While there are many programming languages, Python is the only one that has stood tall among them. This is because it comes with numerous libraries that can help you analyze, visualize, and represent data in whichever way you want. Recently, Python has become the programming language that data experts prefer most. The rise in popularity can be attributed to the numerous libraries available in Python, which can be easily used in working on your data science projects. Sometimes data science experts find it difficult when it comes to choose the correct programming language. Even in the field of business, choosing the correct programming language for big data analysis has proven to be tough. It is essential to select the right language before starting a project, as you cannot change the language midway through. Below are some of the reasons why Python should be your language of choice for data science projects and why most Data Science Course teach you Python coding.
Easy to learn
When compared to other programming languages, Python is the easiest of them all. It is a language that can even be used by those who are not experts in data science. The language is easy to learn because it has an abundance of learning resources and readable codes, and it is used by a large group of people. This means that if you encounter any challenges midway through your project, there are a lot of people you can turn to for help. If you are into business and want to analyze your big data, you can hire Active Wizards developers to help solve all your data science needs. The bottom line is that python is easy to learn with concepts that can be directly applied to your project.
Less for more
With python, you can get a lot of programs up and running with just a few code lines. This is because it can automatically identify and at the same time associated with data types. In general, Python can be used with ease, and also it does not consume much time when it comes to coding. Perhaps one of the most significant benefits is that there is no limit to the type of data you can process. While it has been claimed in the past that Python was slower, recent developments have introduced platforms that make it faster in data processing.
While there are many programming languages, Python is the only one that has stood tall among them. This is because it comes with numerous libraries that can help you analyze, visualize, and represent data in whichever way you want. In the recent past, Python has become the programming language that data experts prefer most. The rise in popularity can be attributed to the numerous libraries available in Python, which can be easily used in working on your data science projects. Sometimes data science experts find it difficult when it comes to choosing the correct programming language. Even in the field of business, choosing the correct programming language for big data analysis has proven to be tough. It is essential to select the right language before starting a project, as you cannot change the language midway through. Below are some of the reasons why Python should be your language of choice for data science projects.
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Python is compatible with Hadoop
The fact that Python is compatible with Hadoop should be enough reason for it to be preferred over other programming languages. At the moment, Hadoop is a very popular big data platform. The compatibility of Python with Hadoop means that programmers can write Hadoop MapReduce programs and applications while using Python. The PyDoop library allows you to perform Hadoop functions on the project you are working on.
The popularity of python is soaring beyond its limits. You can now find people working in various departments, like marketing, customer care, and even maintenance, who have a basic understanding of Python. In general, the use of Python as the favored programming language is a win-win situation for both business enterprises and data science experts.
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