Example sample transform on ISO 4217 Currency Codes

Files	Size	Format	Created	Updated	License	Source
2	96kB	csv zip	5 years ago	5 years ago		SIX Interbank Clearing Ltd (on behalf of ISO)

File	Description	Size	Last changed	Download
codes-all		17kB		csv (17kB) , json (63kB)
example-sample-transform-on-currency-codes_zip	Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json.	26kB		zip (26kB)

Field Name	Order	Type (Format)	Description
Entity	1	string	Country or region name
Currency	2	string	Name of the currency
AlphabeticCode	3	string	3 digit alphabetic code for the currency
NumericCode	4	number	3 digit numeric code
MinorUnit	5	string
WithdrawalDate	6	string	Date currency withdrawn (values can be ranges or months

Integrate this dataset into your favourite tool

Use our data-cli tool designed for data wranglers:

data get https://datahub.io/examples/example-sample-transform-on-currency-codes
data info examples/example-sample-transform-on-currency-codes
tree examples/example-sample-transform-on-currency-codes

# Get a list of dataset's resources
curl -L -s https://datahub.io/examples/example-sample-transform-on-currency-codes/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/examples/example-sample-transform-on-currency-codes/r/0.csv

curl -L https://datahub.io/examples/example-sample-transform-on-currency-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/examples/example-sample-transform-on-currency-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/examples/example-sample-transform-on-currency-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/examples/example-sample-transform-on-currency-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/examples/example-sample-transform-on-currency-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)
    }
  }
})()

Read me

This is an example dataset to demonstrate how data transforms works. In this example, we explain how to get a sample from a resource. We assume a publisher is already familiar with Data Packages and views specifications (views property in Data Package specifications).

Getting sample data

On the top of this page, you can find a table that displays filtered data. Raw data is displayed in preview section. As you can see we are getting sample of 15 rows from the initial data. This is described in the view object of views property:

{
  "name": "sample-view",
  "specType": "table",
  "resources": [
    {
      "name": "codes-all",
      "transform": [
        {
          "type": "sample",
          "size": 15
        }
      ]
    }
  ]
}

where:

"specType": "table" - this way we define the view as a table (other options are "simple" (renders a graph and accepts Plotly spec) and "vega" (renders a graph and accepts Vega spec)).
"resources" property is an array of objects in this case, where publishers can define data transforms they want to apply.
"name" - name of the resource as a reference.
"transform" - array of transforms. Each transform is an object, which properties vary depending on transform type. Only common property is "type" that is used to specify transform type.

Transform properties for “sample”:

"type": "sample" - this way we define the transform to be a sample.
"size" - any integer that will be used as a size of a sample data.

Descriptor for this data package

This is the full datapackage.json of this dataset:

{
  "name": "example-sample-transform-on-currency-codes",
  "title": "Example sample transform on ISO 4217 Currency Codes",
  "licenses": [
    {
      "id": "odc-pddl",
      "label": "Open Data Commons Public Domain Dedication and Licence (PDDL)",
      "url": "http://opendatacommons.org/licenses/pddl/"
    }
  ],
  "keywords": [ "iso", "iso-4217", "currency", "codes" ],
  "homepage": "http://www.iso.org/iso/currency_codes",
  "sources": [{
    "name": "SIX Interbank Clearing Ltd (on behalf of ISO)",
    "email": "[email protected]"
  }],
  "maintainer": [{
    "name": "Rufus Pollock",
    "email": "[email protected]"
  }],
  "contributors": [
    {
      "name": "Rufus Pollock",
      "email": "[email protected]"
    },
    {
      "name": "Kristofer D. Kusano",
      "email": "[email protected]"
    }
  ],
  "resources": [
    {
      "name": "codes-all",
      "path": "data/codes-all.csv",
      "mimetype": "text/csv",
      "size": "16863",
      "schema": {
        "fields": [
          {
            "name": "Entity",
            "type": "string",
            "description": "Country or region name"
          },
          {
            "name": "Currency",
            "type": "string",
            "description": "Name of the currency"
          },
          {
            "name": "AlphabeticCode",
            "title": "Alphabetic Code",
            "type": "string",
            "description": "3 digit alphabetic code for the currency"
          },
          {
            "name": "NumericCode",
            "title": "Numeric Code",
            "type": "integer",
            "description": "3 digit numeric code"
          },
          {
            "name": "MinorUnit",
            "title": "Minor Unit",
            "type": "number",
            "description": ""
          },
          {
            "name": "WithdrawalDate",
            "title": "Withdrawal Date",
            "type": "string",
            "description": "Date currency withdrawn (values can be ranges or months"
          }
        ]
      }
    }
  ],
  "views": [
    {
      "name": "sample-view",
      "specType": "table",
      "resources": [
        {
          "name": "codes-all",
          "transform": [
            {
              "type": "sample",
              "size": 15
            }
          ]
        }
      ]
    }
  ]
}

Example sample transform on ISO 4217 Currency Codes

Data Files

codes-all

Field information

Not found what you're looking for?

Integrate this dataset into your favourite tool

Read me

Getting sample data

Descriptor for this data package