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Last Updated on May 14, 2021

Tabular array of Contents

What is Quandl?
What is Quandl'south Data Construction?
What are the Pros and Cons of Quandl?
Is Quandl Free?
Free VS Premium Products
What are the types of Free Data in Quandl?
What are the types of Paid Data in Quandl?
How to create an business relationship in Quandl?
How to access Quandl Information?
How to extract Quandl Information in Excel?
Example of Quandl usage in Excel
How to extract Quandl information in Python?
- Example 1: WTI Crude Oil prices
- Example 2: US GDP Information
- Instance three: Facebook Almanac Written report Information
Quandl in other programming languages
What are the limitations for Quandl downloads?
What are some Quandl alternatives?
More on Quandl's background
Download code

What is Quandl?

Quandl is a platform that provides its users with economic, financial and culling datasets.

Users tin can download free data, purchase paid data or sell data to Quandl.

In this guide, we will cover how to extract data using Excel and Python (separately).

What is Quandl's Data Construction?

Quandl's data comes in two formats: the showtime one beingness Time-series and the second ane being Tables.

Accept in mind that some datasets tin can be shown in both formats.

Time-series

Time-series information refer to data taken over a period of time.

Fourth dimension-series are commonly displayed using line graphs, where the X-axis represents dates and the Y-axis represents other numeric observations.

The Fourth dimension-series format just contains numerical data which is indexed by one date field. This means that the data is sorted by dates. This allows users to retrieve the entire time-series or a particular office of it, also called a "slice".

Most Quandl datasets are stored in the Time-series format as financial data mostly consist of dates and observations which fit the format nicely.

Table format

Tables don't only comprise numerical values.

They can comprise various unsorted information types such as strings, numbers, dates, etc. They tin as well be filtered into different fields.

Quandl ID code

Each feed of data has a short ID, besides known every bit a Quandl code.

For example:

Federal Reserve Economic Data (time-series): FRED
Cadre US Fundamentals (tables): SF1

Time-serial data such every bit FRED is built-up of a large number of individual time-series where each of them has its own Quandl code appended to the main Quandl code, for example: US civilian unemployment rate: FRED/UNRATE.

On the other hand, Tables data such equally SF1 contain one or more tables where each of them has its ain Quandl code, for example: The Quandl code for the Core United states of america Fundamentals table is SHARADAR/SF1.

When information technology comes to Data Analysis tools, Quandl direct supports API, R, Python, Excel, Ruby and more.

The total list tin can be found here: https://www.quandl.com/tools/full-list

What are the Pros and Cons of Quandl?

The Pros:

Quandl offers an enormous collection of data (over 20 million datasets).
All datasets are available for instantaneous download in any preferred format.
All datasets on Quandl are bachelor through the same API, irrespective of who originally published the data or in what format.
Data is transparent.
Datasets are piece of cake to find and clean.
Some parts of Quandl is free and open for everyone.
New data is added weekly.
Quandl can be used in many programs (Excel, Python, R, Ruby, MATLAB…)
You tin can utilise Quandl to sell your data.

The Cons:

Many of the more exotic datasets are non free.
They offer express amounts of help when constructing analyses or discovering data.
Non too beginner friendly.
They don't have real-time or delayed stock price data.
They don't have a principal security list.

Is Quandl Free?

Quandl offers both free and premium products.

The Quandl API is gratuitous to use and grants access to all gratuitous datasets.

Quandl users accept to pay to access Quandl's premium data products.

What are the differences between Gratuitous and Premium datasets?

Every bit the devil is in the details, their free products come from diverse "apparent and established" sources such as central banks, regime agencies, organizations, etc.

On the other hand, their premium products come from information providers such as: AlgoSeek, Applied Research, Barchart, Brave New Coin, and CryptoCompare etc.

The full listing can be seen here: https://www.quandl.com/publishers

Quandl premium datasets have a regular update fourth dimension while there are no guaranteed update times for free datasets and they can normally take anywhere from a few hours to weeks, months or years (depending on the data itself).

Quandl's premium data is curated and maintained by professional providers with decades of expertise under their belts. This all adds on the edification of documentation, correctness, organisation, uniqueness and structure of the data. Here nosotros tin can encounter the supremacy of the premium data.

