Data Science Programming Languages
Data Science is a study of data analysis in different aspects. In several cases of data analysis consideration, there is a general abstract framework that describes a basic structure for how the data should be designed. For example, in the generation of musical notes, there is a certain criteria like using only particular musical notes for the respective melodies. Describing data analysis is a difficult conundrum. Developing a framework involves considering data elements and implementing them using a programming language.
Why should we use programming languages for data analysis?
As we know data is used in many flows like banks to store customer details, hospitals to store patient records etc. For this, we require a place to store all the data. To make it work according to the requirements, we make use of the programming language.
Let’s take a look at the different programming languages we use for Data Science.
Programming languages-
- Python – The most widely used popular language today, used for a large number of applications and also in data science. The main reason to use python is for its great tools and ease of use. It is an interpreted language as it produces the output simultaneously while we provide input to the interpreter. Thus, it provides a base to store all the data.
- R-it is also a programming language specifically designed to meet the needs of data miners. The most basic IDE (integrated development environment) used is RStudio. It is a user-friendly programming that consists of built-in functions to make it easier to handle.
- Java is the widely used and popular language used for various applications. It has many IDEs just like the other languages. Java can be linked with databases very easily and that is the main reason why we use it for many purposes.
There are many other languages like c/c++, scala, perl, julia that are used for data analysis.
As there are many possibilities for a career in data science, knowledge of these languages plays an important role in building your career. Programming is a must in every field these days. Especially when it comes to data. But having knowledge only in programming does not give you much. To consider this, let’s take a look at the general question that might arise.
Who should come to the field of data science?
The answer is obvious. If you have the skills that meet the requirements of a data scientist, you’re good to go! Let’s consider the skills that are required.
- Statistical Skills – The reason this is important is because data deals with the quantitative analysis of data.
- Programming – As mentioned above, programming is required to design the framework for storing data.
- Ability to work with unstructured data – Many commercial organizations retrieve data in an unstructured form. The data scientist must be able to handle this type of data.