual" %}

```sql
SELECT carto.ST_BUFFER(neighborhood_geom, 50, 'meters', 5) AS geo FROM `bigquery-public-data`.san_francisco_neighborhoods.boundaries WHERE neighborhood = "Financial District";
```

{% endtab %}
{% endtabs %}

In this visualization you can see the Financial Disctrict (darker blue) and its buffer around it. Notice that buffers radius are not necesarily positive numbers. Negative numbers would generate a buffer in the interior of the district’s geomery.

## Bikeshare stations within a buffer <a href="#bikeshare-stations-within-a-buffer" id="bikeshare-stations-within-a-buffer"></a>

Now let’s use the buffer as a way of defining a bigger region around the Financial District of San Francisco and filtering some other geometries.

{% tabs %}
{% tab title="carto-un" %}

```sql
SELECT ST_GEOGPOINT(d2.longitude,d2.latitude) AS geo FROM `bigquery-public-data`.san_francisco_neighborhoods.boundaries d1,
`bigquery-public-data`.san_francisco.bikeshare_stations d2
WHERE d1.neighborhood = "Financial District" AND ST_CONTAINS(`carto-un`.carto.ST_BUFFER(d1.neighborhood_geom, 50, 'meters', 5), ST_GEOGPOINT(d2.longitude, d2.latitude));
```

{% endtab %}

{% tab title="carto-un-eu" %}

```sql
SELECT ST_GEOGPOINT(d2.longitude,d2.latitude) AS geo FROM `bigquery-public-data`.san_francisco_neighborhoods.boundaries d1,
`bigquery-public-data`.san_francisco.bikeshare_stations d2
WHERE d1.neighborhood = "Financial District" AND ST_CONTAINS(`carto-un-eu`.carto.ST_BUFFER(d1.neighborhood_geom, 50, 'meters', 5), ST_GEOGPOINT(d2.longitude, d2.latitude));
```

{% endtab %}

{% tab title="manual" %}

```sql
SELECT ST_GEOGPOINT(d2.longitude,d2.latitude) AS geo FROM `bigquery-public-data`.san_francisco_neighborhoods.boundaries d1,
`bigquery-public-data`.san_francisco.bikeshare_stations d2
WHERE d1.neighborhood = "Financial District" AND ST_CONTAINS(carto.ST_BUFFER(d1.neighborhood_geom, 50, 'meters', 5), ST_GEOGPOINT(d2.longitude, d2.latitude));
```

{% endtab %}
{% endtabs %}

This query uses the `ST_BUFFER` and `ST_CONTAINS` functions in order to filter those bikeshare stations that are contained inside the buffered geometry. The result is displayed below, where bikeshare stations are represented as yellow dots.

<img src="https://content.gitbook.com/content/FEElAdsRIl9DzfMhbRlB/blobs/GWtJUWkKFcCzxcPMkgpe/eu-flag-website.png" alt="EU flag" data-size="line"> This project has received funding from the [European Union’s Horizon 2020](https://ec.europa.eu/programmes/horizon2020/en) research and innovation programme under grant agreement No 960401.