Premium data on Quandl tin be purchased via subscriptions. With them yous subscribe only to particular datasets that you demand. This means that you only pay for what y'all need. Take in mind that there is no fee to use the platform itself or Quandl's open up data feeds.

Nearly all premium datasets come with some free sample data. To see a gratis sample data, y'all need to log in to your Quandl account. Afterwards clicking on whatsoever premium data feed of your interest, the website volition take you to the home folio of that feed where you will be presented with some sample data.

It needs to be mentioned that every single free data feed has a transparent link that leads to its source. This means that we can verify the data and the source information technology comes from.

What are the types of Free Data in Quandl?

When it comes to free data, Quandl offers you a massive range from Prices & Volume, Fundamentals, Sentiment, Derived Metrics, National Statistics, and Other.

Let's mention some of the free datasets:

Wiki Continuous Futures – This dataset is built on top of raw data from Ice, CME, LIFFE, etc, and is curated by the Quandl customs.
Zillow Real Estate Information – This dataset is the leading existent manor and rental market.
Federal Reserve Economic Data – This dataset includes things such as growth, employment, aggrandizement, labor, manufacturing and many more U.s.a. economic data.

What are the types of Paid Data in Quandl?

When it comes to premium information, Quandl offers datasets related to Estimates, Corporate Actions, Alternative Data, Technical Analysis and more.

Let's mention some of the premium datasets:

Zacks Sales Estimates – This dataset has a consensus of auction estimates for over 4k US and Canadian listed companies.
Nasdaq Dorsey Technical Analysis Information – This dataset is fabricated up of 50+ technical indicators and chart information for over 49k global equities, mutual funds and ETFs.
Sharadar Core The states Equities and Fund Prices – This dataset is self-explanatory.

How to create an account in Quandl?

Having a Quandl account is important as it allows you to:

Admission their API, libraries and tools.
Download free and/or premium data in whatever format.
Access their export and visualization tools.
View relevant data near pricing and licensing for their premium data.

Let's get you started with your Quandl account. Accept in listen that it is free and doesn't require any credit carte du jour information.

Permit's go over the steps:

Go over to the Quandl website (https://www.quandl.com/) and click on the sign up button in the summit correct corner.
A screen will open that requires your first and last name, likewise every bit your purpose of using Quandl (business, academic or personal). And so feel gratuitous to input those fields. Afterward that, click on "Next".
Now, another screen volition appear where you volition input your email address and answer a question on "How will you be using this data?" After that, click on "Next".
The final screen of your signing upwardly process volition appear where yous volition be asked to create a password. After you have created your password and checked the terms of service box, click on "Create Account".
Now, a welcome screen will announced with your API key.

Look Igor, what in the world is this API key?! You lot didn't prepare us for that!

Calm down, exist sure to re-create your key and don't forget to verify your email accost. If yous pressed "Proceed" without copying the API key, it'due south not an issue. You tin can find your key in the Account Details section.

At present let's explain what an API central is!

API key stands for the Application Programming Interface key and is represented as a string of code that gets passed in past a computer to an application. The program or application then uses the API cardinal to identify the user to a website.

The API key is a "secret" authentication token as well every bit a unique identifier.

Call up of it as your personal secret "password" for collecting data from Quandl.

How to access Quandl Data?

The data tin be accessed using Excel, Python, R, MATLAB, Ruddy and more.

Nosotros will cover the Excel and Python methods in this commodity.

How to extract Quandl Data in Excel?

When it comes to Excel, y'all tin pull Quandl datasets in a affair of minutes without any programming skills required.

It's time for us to come across Quandl in action. But commencement, nosotros need to set upwards the Quandl Plugin for Excel.

Allow'south do the steps together:

Get to this link (https://www.quandl.com/tools/excel) and click the blue "Download" button.
Now, click on the downloaded "Quandl Excel Addin" and follow the installation steps.
Later on the installation, open up up your Excel programme and click on the newly appeared "Quandl" in your toolbar.
After that, click on the settings button and insert your API key in the newly opened window and click salvage (equally shown in the flick below)

Example of Quandl usage in Excel

Allow's become our Database. Press the "Go Data" button inside of your Quandl toolbar.
After your API key gets verified (remember that?), we'll select our Data. For this example, I'll pick the European Stock Prices for FSE Frankfurt Stock Commutation.

