Hawaii Public Electric Vehicle Charging Stations

JohnSnowLabs

Files Size Format Created Updated License Source
2 326kB csv zip 3 months ago John Snow Labs Standard License John Snow Labs Data City of Hawaii Home Lands
Download

Data Files

File Description Size Last changed Download
hawaii-public-electric-vehicle-charging-stations-csv 75kB csv (75kB) , json (156kB)
hawaii-public-electric-vehicle-charging-stations_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 70kB zip (70kB)

hawaii-public-electric-vehicle-charging-stations-csv  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
Station_ID 1 integer Identity of Vehicle Charging Station
Property_Business_Name 2 string Name of The Business Property
Street_Address 3 string Address of the Station
City 4 string Name 0f City
Zip_Code 5 integer Identify city and state for given code
Island 6 string Name of The Island
Charge_Fees 7 string Fees For Charging
Charger_Location 8 string Location of Charging Station
Hours_of_Operation 9 string Hours of Operation for Vehicle Charging
Number_of_Chargers 10 integer Total Number of Vehicle Charging Stations
Number_of_Ports 11 integer Total Number of Ports used for Charging
Charger_Level 12 integer Charging Station Level
Charger_Fee 13 string Fee for Charging Vehicle
Parking_Fee 14 string Vehicle Parking Fee
Manufacturers 15 string Station Manufacturers
Notes 16 string Notes For Vehicle Drivers
Latitude 17 number Latitude Location of Charging Station
Longitude 18 number Longitude Location of Charging Station

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Use data with the datahub.io almost like you use git with the github. Here are installation instructions.

data get https://datahub.io/JohnSnowLabs/hawaii-public-electric-vehicle-charging-stations
tree JohnSnowLabs/hawaii-public-electric-vehicle-charging-stations
# Get a list of dataset's resources
curl -L -s https://datahub.io/JohnSnowLabs/hawaii-public-electric-vehicle-charging-stations/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/JohnSnowLabs/hawaii-public-electric-vehicle-charging-stations/r/0.csv

curl -L https://datahub.io/JohnSnowLabs/hawaii-public-electric-vehicle-charging-stations/r/1.zip

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite", repos="https://cran.rstudio.com/")
library("jsonlite")

json_file <- 'https://datahub.io/JohnSnowLabs/hawaii-public-electric-vehicle-charging-stations/datapackage.json'
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# get list of all resources:
print(json_data$resources$name)

# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
  if(json_data$resources$datahub$type[i]=='derived/csv'){
    path_to_file = json_data$resources$path[i]
    data <- read.csv(url(path_to_file))
    print(data)
  }
}

Note: You might need to run the script with root permissions if you are running on Linux machine

Install the Frictionless Data data package library and the pandas itself:

pip install datapackage
pip install pandas

Now you can use the datapackage in the Pandas:

import datapackage
import pandas as pd

data_url = 'https://datahub.io/JohnSnowLabs/hawaii-public-electric-vehicle-charging-stations/datapackage.json'

# to load Data Package into storage
package = datapackage.Package(data_url)

# to load only tabular data
resources = package.resources
for resource in resources:
    if resource.tabular:
        data = pd.read_csv(resource.descriptor['path'])
        print (data)

For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):

pip install datapackage

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

from datapackage import Package

package = Package('https://datahub.io/JohnSnowLabs/hawaii-public-electric-vehicle-charging-stations/datapackage.json')

# print list of all resources:
print(package.resource_names)

# print processed tabular data (if exists any)
for resource in package.resources:
    if resource.descriptor['datahub']['type'] == 'derived/csv':
        print(resource.read())

If you are using JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use the following code snippet:

const {Dataset} = require('data.js')

const path = 'https://datahub.io/JohnSnowLabs/hawaii-public-electric-vehicle-charging-stations/datapackage.json'

// We're using self-invoking function here as we want to use async-await syntax:
;(async () => {
  const dataset = await Dataset.load(path)
  // get list of all resources:
  for (const id in dataset.resources) {
    console.log(dataset.resources[id]._descriptor.name)
  }
  // get all tabular data(if exists any)
  for (const id in dataset.resources) {
    if (dataset.resources[id]._descriptor.format === "csv") {
      const file = dataset.resources[id]
      // Get a raw stream
      const stream = await file.stream()
      // entire file as a buffer (be careful with large files!)
      const buffer = await file.buffer
      // print data
      stream.pipe(process.stdout)
    }
  }
})()
Datapackage.json