What is API: Technology of Working with Quantitative Data

In these days of information abundance, one is supposed to stop taking the information spread by the media as indisputable truth, at least as far as finance and economics are concerned. Different political forces still hope to mask their goals under populist paroles, adjusting quantitative data, i.e. economic indicators and stock market data to their political needs. But it is economics and finance that are the heroes of our time, not politics. And no one should and would believe an opinion when it is not supported by a piece of funded quantitative research. Moreover, thanks to the existence of the API (application programming interface) technology, one can carry out their own small quantitative research. Indeed, the last EARL (Effective Applications of the R Language) conference has made it clear that we are at the beginning of a new era of journalism - quantitative journalism where anyone who has mastered statistics and data science can do their own quantitative research. In this blogpost, we are going, first and foremost, give an answer to the question, 'What is API?'. Next, we shall see what tools we can use (MS Excel, R and Python) to conduct our own quantitative research. Finally, we shall have a look at one of the stable and professional APIs - Econdb.com.

What is API (Application Quantitative Interface)? | Quantitative Journalism in Economics and Finance: Doing Quantitative Research and Finding the Right Quantitative Data (Economic Indicators and Stock Market Data) for Pitching your Point

Technology | What is API?

What is API (application programming interface) | Quantitative Data of Economic Indicators and Stock Market Data for Quantitative Research
What is API (application programming interface) Technology for Economics and Finance | Quantitative Data of Economic Indicators and Stock Market Data for Quantitative Research 

API stands for Application Programming Interface. To put it simply, it is a web application which allows one piece of software to communicate with another one, i.e. it allows the customer in possession of various tools (e.g. MS Excel, R or Python, which we cover below) using some commands to get access to a database of a web service like Twitter, YouTube or another one. Even more simply, the API technology enables us to get access to some data and process it and tailor to our needs.

How API technology works

API (application programming interface) functions in the following way. The customer sends a call to the database located on the web server of the application. The necessary data is retrieved and comes back to the customer. Thus, the customer gets access to the structured data from a particular web service. 

That reminds the principle of working of any real-life service company. Imagine yourself sitting in a restaurant and making an order. In some 15 minutes (or longer, depending on the restaurant), you finally receive your order. The API technology is based on the same principle. You order the data (imagine that you need some info about economic indicators or stock market data), and provided that the data exists and eligible for public use, you receive it. In contrast to our restaurant example, the API technology does its work in a matter of seconds. 

These days, any relatively big and serious web service is supposed to have its API (application programming interface). Starting from social networks such as Twitter, Facebook and YouTube, you have an opportunity to get access to the information concerning the actions of users, their reactions etc. In the same way, economists and financial specialists can get access to all sorts of quantitative research containing the dynamics of change in economics indicators, stock market data and other types of quantitative data. 

API in economics and finance

In case of economics and finance, it is more important than anywhere else to prove the opinion with quantitative research. What serves this reasoning otherwise? Anyone can say anything today. Social media have facilitated the laymen with an opportunity to disrupt even the most funded source with emotions and politically coloured heresy. That is why the concept of quantitative journalism appeared. How else can one describe a certain tendency in economics or finance? The info, not cemented by facts and quantitative data, does not cost a penny. It is no longer enough just to quote the source. In order to be listened to, one needs to illustrate his or her point of view with quantitative data.

Quantitative Data in Economics and Finance | What is Quantitative Journalism and Quantitative Research?

Quantitative Journalism Technology for Economics and Finance | Economic Indicators and Stock Market Data from API (Application Programming Interface) | Quantitative Data with MS Excel, R, Python
Doing Quantitative Research | Quantitative Journalism Technology for Economics and Finance | Economic Indicators and Stock Market Data from API (Application Programming Interface) | Quantitative Data with MS Excel, R, Python

The time has passed when intellectually looking so-called 'pundits' could escape with misleading words covering nothing more than their ideas, not grounded by any evidence, or quantitative data. It is facts and, even more, the facts illustrated by quantitative data (economic indicators and stock market data) that value today, especially for the areas of economics and finance. Moreover, there are so many resources at our disposal today which can help us access, process and visualise data. MS Excel, R and Python are only some of them. 

MS Excel 

MS Excel, the classic spreadsheet programme, has come along way since its first days. Apart from its classical spreadsheet functions it can now do much more. To name a few MS Excel functions, you can work with databases and big amounts of data, processing it and visualising in the way that you find the most convenient for you and your audience. Visit our MS Excel tutorials to find out more.


R is a relatively new open-source programming language. It built on the base of Fortan and applied for statistics and data analysis. Having a large amount of open-source libraries, R has become one of the most popular tools for statistics, data mining and visualisation. Besides, there are also many applications which are built on R today whose main purpose is to present data. At the biggest R conference in 2016, EARL (Effective Applications of the R Language), one of the London speakers working for the Financial Times, John Burn-Murdoch (@jburnmurdoch), has admitted to the fact that the Financial Times, one of the quality financial and economic newspapers, uses R for data visualisation. Learn more about R by reading our R tutorials.


Python is a little bit older than R and has a wider area of application. The programming language allows us not only to work with data, but also do many other things, such as developing websites automatising various PC processes etc. Like R, Python is open-source and has many libraries which can be used for different purposes. In addition to that, Python is very often used for risk management purposes. To learn more about Python, visit our Python tutorials.

Summing up all, the times we are living in are those of quantitative journalism. Every opinion, be that in economics or in finance, should be covered by quantitative research. On the other hand, thanks to such tools as MS Excel, R and Python, everyone has easy access to various quantitative data facilitated by the API (application programming interface). Therefore, one can and should learn to do quantitative journalism and apply one or all of the aforementioned tools to use economic indicators and stock market data for his quantitative research purposes.  

Econdb.com | How does API (Application Programming Interface) work for quantitative data (economic indicators and stock market data)?

Econdb.com API | Quantitative Data of Economic Indicators and Stock Market Data for Quantitative Research | MS Excel, R, Python for API
Econdb.com API Technology | Quantitative Data of Economic Indicators and Stock Market Data for Quantitative Research | MS Excel, R, Python for API (Application Programming Interface)

There are many API (application programming interface) services all over the web. It is difficult to choose the best one having the widest range of quantitative data available for quantitative research. Moreover, not all API services are technically consistent and have economic indicators and stock market data 

One of the best services you can find today remains ECONDB (econdb.com, @inquirim). The API (application programming interface) service contains the quantitative data of economic indicators as well as stock market data collected by the reputed statistical agencies and economic organisations (OECD, IMF etc.) the world over. The biggest advantage of the ECONDB API service lies in the structure of the quantitative data. The data you retrieve from the econdb.com API is subject to unified standards, which makes the economic indicators as well as stock market data easily retrievable and comparable for quantitative research. 

The econdb.com api service is free and has a very good technical support. Moreover, the service provides professional counselling for quantitative research and accessing the quantitative data in MS Excel, R and Python.   
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