Electric Vehicle Charging Network

JohnSnowLabs

Files Size Format Created Updated License Source
2 298kB csv zip 3 months ago John Snow Labs Standard License John Snow Labs Data City of Austin
Download

Data Files

File Description Size Last changed Download
electric-vehicle-charging-network-csv 57kB csv (57kB) , json (181kB)
electric-vehicle-charging-network_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 33kB zip (33kB)

electric-vehicle-charging-network-csv  

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

Field information

Field Name Order Type (Format) Description
Station_Display_Name 1 string Identity of Vehicle Charging Network
Latitude 2 number Electric Vehicle Supply Equipment Latitude Location
Longitude 3 number Electric Vehicle Supply Equipment Longitude Location
Port_1_Voltage 4 string Vehicle Charging Port 1 in Voltage
Port_1_Current 5 string Vehicle Charging Port 1 in Current
Port_1_Connector_Type 6 string Connector Type Vehicle Charging Port 1
Port_2_Voltage 7 string Vehicle Charging Port 2 in Voltage
Port_2_Current 8 string Vehicle Charging Port 2 in Current
Port_2_Connector_Type 9 string Connector Type Vehicle Charging Port 2
Organization_Name 10 string Name of the Organization
Address_1 11 string Address 1 of Charging Network
Address_2 12 string Address 2 of Charging Network
Floor_Label 13 string Label of the Floor
City 14 string City of Charging Network
Postal_Code 15 integer Charging Network Postal Code
County 16 string Charging Network County
Number_of_Ports 17 integer Total Number of Ports Used for Charging
Reservation 18 string Reservation is Disabbled
Customer_Category 19 string Category of the Customer
Customer_Subcategory 20 string Subcategory of the Customer

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

# Get resources

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

curl -L https://datahub.io/JohnSnowLabs/electric-vehicle-charging-network/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/electric-vehicle-charging-network/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/electric-vehicle-charging-network/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/electric-vehicle-charging-network/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/electric-vehicle-charging-network/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