IMO IMDG Classification Codes

core

Files Size Format Created Updated License Source
2 32kB csv zip 6 months ago 2 months ago ODC-PDDL-1.0 IMO Gov.uk
Official IMDG Codes for use in transport of dangerous goods as described by the IMO Data Source of the information is from the IMO and Gov.uk: http://www.imo.org/blast/mainframe.asp?topic_id=158 https://www.gov.uk/guidance/moving-dangerous-goods#the-classification-of-dangerous-goods Requests for read more
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Data Files

File Description Size Last changed Download
data 1kB csv (1kB) , json (3kB)
imo-imdg-codes_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 4kB zip (4kB)

data  

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

Field information

Field Name Order Type (Format) Description
un class 1 number A Single digit to describe the class of goods
dangerous goods 2 string Group of Hazard
division 3 number A defined set of divisions of the main class
classification 4 string Descriptive explanation of the division or classification

Read me

Official IMDG Codes for use in transport of dangerous goods as described by the IMO

Data

Source of the information is from the IMO and Gov.uk: http://www.imo.org/blast/mainframe.asp?topic_id=158 https://www.gov.uk/guidance/moving-dangerous-goods#the-classification-of-dangerous-goods

Requests for addition to the codes should be made to the IMO directly

License

This data is made available under the Public Domain Dedication and License version v1.0 whose full text can be found at http://opendatacommons.org/licenses/pddl/ - See more at: http://opendatacommons.org/guide/#sthash.97PSVxmh.dpuf

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Download CLI tool and use it with the datahub almost like you use git with the github:

data get https://datahub.io/core/imo-imdg-codes
data info core/imo-imdg-codes
tree core/imo-imdg-codes
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/imo-imdg-codes/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/core/imo-imdg-codes/r/0.csv

curl -L https://datahub.io/core/imo-imdg-codes/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/core/imo-imdg-codes/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/core/imo-imdg-codes/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/core/imo-imdg-codes/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/core/imo-imdg-codes/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