Being a data analyst is hard. Data is really important for every business and research. This is exactly why the data analyst industry is booming year by year. Today we have seen the rise of programming languages and coding as well. This has led to a question and a possibility that if programming is mixed with data analysis industries, the potential could be huge. So today, we will be answering the question if it’s necessary to learn python to be employable and competitive?
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3 Types of Programming Used In Data Science
Computer programming languages allow you to give instructions to a computer in a language that the computer understands. Like many human-based languages, there are various computer programming languages that programmers can use to communicate with a computer. The part of the language that a computer understands is called “binary.”
Programmers are in high demand these days – the mastery of the coding language is priceless. Knowledge of various programming languages doesn’t make it very difficult for engineers, but a basic understanding of the languages can benefit anyone, even if you don’t want to be a coding expert.
Understanding the general understanding of coding will help you properly engage your business needs, communicate better with your engineering team, and avoid unpleasant misunderstandings (Ruby is not a gem, Java is not a good cup of coffee). To be honest there are a lot of programming languages that you can learn to enhance your skills. Here are top 4 programming languages that are not only popular but also drives great result. Let’s look at each of them separately.
- Java is one of the most popular programming languages, used to build server-side applications for video games and mobile applications. It is the first language for app development, which makes him a favorite among many apps. WORA is designed to be portable and works happily on a wide range of software platforms.
- Python is a structured descriptive-level programming language with semantic capabilities. High-quality data structure and combined with excellent typography and binding. This makes it ideal for rapid application development. This includes using scripts or language glue to link all components together.
- C is a general procedural computer programming language that supports structured programming. With a static type system, C design provides a structure that is effectively matched with special machine indicators. C is highly portable and used for scripting system applications and more.
Now that we know the most used programming languages, let’s move onto the other part of the story. Let to get the average pay a data scientist gets as well as other factors to consider.
Can Python Change the Game?
Python is an open-source, interpretable, and high-level language that provides an excellent approach to object-oriented programming. Python is one of the best languages used by data scientists for various data science projects/applications and has excellent functions for handling mathematical, statistical, and scientific functions. It has a great library for handling computing applications.
One of the main reasons why Python is widely used in the scientific and research community. This is due to its ease of use and simple syntax. This makes it easier for those without a technical background to adapt. It is also ideal for making rapid prototypes. Python is the ideal choice of someone if they refer to code-based applications and more. It is also ideal for implementing algorithms.
There are also Python packages specifically designed for certain features, such as Panda, NumPy, and SciPy. Data analysts and researchers who often refer to machines and want to learn them deeply love Python Matplotlib, another Python package, is also a complete solution for data science projects that require graphics and other visuals.
It is called python when the code is written fluently and naturally. In addition, Python is known for other features that have captured the imagination of the scientific data community.
Is R Programming Enough?
R is a free programming language and software environment for statistical calculation and graphics, supported by the R Core Team and the R Foundation for statistical calculation. The R language is widely used among statisticians and data processing companies in the development of statistical software and data analysis.
R programming is best studied statistically, with libraries unsuitable for data exploration and experimentation. Python is a better choice for machine learning and large-scale applications, especially for data analysis in web applications.
One review performing a comparative analysis says that “I think you can use R programming can solve many deep learning problems. I had some experience using R & Python to construct deep learning. Although many experiments on the internet almost using python, R increases quickly and will become the most popular for those willing to apply deep learning. In many deep learning problems, we only use R alone to solve them easily.”
Average Pay of a Data Analyst
Collaboration brings together ideas and actions to identify and interpret data that enable management, stakeholders, and other leaders in the organization to make informed decisions. Experts will be able to answer questions about the competitive environment, internal and external business interests, and the lack of specific data and advice based on data they provide to potential stakeholders.
The Master in Professional Management and Management prepares students for the role of a data scientist by discussing conceptual ideas, performing statistics, data analysis, forecast analysis, and risk management in a business environment.
Before we get into how much a data analyst earns, Please note a few things, whenever someone works with a company it depends upon a lot of factors like degree, industry, specialization, interview skills, knowledge, and the potential of the individual. So, these figures are just an overview and might not be true for every person.
In this day and age, even if starting at zero levels as a data analyst and have a proper degree then you have the potential of earning ₹325,616 every year. Although, if you are at intermediate level and you have done a few internships or jobs then you are qualified to actually a lot more. According to Glassdoor, glass doors at the intermediate you can earn up to ₹635,379 in India.
Now we already know what is as well as why you should learn it. In this section of the article, we will look at some of the ways that you can learn Python that sticks with you. As well as we’ll look at some of the resources that you can use to learn and grow with Python. Here are four ways that you can efficiently learn the Python programming language
- Consistency is really important and that is why when you are learning Python start by actually coding while you learn.
- If you are just starting out and you do not have solid material to start coding, start taking notes. If you start taking notes you will learn more because you will build memory not only in your mind but also in your hands.
- Notice what they do not teach you. Sometimes the person teaching you will make mistakes. Learn from them and notice how the wrong procedure is giving different results so that if you are in a similar situation you can enter the wrong cord and derive desired results.
- Contact other developers on the same journey as you and ask them if they would like to work on a beta project together with you. It will help you realize your mistakes as well as learn better.
Now that you know how to efficiently learn Python language let’s look at where you can learn it. If you do not want to pay the price for learning Python course, watch this YouTube playlist. Although, we do not recommend any other course click here to know about it. Now you know that Python can change your professional life and open more opportunities for you, go out there and have fun while learning.