Importance of Python for Data Science Professionals!

Python is an open source programming language with a rich set of libraries and tools that make the tasks easy for data scientists. Python community is one of the best in the world. It is very active with any question or query raised by anyone. Data science professionals have been using Python for a long time now. It is undoubtedly the top choice for data scientists and developers. Professionals with Python on their resume are quite desirable in the data science industry. Hence, Data Science with Python training program is perfect for analytics professionals who want to excel in this ever-growing industry. Companies like Netflix are choosing python as their primary language, and encouraging their data scientists and developers to learn the same. In a very short time, Python has made its place in the analytics industry. Today, we will talk about a few reasons why data scientists choose Python over any other language.

1. Python is User-Friendly

Python is known for its simplicity. When it comes to programming, simple is better. Using Python, it takes less time to code a solution. Unlike R, it is versatile and easy. For example, even novice data science professionals can quickly build a machine learning classifier using the popular Scikit-learn package.

2. Python is Flexible and Scalable

Python is one of the most powerful and flexible open-source data analysis tools. It is loved by data scientists for its flexible and robust nature.  It is more scalable than R and faster than Matlab and Stata in solving problems. Due to its flexibility, it is used in developing machine learning models, web services, data mining, classification etc.

3. Python is Better at Building Analytics Tools

Data analytics means extracting data, categorizing it in order to analyze the various patterns, relations, connections and other such valuable insights from it. Python is a better choice for building data analytics tools as it provides better insights and understanding.

4. Python is Widely used in deep learning

There are a lot of deep learning frameworks, such as Caffe, TensorFlow, PyTorch, Keras, and mxnet, helping in building deep learning architectures with a few lines of Python code. Google created TensorFlow using Python as the primary language. Similarly, Facebook has been using it as a prominent language in their environment.

5. Python has a Large Number of Libraries

The rising popularity of Python led to wide-ranging libraries that can be easily imported into projects using the PIP Python package installer. This gives data scientists access to many powerful open-source Python libraries like Data manipulation, Statistics, Mathematics, Data Visualization, Machine Learning, Natural Language Processing and much more. About the author: Nisha Negi is a Technical Content Writer at Multisoft Systems. She writes blog posts and articles on various technical subjects. She is an experienced IT professional, and bears immense knowledge of the latest technology. She stays current with all the ongoing and upcoming certifications. Her way of expression is contemporary and crisp.