Other Exchange Listed Securities

JohnSnowLabs

Files Size Format Created Updated License Source
2 2MB csv zip 3 months ago John Snow Labs Standard License John Snow Labs Nasdaq Trader
Download

Data Files

File Description Size Last changed Download
other-exchange-listed-securities-csv 279kB csv (279kB) , json (744kB)
other-exchange-listed-securities_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 244kB zip (244kB)

other-exchange-listed-securities-csv  

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

Field information

Field Name Order Type (Format) Description
ACT_Symbol 1 string Identifier for each security used in ACT (Automated Confirmation Transaction Service) and CTCI (Computer-to-computer interface) connectivity protocol. Typical identifiers have 1-5 character root symbol and then 1-3 characters for suffixes, allowing up to 14 characters.
Security_Name 2 string The name of the security including additional information, if applicable. Examples are security type (common stock, preferred stock, etc.) or class (class A or B, etc.).
Stock_Exchange_Listing 3 string The listing stock exchange or market of a security.
CQS_Symbol 4 string Identifier of the security used to disseminate data via the SIAC Consolidated Quotation System (CQS) and Consolidated Tape System (CTS) data feeds. Typical identifiers have 1-5 character root symbol and then 1-3 characters for suffixes, allowing up to 14 characters.
Is_Exchange_Traded_Fund 5 string Identifies whether the security is an exchange traded fund (ETF). Values: true = Yes, security is an ETF. false= No, security is not an ETF. For new ETFs added to the file, the ETF field for the record will be updated to a value of "true".
Round_Lot_Size 6 integer Indicates the number of shares that make up a round lot for the given security
Is_Test_Issue 7 string Indicates whether the security is a test security. Values: true = Yes, it is a test issue. false = No, it is not a test issue.
NASDAQ_Symbol 8 string Identifier of the security used to in various NASDAQ connectivity protocols and NASDAQ market data feeds. Typical identifiers have 1-5 character root symbol and then 1-3 characters for suffixes

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/other-exchange-listed-securities
tree JohnSnowLabs/other-exchange-listed-securities
# Get a list of dataset's resources
curl -L -s https://datahub.io/JohnSnowLabs/other-exchange-listed-securities/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/JohnSnowLabs/other-exchange-listed-securities/r/0.csv

curl -L https://datahub.io/JohnSnowLabs/other-exchange-listed-securities/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/other-exchange-listed-securities/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/other-exchange-listed-securities/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/other-exchange-listed-securities/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/other-exchange-listed-securities/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