@datafire/quandl

Client library for Quandl API

Installation and Usage

npm install --save @datafire/quandl

let quandl = require('@datafire/quandl').create({
  apiKey: ""
});

.then(data => {
  console.log(data);
});

Description

The Quandl API

Actions

datasets.database_code.dataset_code.metadata.get

To download the metadata associated with any dataset object, append /metadata to your API request. (You can replace .csv with .json or .xml in this request). The following metadata fields are available in the response:

quandl.datasets.database_code.dataset_code.metadata.get({
  "column_names": "",
  "database_code": "",
  "dataset_code": "",
  "description": "",
  "frequency": "",
  "name": "",
  "newest_available_date": "",
  "oldest_available_date": "",
  "premium": "",
  "refreshed_at": "",
  "type": ""
}, context)

Input

• input object
  • column_names required string
  • database_code required string: The unique database code on Quandl (ex. WIKI)
  • dataset_code required string: The unique dataset code on Quandl (ex. APPL)
  • description required string
  • frequency required string
  • name required string
  • newest_available_date required string
  • oldest_available_date required string
  • premium required string
  • refreshed_at required string
  • type required string

Output

• output object
  • dataset required object
    • database_id required number
    • premium required boolean
    • type required string
    • frequency required string
    • column_names required array
      • items object
    • oldest_available_date required string
    • newest_available_date required string
    • refreshed_at required string
    • description required string
    • name required string
    • database_code required string
    • dataset_code required string
    • id required number

datasets.database_code.dataset_code.data.get

To download the data in a dataset, simply append /data to the Quandl code in your API request. (You can replace .csv with .json or .xml in this request). If you request CSV, only the data you requested will be returned. If you request JSON or XML, both data and input parameters will be returned. You can customize the dataset object being returned by adding various optional parameters to your query. Available parameters are tabulated below: If a datapoint for time t is denoted as y[t] and the transformed data as y’[t], the available transformations are defined as below: y[0] in the above table refers to the starting date for the API call, i.e., the date specified by start_date= or rows=, NOT the starting date of the underlying dataset.

quandl.datasets.database_code.dataset_code.data.get({
  "Cumulative": "",
  "Row-on-row": "",
  "Start": "",
  "database_code": "",
  "dataset_code": ""
}, context)

Input

• input object
  • Cumulative required string: y’[t] = y[t] +y[t-1] + … + y[0]
  • Row-on-row required string: y’[t] = y[t] - y[t-1]
  • Start required string: y’[t] = (y[t]/y[0]) * 100
  • collapse string: Parameters to indicate the desired frequency. When you change the frequency of a dataset, Quandl returns the last observation for the given period. By collapsing a daily dataset to monthly, you will get a sample of the original dataset where the observation for each month is the last data point available for that month. Set collapse with: collapse=none|daily|weekly|monthly|quarterly|annual
  • column_index string: Request a specific column by passing the column_index=n parameter. Column 0 is the date column and is always returned. Data begins at column 1.
  • database_code required string: Each database on Quandl has a unique database code. For example, the database code for “Wiki EOD Stock Prices” has the Quandl code WIKI.
  • dataset_code required string: Each dataset on Quandl has a unique dataset code. For example, to access the dataset named Apple Inc. (AAPL) use the dataset code AAPL. The dataset code must be used in combination with the database code, for example, to retrieve the dataset named Apple, use WIKI/AAPL.
  • end_date string: Retrieve data within a specific date range, by setting end dates for your query. Set the end date with: end_date=yyyy-mm-dd
  • limit string: You can use limit=n to get only the first n rows of your dataset. Use limit=1 to get the latest observation for any dataset.
  • order string: Select the sort order by passing the parameter order=asc|desc. (Notice that the | in the parameter specification separates various mutually-exclusive options). The default sort order is descending.
  • rows string: You can use rows=n to get only the first n rows of your dataset. Use rows=1 to get the latest observation for any dataset.
  • start_date string: Retrieve data within a specific date range, by setting start dates for your query. Set the start date with: start_date=yyyy-mm-dd
  • transform string: Perform calculations on your data prior to downloading. The transformations currently availabe are row-on-row change, percentage change, cumulative sum, and normalize (set starting value at 100). Set the transform parameter with: transform=none|diff|rdiff|cumul|normalize

Output

• output object
  • dataset_data required object
    • order required string
    • data required array
      • items object
        • 0 array
          • items object
        • 1 array
          • items object
        • 2 array
          • items object
        • 3 array
          • items object
    • frequency required string
    • end_date required string
    • start_date required string
    • column_names required array
      • items object

datasets.database_code.dataset_code.get

You can download both data and metadata in a single call, using the following API request. (You can replace .json with .csv or .xml in this request. If you use .csv, only data will be returned.). In this call, you can customize the dataset object being returned, exactly as in the /data request above.

quandl.datasets.database_code.dataset_code.get({
  "database_code": "",
  "dataset_code": ""
}, context)