3. Click the blueish "Next" button and select your preferred stock. I'll use the Zooplus (ZO1_X). Click "Next".

4. Afterwards that, a new window will open that volition ask you to specify what Columns will your dataset have. I selected the Date, Open, High, Depression and Close columns. Click "Next".

5. At present, we'll select the filters that we want for our data. As I
don't want to make the steps too complicated, I won't apply any filters.

vi. After clicking the "Next" push button, you are given a Placement pick aka where do you want your data to be placed at in your Excel sheet. When you specify your Excel Canvass and Cell, click the "Insert" button.

seven. Voilà! Your data is set! If it didn't announced for you, don't panic! Only printing the "Refresh Sheet" button that is constitute in your Quandl toolbar.

For the next case, the steps are the same simply the dataset will be different. I'll show yous a Corporate Almanac Study data for the Facebook Inc. dataset:

The next instance will exist different. We'll utilize the Quandl "Formulas" option to code what we need and desire.

Let's follow the steps:

ane. Let's suppose that we want to download the daily closing prices for two assets in the last 3 days (as shown in the motion picture). First we need to specify that nosotros desire the endmost prices past writing the following string (='your cell'&"/CLOSE") in our formula Excel department. Exist sure to do this for both assets. You tin can just drag the cell with the written code to the other prison cell.

2. Now, allow's add together our Outset and End dates. For this I'll employ the "today()" formula in Excel. For the Commencement date nosotros will write "today()-3" which means past iii days and for the End engagement we volition just use "today()".

3. This stride requires u.s. to utilise the "qseries" formula which, in our instance, looks like this "=QSERIES(D2:E2,B1:B2)" As you lot tin see, the D2:E2 specifies our asset filter and the B1:B2 office specifies our Start and End appointment. Later on the formula is written, refresh the sheet as we did in our past instance, and you're done.

If you want to change stuff up, and look at the data for the past 3 years, in the Get-go date field write "=today()-365*three". Be sure to play with Quandl and so yous go a hang of it!

How to extract Quandl information in Python?

For this part, I'll be using the Jupyter Notebook from the Anaconda application for Information Scientific discipline.

More info on how to set up your Jupyter Notebook: Preparing Your Python Coding Environment

Firstly, we need to install the Quandl packet for Python. For this, utilize the control "pip install quandl".

Allow'southward bear witness a few examples:

Example 1: WTI Crude Oil prices

For this example, we desire to become the WTI Crude Oil price from the United States section of Energy:

ane. We need to import all the packages nosotros're going to employ. For this example, I'll import Quandl, NumPy and Pandas. Note that you need to have NumPy and Pandas installed. They come pre-installed with the Anaconda program and the codes go like this: "pip install NumPy" and "pip install Pandas".

two. Subsequently that, nosotros need to activate our API key. Apply the following command: quandl.ApiConfig.api_key = "YOUR_API_KEY"

3. The next step is to apply the post-obit control "mydata = quandl.become("Eia/PET_RWTC_D")".

It is of utmost importance to know the Quandl lawmaking ("EIA/PET_RWTC_D") of each dataset you lot desire to utilise.

You lot can find the Quandl lawmaking for each dataset under the documentation page of each dataset. Example: https://www.quandl.com/data/EIA-U-S-Energy-Information-Administration-Data/documentation

If you desire to go the same data, simply as a NumPy array, y'all can utilise this lawmaking: mydata = quandl.become("Environmental impact assessment/PET_RWTC_D", returns="numpy")

Example two: US Gross domestic product Data

For our next example, let'due south download a slice of macroeconomic data with specific dates and salvage information technology as a .csv file.

