Python and R important for data scientists

In our blog post today, we will talk about 2 programming languages that anyone who wants to become a data scientist or who will come into contact with data science at some point should know, from engineers to software. The point we will mainly touch on is why we need to know these software programming languages, and from here we will touch on the importance and usability of software languages.


Data science is a rapidly growing and increasingly important area. Statistics, computer science, and artificial intelligence data with the basic science area, a large number of needed tools and expertise used to analyze the data. the two most important programming languages Python is used in data science and R is worth the time to learn. Each specific niche separates it from other languages and has unique features.


Because neither of them is widely used in real-world data science companies around the world, also both know will help you become a versatile data scientist can fit in anywhere. This article describes the basics of R and Python as well as data scientists, we share the specific use and application.


Let's start with python now:


Python: Easy Syntax + Powerful Libraries

Compared to other languages, Python programs are both short and readable. Syntax skips unnecessary special characters. The philosophy of the Python community, simplicity, readability, uncertainty avoidance, and encourages one to have a clear path to accomplish any task. This philosophy is both the language itself dates back to the third-party library.


It began Python as a scripting language, so regulating the components of a larger system was used to write simple scripts. modify files, text processing, and other common tasks are often automated with Python. Language and programming community grows and evolves, more and more people made more complicated language Python web application previously started using to write back-end and other software.


This brings us to today. Scientific instruments, with the proliferation of other powerful tools of machine learning libraries and Python, as a way to interact with many of the leading technology used in data science, has proved themselves a robust way. Python libraries such as the calculation itself but not fast enough to implement weighted NumPy code, this calculation library is heavily optimized to facilitate the transfer of local code.


Here are a few use cases and libraries that make it easier for them to Python:

-Machine learning with libraries like TensorFlow and scikit-learn

-Numerical and scientific computing with NumPy, SciPy and Matplotlib

-Automate tedious procedures with standard library (built-in) functionality

-Creating web apps and web-based visualizations with Flask or Django



R: Advanced + Heuristic Stats

Python, a large number of data used in science, although a very general-purpose programming language with a third-party library, RI, is a more specific language designed specifically for statistical calculations. as well as built-in features found in both the R and Python NumPy Matplotlib includes several features in the Python library. Out of the box, RI performs almost all standard statistical functions, creates charts and graphs, makes calculations and linear algebra can be used for much more.


R and this is often used as an interactive, data scientists, statistics and math functions built-R facilitates the visualization and analysis tools in an efficient way the new dataset using the extensible programming environment.


R Shiny with libraries as possible to create an interactive control panel for exposing data and visualizations. For these reasons, it is likely to encounter the R code in many work environments.


R, while the Internet in a wide variety of third-party libraries and packages, it does not compete with the choice of Python. R is generally used to write web applications or scripts. In addition, Python is used more often today than R machine for learning. However, both languages are used extensively in the world of science data. R is not focused almost entirely on statistics, the wide variety of problems in this area match perfectly. Moreover, R is much faster than Python, without third-party libraries for numerical calculations.


More specifically, R is some common uses include:

-Data mining and data analysis

-Matrix and vector mathematics

-Regression models, time series analysis, statistical modeling, etc.

-Visualization of charts, graphs and interactive dashboards with R Shiny and similar libraries

and finally


The data is a versatile scientist with Python & R

Python and R, have their own places in the toolbox of a data scientist. Programmers and data scientists throughout their careers often learn the programming languages, a dozen or so, so be proficient in both languages is very likely. Some companies, for all the data they need when using a language as a special science, others can mix and match accordingly. Each learns both languages will prepare you for success in a variety of working environments and situations.


Our Finage team is ready to give you more information about python and R and to answer your questions. We look forward to your consultancy and contributions.


Artificial intelligence and machine learning technologies will feed financial systems such as Forex API, stocks API. Technologies like these are technologies that make data analysis easier. It will support major developments in the real-time market space.


On the other hand, as the Finage family, we support technological developments in every aspect. We offer technological developments to your service by processing them in order to make them usable. We owe the satisfaction of the Finage API system to our customers to our work team that processes technological developments.


As the Finage company, we aim to present our articles on more detailed topics such as US Stock API, Live Market Data API, and Algo Trading API in the near future. Beyond that, you can browse our articles on topics such as Finage Stocks Data API, Finage Forex Data API, Finage Cryptocurrency Data API. For your possible questions, Finage consultants will welcome you with team spirit and take care of your questions.