Work with geo-temporal data
Sample data
- Load annotated CSV sample data
- Write sample data to InfluxDB with line protocol

Work with geo-temporal data

Use the Flux Geo package to filter geo-temporal data and group by geographic location or track.

The Geo package is experimental and subject to change at any time. By using it, you agree to the risks of experimental functions.

To work with geo-temporal data:

Import the experimental/geo package.
```
import "experimental/geo"
```
Load geo-temporal data. See below for sample geo-temporal data.
Do one or more of the following:
- Shape data to work with the Geo package
- Filter data by region (using strict or non-strict filters)
- Group data by area or by track

Shape data to work with the Geo package

Functions in the Flux Geo package require lat and lon fields and an s2_cell_id tag. Rename latitude and longitude fields and generate S2 cell ID tokens.

import "experimental/geo"
sampleGeoData
  |> geo.shapeData(latField: "latitude", lonField: "longitude", level: 10)

Filter geo-temporal data by region

Use the geo.filterRows function to filter geo-temporal data by box-shaped, circular, or polygonal geographic regions.

import "experimental/geo"
sampleGeoData
  |> geo.filterRows(
    region: {lat: 30.04, lon: 31.23, radius: 200.0},
    strict: true
  )

Group geo-temporal data

Use the geo.groupByArea() to group geo-temporal data by area and geo.asTracks() to group data into tracks or routes.

import "experimental/geo"
sampleGeoData
  |> geo.groupByArea(newColumn: "geoArea", level: 5)
  |> geo.asTracks(groupBy: ["id"],sortBy: ["_time"])

Sample data

Many of the examples in this section use a sampleGeoData variable that represents a sample set of geo-temporal data. The Bird Migration Sample Data available on GitHub provides sample geo-temporal data that meets the requirements of the Flux Geo package.

Load annotated CSV sample data

Use the experimental csv.from() function to load the sample bird migration annotated CSV data from GitHub:

import `experimental/csv`
sampleGeoData = csv.from(
  url: "https://github.com/influxdata/influxdb2-sample-data/blob/master/bird-migration-data/bird-migration.csv"
)

csv.from(url: ...) downloads sample data each time you execute the query (~1.3 MB). If bandwidth is a concern, use the to() function to write the data to a bucket, and then query the bucket with from().

Write sample data to InfluxDB with line protocol

Use curl and the influx write command to write bird migration line protocol to InfluxDB. Replace example-bucket with your destination bucket:

curl https://raw.githubusercontent.com/influxdata/influxdb2-sample-data/master/bird-migration-data/bird-migration.line \
  --output ./tmp-data
influx write -b example-bucket @./tmp-data
rm -f ./tmp-data

Use Flux to query the bird migration data and assign it to the sampleGeoData variable:

sampleGeoData = from(bucket: "example-bucket")
  |> range(start: 2019-01-01T00:00:00Z, stop: 2019-12-31T23:59:59Z)
  |> filter(fn: (r) => r._measurement == "migration")