Downloading data from a specific date range in Quandl

1. In order to set specific Starting time and End dates, nosotros shall write the following: mydata = quandl.get("FRED/Gross domestic product", start_date="2019-12-31″, end_date="2020-ix-26″)

2. This is where Pandas come into play, as nosotros desire to save our extracted information to a .csv aka Excel format.

Nosotros will convert our information into a Pandas DataFrame using the post-obit command: "df = pd.DataFrame(mydata, columns= ['Engagement','Value'])"

iii. Afterward that, we will export our data and requite the .csv file a name: "df.to_csv ('Proper noun.csv')"

Example 3: Facebook Almanac Report Data

Let's download a Corporate Annual Written report for Facebook. The steps are the same equally in our first Python case, but with a little twist. Our Quandl code for this 1 is "WIKI/FB".

We specify the years we desire to go through and get the data we'll demand to preprocess it. This ways that nosotros demand to excerpt just the annual part of it.

For this, we shall employ the following command: mydata = quandl.get("WIKI/FB", collapse="annual")

Now our data looks like this:

Now you are all equipped to proceed a Quandl coding journey in Python!

"May the code be with you!" – Obi Wan Kenobi

Quandl in other programming languages

Quandl is likewise equipped for other programming languages like R, MATLAB, Ruby and others.

In this article, we won't go into them every bit it would make information technology too long. But R, Carmine and MATLAB enthusiasts worry not, as I'll provide yous with useful links where you can learn how to use Quandl in your programs!

R – https://www.quandl.com/tools/r

Ruby – https://github.com/quandl/quandl-ruddy

MATLAB – https://github.com/quandl/Matlab

What are the limitations for Quandl downloads?

Quandl needs to limit their users when it comes to downloading and so the API doesn't get over flooded and the whole service crashing down.

Anonymous users are limited to xx calls per ten minutes and 50 calls per day; while authenticated users have a limit of 300 calls per 10 seconds, 2k calls per 10 minutes and 50k calls per day.

When information technology comes to the gratuitous authenticated users, they have a concurrency limit of one which means that they tin can only brand one telephone call at a time and have an boosted call waiting in the queue.

As for the premium users, they have a limit of 5k calls per 10 minutes and a limit of 720k calls per day. They are also limited to ten bulk downloads per hr.

What are some Quandl alternatives?

When it comes to cost and corporate fundamentals, there are the following: Yahoo finance, IEX, Blastoff Vantage, Polygon, TradingView…

More info: Google Finance API and 9 Alternatives

When information technology comes to Alternative data, there are the following: Yard Science, Advan, Thinknum, YipitData, Tegus, Curvation Metrics and many more.

Hither is the full list – https://alternativedata.org/data-providers/

More on Quandl'due south groundwork

Co-ordinate to Quandl, they have over 400,000 users. These ranges from the world's top hedge funds to investment banks and various asset managers.

Quandl'south specialization is in the field of data that gets nerveless over time and is categorized as economical, social and financial data – this includes things like: stock prices, crime rates, unemployment rates, various populations, etc.

They manage to do this past indexing millions of numerical datasets from around the cyberspace. For case, if you lot click on a specific dataset that is indexed in Quandl, it will get to its original dataset source, extract the newest version of it, clean information technology, and give it back to you in whatever grade you want.

Quandl is striving for the democratization of information and making information technology easier to find and apply for all its users. Their goal is to provide their service to various types of users and professions.

Can you lot believe that they fifty-fifty offer data pertained to some basic sport statistics?!

Ok Igor, that all sounds sweet, only how does Quandl acquire data?

Well, Quandl acquires its data by having various homo curators that point their bots at specific datasets. Recently, they've been looking for more curators that are similar to Wikipedia's volunteer editors.

Y'all can also become a vendor and sell your information to Quandl. For this, the technical requirements aren't strict just you need to create, certificate and maintain the data yourself with a "professional standard of quality".

The skilful thing is that the listing of your information to Quandl doesn't come with whatsoever fees. You too get support from the Quandl team for free and your information is viewed every bit your intellectual property.

As a Quandl vendor, you have full transparency of who's ownership/accessing your data. Y'all are likewise provided with a vendor dashboard that shows y'all all the sales, subscribers, revenues and other information in real-time.

Download Lawmaking

Download the Python code used: https://github.com/Lucas170/Quandl-Guide-AlgoTrading101

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Source: https://algotrading101.com/learn/quandl-guide/