Nasdaq Listings

core

Files Size Format Created Updated License Source
3 3MB csv zip 1 week ago 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
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Data Files

File Description Size Last changed Download Other formats
nasdaq-listed [csv] 253kB nasdaq-listed [csv] nasdaq-listed [json] (633kB)
nasdaq-listed-symbols [csv] 91kB nasdaq-listed-symbols [csv] nasdaq-listed-symbols [json] (181kB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 320kB datapackage_zip [zip]

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

datapackage_zip  

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

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

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite")
library("jsonlite")

json_file <- "http://datahub.io/core/nasdaq-listings/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources[[1]]$path
data <- read.csv(url(path_to_file))
print(data)

In order to work with Data Packages in Pandas you need to install the Frictionless Data data package library and the pandas extension:

pip install datapackage
pip install jsontableschema-pandas

To get the data run following code:

import datapackage

data_url = "http://datahub.io/core/nasdaq-listings/datapackage.json"

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'pandas')

# data frames available (corresponding to data files in original dataset)
storage.buckets

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

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('http://datahub.io/core/nasdaq-listings/datapackage.json')

# get list of resources:
resources = package.descriptor['resources']
resourceList = [resources[x]['name'] for x in range(0, len(resources))]
print(resourceList)

data = package.resources[0].read()
print(data)

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 = 'http://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 the first data file in this dataset
  const file = dataset.resources[0]
  // Get a raw stream
  const stream = await file.stream()
  // entire file as a buffer (be careful with large files!)
  const buffer = await file.buffer
})()

Install the datapackage library created specially for Ruby language using gem:

gem install datapackage

Now get the dataset and read the data:

require 'datapackage'

path = 'http://datahub.io/core/nasdaq-listings/datapackage.json'

package = DataPackage::Package.new(path)
# So package variable contains metadata. You can see it:
puts package

# Read data itself:
resource = package.resources[0]
data = resource.read
puts data
Datapackage.json