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Is Python Perfect for Data Science?

Python is one of the most popular programming languages, and it is expanding its user group with each passing day. Python is used to develop applications, create test cases, and many other things in the IT industry. It is also used in Data Science, Big Data, and other Business Intelligence fields. Still, many people are wondering whether Python is a good programming language for Data Science. Let us try to find the answer for the same. 

Data Analysis

Before deciding whether Python is ideal for Data Science or not, let us understand a data analyst’s job roles. The more you understand the job, the better tools and technology you use in the job. A data analyst’s primary responsibility is to analyze the numerous data types, analyze its results through statistical techniques, and provide insights into ongoing projects. They try to optimize the quality and efficiency by developing and implementing the data analysis, data collection techniques, and other strategies. The data analysts are also responsible for gathering the data from primary and secondary sources and maintaining the database. 

Furthermore, they are required to identify, analyze, interpret trends or patterns from complex data sources. They strive to filter and clean the entire data source and are responsible for monitoring the quality and performance of data and identifying improvement opportunities. Finally, they use the outcome of all duties and responsibilities provided so far and help improve a business’s performance by working closely with decision-makers. This is one reason why a data scientist draws a handsome salary, and people are looking to learn python from an online python course for beginners classes

Is Python suitable for Data Science?

Yes, there is no need to argue whether it is the best programming language for data science. Many people are already agreed to this fact and reaping the benefits from the usage of Python. So, rather than discussing whether it is a good choice for data science or not, let us know why it is so versatile programming language and why the aspirants who want to grow their career in data science need to learn Python. After going through the below points, you will understand its importance. Even if you are a beginner in this subject, you can learn it by enrolling in the best online python course for beginners with certificate courses. 

Flexibility

Python is one of the general-purpose programming languages used by millions of people worldwide. That means you can use Python for building both web and desktop applications. This programming language is flexible and versatile. So, you can use it in developing complex and scientific applications. If a developer wants to create new things, then Python is the ideal choice. By using Python, it is easier to script websites and applications. 

Simplicity

Of course, Python is used for complex program development. However, Python, as a language, is straightforward to learn and understand. It focuses on readability and simplicity, and this quality makes it one of the simple programming languages. The syntax of Python is short, and it is similar to English. It is one of the reasons why many beginners select to learn Python rather than other languages. Even if you require to develop a complex program, you no need to write lengthy code. Hence, it lets you spend more time building the logic rather than writing the code. 

Open-source

Many startups use Python because it is available without investment. Since it is an open-source platform, it uses community support for development. Besides, you can easily port the code to numerous platforms. There are numerous open-source libraries for everything, including Machine Learning, Statistics, Data Visualization, Mathematics, and others. The learning of Python is also easy since you can choose the best python training online and learn. Some of the courses are available for free. 

Well supported language

The major problem of any free tool is the unavailability of proper support. But Python is an exception to it. It is followed and backed by a strong community, and if you are stuck with any issue, you can get assistance from the community. Additionally, Python is widening its territory, and hence you can find an increasing number of users. The more users in the community mean you will get more support and frequent updates. 

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