​getFieldsFromData​
​processCsvData​
​processGeojson​
​processKeplerglJSON​
​processRowObject​
Analyze field types from data in string
format, e.g. uploaded csv. Assign type
, tableFieldIndex
and format
(timestamp only) to each field
Parameters
fieldOrder
Array array of field names as string
Examples
import {getFieldsFromData} from 'kepler.gl/processors';const data = [{time: '2016-09-17 00:09:55',value: '4',surge: '1.2',isTrip: 'true',zeroOnes: '0'}, {time: '2016-09-17 00:30:08',value: '3',surge: null,isTrip: 'false',zeroOnes: '1'}, {time: null,value: '2',surge: '1.3',isTrip: null,zeroOnes: '1'}];​const fieldOrder = ['time', 'value', 'surge', 'isTrip', 'zeroOnes'];const fields = getFieldsFromData(data, fieldOrder);// fields = [// {name: 'time', format: 'YYYY-M-D H:m:s', tableFieldIndex: 1, type: 'timestamp'},// {name: 'value', format: '', tableFieldIndex: 4, type: 'integer'},// {name: 'surge', format: '', tableFieldIndex: 5, type: 'real'},// {name: 'isTrip', format: '', tableFieldIndex: 6, type: 'boolean'},// {name: 'zeroOnes', format: '', tableFieldIndex: 7, type: 'integer'}];
Returns Array<Object> formatted fields
Process csv data, output a data object with {fields: [], rows: []}
. The data object can be wrapped in a dataset
and pass to addDataToMap
​
Parameters
rawData
string raw csv string
Examples
import {processCsvData} from 'kepler.gl/processors';​const testData = `gps_data.utc_timestamp,gps_data.lat,gps_data.lng,gps_data.types,epoch,has_result,id,time,begintrip_ts_utc,begintrip_ts_local,date2016-09-17 00:09:55,29.9900937,31.2590542,driver_analytics,1472688000000,False,1,2016-09-23T00:00:00.000Z,2016-10-01 09:41:39+00:00,2016-10-01 09:41:39+00:00,2016-09-232016-09-17 00:10:56,29.9927699,31.2461142,driver_analytics,1472688000000,False,2,2016-09-23T00:00:00.000Z,2016-10-01 09:46:37+00:00,2016-10-01 16:46:37+00:00,2016-09-232016-09-17 00:11:56,29.9907261,31.2312742,driver_analytics,1472688000000,False,3,2016-09-23T00:00:00.000Z,,,2016-09-232016-09-17 00:12:58,29.9870074,31.2175827,driver_analytics,1472688000000,False,4,2016-09-23T00:00:00.000Z,,,2016-09-23`​const dataset = {info: {id: 'test_data', label: 'My Csv'},data: processCsvData(testData)};​dispatch(addDataToMap({datasets: [dataset],options: {centerMap: true, readOnly: true}}));
Returns Object data object {fields: [], rows: []}
Process GeoJSON FeatureCollection
, output a data object with {fields: [], rows: []}
. The data object can be wrapped in a dataset
and pass to addDataToMap
​
Parameters
rawData
Object raw geojson feature collection
Examples
import {addDataToMap} from 'kepler.gl/actions';import {processGeojson} from 'kepler.gl/processors';​const geojson = {"type" : "FeatureCollection","features" : [{"type" : "Feature","properties" : {"capacity" : "10","type" : "U-Rack"},"geometry" : {"type" : "Point","coordinates" : [ -71.073283, 42.417500 ]}}]};​dispatch(addDataToMap({datasets: {info: {label: 'Sample Taxi Trips in New York City',id: 'test_trip_data'},data: processGeojson(geojson)}}));
Returns Object dataset containing fields
and rows
Process saved kepler.gl json to be pass to addDataToMap
. The json object should contain datasets
and config
.
Parameters
Examples
import {addDataToMap} from 'kepler.gl/actions';import {processKeplerglJSON} from 'kepler.gl/processors';​dispatch(addDataToMap(processKeplerglJSON(keplerGlJson)));
Returns Object datasets and config {datasets: {}, config: {}}
Process data where each row is an object, output can be passed to addDataToMap
​
Parameters
Examples
import {addDataToMap} from 'kepler.gl/actions';import {processRowObject} from 'kepler.gl/processors';​const data = [{lat: 31.27, lng: 127.56, value: 3},{lat: 31.22, lng: 126.26, value: 1}];​dispatch(addDataToMap({datasets: {info: {label: 'My Data', id: 'my_data'},data: processRowObject(data)}}));
Returns Object dataset containing fields
and rows