GeoJSON Tutorial

examples

Files Size Format Created Updated License Source
1 8kB geojson
This is an example Data Package, that demonstrates how to package up GeoJSON data and display it on the map. We are using GeoJSON data for United Kingdom. Views We assume that you are familiar with what datapackage.json is and it's specifications. To display your GeoJSON data on the map you read more
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This is an example Data Package, that demonstrates how to package up GeoJSON data and display it on the map. We are using GeoJSON data for United Kingdom.

Views

We assume that you are familiar with what datapackage.json is and it's specifications.

To display your GeoJSON data on the map you should define path to your data inside resources and set format attribute to geojson. See example datapackage.json:

{
  "datahub": {
    "findability": "published",
    "hash": "2e981dcee3e58eba58b91d1d62e73814",
    "modified": "2017-08-08T17:38:15.627431",
    "owner": "examples",
    "ownerid": "examples",
    "stats": {
      "bytes": 8270,
      "rowcount": 0
    }
  },
  "id": "examples/geojson-tutorial",
  "name": "geojson-tutorial",
  "readme": "This is an example Data Package, that demonstrates how to package up GeoJSON data and display it on the map. We are using GeoJSON data for United Kingdom.\n\n### Views\n\nWe assume that you are familiar with what [datapackage.json][datapackage.json] is and it's specifications.\n\nTo display your GeoJSON data on the map you should define path to your data inside resources and set format attribute to `geojson`. See example datapackage.json:\n\n{{ datapackage.json }}\n\nNote: We are currently not supporting the TopoJSON format. You can use \"Vega Graph Spec\" and display you TopoJSON data using [Vega][vega] specification. See our [example Data Package][topo]\n\n[datapackage.json]: http://specs.frictionlessdata.io/data-package/#specification\n[topo]: /examples/vega-views-tutorial-topojson\n[vega]: https://vega.github.io/vega/\n",
  "resources": [
    {
      "bytes": 8270,
      "datahub": {
        "type": "non-tabular"
      },
      "format": "geojson",
      "mediatype": "application/json",
      "name": "example",
      "path": "extra/data/example.geojson",
      "url": "https://s3.amazonaws.com/rawstore.datahub.io/db696b3bf628d9a273ca9907adcea5c9"
    }
  ],
  "title": "GeoJSON Tutorial",
  "version": "0.1.0"
}

Note: We are currently not supporting the TopoJSON format. You can use "Vega Graph Spec" and display you TopoJSON data using Vega specification. See our example Data Package

Import into your tool

In order to use Data Package in R follow instructions below:

install.packages("devtools")
library(devtools)
install_github("hadley/readr")
install_github("ropenscilabs/jsonvalidate")
install_github("ropenscilabs/datapkg")

#Load client
library(datapkg)

#Get Data Package
datapackage <- datapkg_read("https://pkgstore.datahub.io/examples/geojson-tutorial/latest")

#Package info
print(datapackage)

#Open actual data in RStudio Viewer
View(datapackage$data$"example")

Tested with Python 3.5.2

To generate Pandas data frames based on JSON Table Schema descriptors we have to install jsontableschema-pandas plugin. To load resources from a data package as Pandas data frames use datapackage.push_datapackage function. Storage works as a container for Pandas data frames.

In order to work with Data Packages in Pandas you need to install our packages:

$ pip install datapackage
$ pip install jsontableschema-pandas

To get Data Package run following code:

import datapackage

data_url = "https://pkgstore.datahub.io/examples/geojson-tutorial/latest/datapackage.json"

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'pandas')

# to see datasets in this package
storage.buckets

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

In order to work with Data Packages in Python you need to install our packages:

$ pip install datapackage

To get Data Package into your Python environment, run following code:

import datapackage

dp = datapackage.DataPackage('https://pkgstore.datahub.io/examples/geojson-tutorial/latest/datapackage.json')

# see metadata
print(dp.descriptor)

# get list of csv files
csvList = [dp.resources[x].descriptor['name'] for x in range(0,len(dp.resources))]
print(csvList) # ["resource name", ...]

# access csv file by the index starting 0
print(dp.resources[0].data)

To use this Data Package in JavaScript, please, follow instructions below:

Install datapackage using npm:

$ npm install [email protected]

Once the package is installed, use code snippet below


const Datapackage = require('datapackage').Datapackage

async function fetchDataPackageAndData(dataPackageIdentifier) {
  const dp = await new Datapackage(dataPackageIdentifier)
  await Promise.all(dp.resources.map(async (resource) => {
    if (resource.descriptor.format === 'geojson') {
      const baseUrl = resource._basePath.replace('/datapackage.json', '')
      const resourceUrl = `${baseUrl}/${resource._descriptor.path}`
      const response = await fetch(resourceUrl)
      resource.descriptor._values = await response.json()
    } else {
      // we assume resource is tabular for now ...
      const table = await resource.table
      // rows are simple arrays -- we can convert to objects elsewhere as needed
      const rowsAsObjects = false
      resource.descriptor._values = await table.read(rowsAsObjects)
    }
  }))

  // see the data package object
  console.dir(dp)

  // data itself is stored in Resource object, e.g. to access first resource:
  console.log(dp.resources[0]._values)

  return dp
}


fetchDataPackageAndData('https://pkgstore.datahub.io/examples/geojson-tutorial/latest/datapackage.json');

Our JavaScript is written using ES6 features. We are using node.js v7.4.0 and passing --harmony option to enable ES6:

$ node --harmony index.js

In order to work with Data Packages in SQL you need to install our packages:

$ pip install datapackage
$ pip install jsontableschema-sql
$ pip install sqlalchemy

To import Data Package to your SQLite Database, run following code:

import datapackage
from sqlalchemy import create_engine

data_url = 'https://pkgstore.datahub.io/examples/geojson-tutorial/latest/datapackage.json'
engine = create_engine('sqlite:///:memory:')

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'sql', engine=engine)

# to see datasets in this package
storage.buckets

# to execute sql command (assuming data is in "data" folder, name of resource is data and file name is data.csv)
storage._Storage__connection.execute('select * from data__data___data limit 1;').fetchall()

# description of the table columns
storage.describe('data__data___data')