Nasdaq Listings

core

Files Size Format Created Updated License Source
3 304kB csv zip 6 months ago 2 months ago Public Domain Dedication and License NASDAQ official page
List of companies in the NASDAQ exchanges. Data Data and documentation are available on NASDAQ's official webpage. Data is updated regularly on the FTP site. The file used in this repository: NASDAQ Listed Securities Notes: Company Name is a parsed field using the Security Name field. Test read more
Download

Data Files

File Description Size Last changed Download
nasdaq-listed 253kB csv (253kB) , json (633kB)
nasdaq-listed-symbols 91kB csv (91kB) , json (181kB)
nasdaq-listings_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 258kB zip (258kB)

nasdaq-listed  

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

Field information

Field Name Order Type (Format) Description
Symbol 1 string
Company Name 2 string
Security Name 3 string
Market Category 4 string
Test Issue 5 string
Financial Status 6 string
Round Lot Size 7 number

nasdaq-listed-symbols  

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

Field information

Field Name Order Type (Format) Description
Symbol 1 string
Company Name 2 string

Read me

List of companies in the NASDAQ exchanges.

Data

Data and documentation are available on NASDAQ’s official webpage. Data is updated regularly on the FTP site.

The file used in this repository:

Notes:

  • Company Name is a parsed field using the Security Name field.
  • Test Listings are excluded in the final dataset

Preparation

You need python plus pandas library tool installed to run the scripts. You also probably need to be on Linux/Unix or Mac for the shell scripts to work.

all datasets

Creates all csv files and datapackage.json

Run python script:

  python scripts/process.py

License

This Data Package is licensed by its maintainers under the Public Domain Dedication and License (PDDL).

Refer to the Copyright notice of the source dataset for any specific restrictions on using these data in a public or commercial product. Copyright © 2010, The NASDAQ OMX Group, Inc. All rights reserved.

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

# Get resources

curl -L https://datahub.io/core/nasdaq-listings/r/0.csv

curl -L https://datahub.io/core/nasdaq-listings/r/1.csv

curl -L https://datahub.io/core/nasdaq-listings/r/2.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/nasdaq-listings/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/nasdaq-listings/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/nasdaq-listings/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/nasdaq-listings/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