Input

• input object
  • collapse string: Parameters to indicate the desired frequency. When you change the frequency of a dataset, Quandl returns the last observation for the given period. By collapsing a daily dataset to monthly, you will get a sample of the original dataset where the observation for each month is the last data point available for that month. Set collapse with: collapse=none|daily|weekly|monthly|quarterly|annual
  • column_index string: Request a specific column by passing the column_index=n parameter. Column 0 is the date column and is always returned. Data begins at column 1.
  • database_code required string: Each database on Quandl has a unique database code. For example, the database code for “Wiki EOD Stock Prices” will have the Qunadl code WIKI.
  • dataset_code required string: Each dataset on Quandl has a unique dataset code. For example, to access the dataset named Apple Inc. (AAPL) use the dataset code AAPL. The dataset code must be used in combination with the database code, for example, to retrieve the dataset named Apple, use WIKI/AAPL.
  • end_date string: Retrieve data within a specific date range, by setting end dates for your query. Set the end date with: end_date=yyyy-mm-dd
  • exclude_column_names string: Request data without column names by passing the exclude_column_names=true parameter. This can only be applied to CSV.
  • limit string: You can use limit=n to get only the first n rows of your dataset. Use limit=1 to get the latest observation for any dataset.
  • order string: You can select the sort order by passing the parameter order=asc|desc. (Notice that the | in the parameter specification separates various mutually-exclusive options). The default sort order is descending.
  • rows string: You can use rows=n to get only the first n rows of your dataset. Use rows=1 to get the latest observation for any dataset.
  • start_date string: Retrieve data within a specific date range, by setting start for your query. Set the start date with: start_date=yyyy-mm-dd
  • transform string: Perform calculations on your data prior to downloading. The transformations currently availabe are row-on-row change, percentage change, cumulative sum, and normalize (set starting value at 100). Set the transform parameter with: transform=none|diff|rdiff|cumul|normalize

Output

• output object
  • dataset required object
    • database_id required number
    • order required string
    • data required array
      • items object
        • 0 array
          • items object
        • 1 array
          • items object
        • 2 array
          • items object
        • 3 array
          • items object
        • 4 array
          • items object
    • end_date required string
    • start_date required string
    • premium required boolean
    • type required string
    • frequency required string
    • column_names required array
      • items object
    • oldest_available_date required string
    • newest_available_date required string
    • refreshed_at required string
    • description required string
    • name required string
    • database_code required string
    • dataset_code required string
    • id required number

datasets.get

You can search for individual datasets on Quandl by making the following API request. The API will return datasets related to your query, as well as datasets that belong to databases related to your query. Datasets are returned 100 results at a time. You can page through the results using these parameters:

quandl.datasets.get({}, context)

Input

• input object
  • database_code string: You can restrict your search to a specific database by including a Quandl database code. For example, the database code for “IMF Cross Country Macroeconomic Statistics” is ODA.
  • page string: The current page of total available pages you wish to view.
  • per_page string: The number of results per page that will be returned.
  • query string: You can retrieve all datasets related to a search term using the query parameter. Multiple search terms should be separated by a + character.

Output

• output object
  • meta required object
    • current_last_item required number
    • current_first_item required number
    • total_count required number
    • total_pages required number
    • current_page required number
    • per_page required number
    • query required string
  • datasets required array
    • items object
      • database_id required number
      • premium required boolean
      • type required string
      • frequency required string
      • column_names array
        • items object
      • oldest_available_date required string
      • newest_available_date required string
      • refreshed_at required string
      • description required string
      • name required string
      • database_code required string
      • dataset_code required string
      • id required number

databases.database_code.data.get

You can download all the data in a premium database in a single call, by appending /data to your database request. You can specify whether you want the entire history, or merely the last day’s worth of updates, by setting the correct query parameters.

quandl.databases.database_code.data.get({
  "database_code": ""
}, context)

Input

• input object
  • database_code required string: The unique database code on Quandl (ex. YC)
  • download_type string: Data returned can be either partial or complete. Partial returns results from the last day, while complete returns the entire database. Default is complete.

Output

Output schema unknown

databases.database_code.codes.get

You can download a list of all dataset codes in a database in a single call, by appending /codes to your database request. The call will return a ZIP file containing a CSV.

quandl.databases.database_code.codes.get({
  "database_code": ""
}, context)

Input

• input object
  • database_code required string: The unique database code on Quandl (ex. YC)

Output

Output schema unknown

databases.database_code.get

This call returns descriptive metadata for the specified database.

quandl.databases.database_code.get({
  "database_code": ""
}, context)

Input

• input object
  • database_code required string: The unique database code on Quandl (ex. WIKI)

Output

• output object
  • database required object
    • image required string
    • premium required boolean
    • downloads required number
    • datasets_count required number
    • description required string
    • database_code required string
    • name required string
    • id required number

databases.get

You can search for specific databases on Quandl by making the following API request. The API will return databases related to your query. Databases are returned 100 results at a time. You can page through the results using these parameters:

quandl.databases.get({}, context)

Input

• input object
  • page string: The current page of total available pages you wish to view.
  • per_page string: The number of results per page that will be returned.
  • query string: You can retrieve all databases related to a search term using the query parameter. Multiple search terms should be separated by a + character.

Output

• output object
  • meta required object
    • current_last_item required number
    • current_first_item required number
    • next_page required number
    • total_count required number
    • total_pages required number
    • current_page required number
    • per_page required number
    • query required string
  • databases required array
    • items object
      • image required string
      • premium required boolean
      • downloads required number
      • datasets_count required number
      • description required string
      • database_code required string
      • name required string
      • id required number

Definitions

This integration has no definitions