Python: Why is the language so used for Data Science and finance?

The programming world has some language options for creating websites and other activities; Python is one of those adopted by many technology professionals.

But an interesting fact is that In recent years, it has come to the fore in two different areas: data science and the finance sector.. If you want to learn the reason for this increasing search in the mentioned sectors and other information about this language, take a look below.

What is Python?

Python is a high-level programming language – High Level Language – developed between 1980 and 1990. It is known for its simplicity and versatility. It allows greater code control due to the special way of editing the software.

It is widely used in software development, automation, data analysis and artificial intelligence, especially due to its wide range of libraries that facilitate its use in different sectors.

Besides, it also has many libraries, local or created by others.It facilitates its adoption by different fields of activity.

Python and data science: what’s the relationship?

According to programmer Bendev Junior, Python is the most used language in data science due to its ease of dealing with analytics and quantitative calculation.

“Python is one of the most used languages ​​when it comes to data science, especially Flexible language and open source making it easy to use for more quantitative calculations“developed with huge libraries that allow for better data analysis.”

Among the main points of more and more people working with data analysis to adopt Python, we can highlight the following:

• Large community: With a large number of users, it is possible to find someone at any time to find the appropriate path in coding;
• The number of libraries is increasing: NumPy, SciPy and StatsModels are just a few of the data science library models available for those who want to use this programming language;
• Ease of learning: Because it’s designed to be simple, anyone can learn Python even without a lot of programming experience;
• Scalability: Python has much faster scalability than other languages ​​and packages.

Python and financial fields: task simplifyer

“Python is also widely adopted in financial fields due to its effectiveness in data manipulation, analysis and complex modelling. It makes domain-related tasks much easier by simplifying tasks such as statistical analysis, risk simulations and financial calculations,” comments Junior.

“Its flexibility and integration with other tools also allow it to become a central choice for automating tasks and developing personalized financial applications,” continues the expert.

It is possible to highlight the following elements that are important for those working in the field of finance and those who want to use this programming language in their daily work:

• Simplicity and flexibility: Since it is easy to write and distribute, it is a good choice for dealing with financial services applications;
• Quickly create MVPs: Python allows companies to customize parts of the code to create a final product that meets the user’s needs;
• Lots of tools: Since it is a language that allows users to create various tools and libraries, it helps make all kinds of development easier and faster compared to other options;
• Analysis features: Analyzing data sets is crucial for anyone working in finance; This is something that Python can offer very well thanks to the resources of its libraries.

Main applications of Python in the financial sector

Among the main areas of use of Python in the daily lives of those working in the field of finance, we can highlight the following:

• Download stock prices from the stock market;
• Analyze main stock indicators;
• Create charts;
• Calculate the risk and return of individual stocks;
• Build an optimized stock portfolio.

What are other uses of Python?

In addition to data analysis and the finance sector, this language also finds its place on other fronts such as web development, computer graphics and even artificial intelligence.

So, are you thinking of learning Python or are you already using Python resources in your professional tasks? What do you think about this language being the basis of various activities? Share your opinion with other readers TecMundo We use our social networks.