<h2 class="ql-align-justify">Important Advantages of Using Python for Data Science</h2>In the world of data science, there are many different programming languages. However, Python has become a very popular and powerful programming language. First, Python is one of the easiest programming languages to learn. Even if people have no background with coding, learning Python will not be difficult. Python is also a programming language that clean and easy to handle. It requires only a few lines of coding which can significantly cuts down the coding time. Furthermore, other reasons why python is quite popular among data scientists are because Python also comes with huge range packages such as NumPy, SciPy, PyBrain, Pandas, etc. These packages make python incredibly simple to code complex data analytics problems. Lastly, Python equipped with libraries such as ggplot, Matplotlib, NetworkX, etc. and APIs that allows you to create better data visualizations and integrate other big data visualization tools. <h2 class="ql-align-justify">Understand Python Libraries to become a Great Data Scientist</h2>Python has been best and the most used programming language for data science. It boasts numerous libraries that makes data scientist job easier. There are several python libraries that shall be known and understand by every data scientist. First, Pandas. It is a Python library that provides high-performance, easy-to-use data structures and data analysis tools for the labelled data in Python. Then, NumPy; known as a general-purpose array-processing library that used for basic array operations like add, multiply, slice, flatten, reshape, index arrays. Continue to the next libraries, there is Matplotlib and Seaborn libraries. Both of them are the most powerful libraries when it comes to visualizing data. They provide numerous types of plot ranging from simple to high level. Next, there is Scikit Learn that focused on data modelling. It is a robust machine learning library for Python which features ML algorithms like SVMs, random forests, k-means clustering, and much more. After that, StatsModel. It is a Python library that provides easy computations for descriptive statistics, estimation, and inference for statistical models. It can do statistical analysis like linear regression, correlation analysis, survival analysis and others. Lastly, TensorFlow is a library that helps data scientists create large-scale neural networks with many layers using data flow graphs. <h2 class="ql-align-justify">Five Things That You Can Do with Python Programming Language</h2>Compared to other languages, Python is easier to learn and use for data scientists. Its functions can be carried out with simpler commands and less text than the most competing languages. There are several things you can do with Python that could jumpstart your career in the data science world. First, Python can be used to build server-side web applications and can be integrated with any frontend. Generally, developers use JavaScript in frontend and python for supporting server-side operations. Then, Python can be used for automation and scripting such as set cron jobs and reminders. After that, Python could support games development. You can make cross-platform games using Kivy (Open source Python library), which runs on Windows, Mac, Linux, Android, and iOS. Furthermore, Python provides an easy way to parse and consume unstructured data on web as well as do further analysis and operations of it. Python makes it even easier with its amazing support and libraries. Lastly, Python is well suited for data manipulation, analysis, and implementing complex algorithms. Data parsing and visualization are usually a few lines of code with python libraries like NumPy, scipy, and scikit-learn. Python can also be used in data-intensive and machine learning application using a lot of popular libraries like NumPy, Pandas, Matplotlib, and Seaborn. ConclusionPython is proven to give various benefits. Therefore, it is not surprising that Python is the most popular programming language in the world of data science. If you aspire to become a successful data scientist in the future, learning Python programming language could be a good first step.Reference:Raschka, S. (2015). Python machine learning. Packt publishing ltd.Veeraraghavan, S. (2021, April 9). Best Programming Languages to Learn in 2021. Simplilearn.Com. https://www.simplilearn.com/best-programming-languages-start-learning-today-articleWhy Python is One of the Most Preferred Languages for Data Science? (n.d.). KDnuggets. https://www.kdnuggets.com/2020/01/python-preferred-languages-data-science.html

Python has been best and the most used programming language for data science. It boasts numerous libraries that makes data scientist job easier.

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Utilize Python Programming Language to Gain Success in the World of Data Science