Last Updated on by Kumar Raja

Python For Data Science

Python is a very prominent programming language whose applications can be found across multiple fields & technologies. Being open-source in nature, Python can be interpreted as a high-performance language that is best fit for various analytics operations in Data Science. It has many libraries that support the mathematical, statistical, and analytical services involved in Data Science. Also, it’s easy to learn & easy to code syntax have made the best-loved programming language by Data Scientists. Data Scientists with no prior coding experience won’t be finding any difficulty performing analytics operations using Python.

In addition to Data Scientists, Python is also the preferred programming language of Machine Learning professionals. As the prominence of Python is growing relentlessly across various fields & technologies, this is the perfect time to get started with the learning process in Python. Learn how to code with Python & boost your programming skills by joining for the real-time Python Training In Hyderabad program offered by Kelly Technologies.

Now, let’s have a look at the most commonly used Python libraries for Data Science.

Most Commonly Used Python Libraries For Data Science-

  • Numpy

Data Scientists can make use of the Numpy library in Python to execute mathematical operations for handling large dimension arrays. This library supports different execution functions for Array, Metrics, and linear algebra.

By using this library, Data Scientists can speed up their operation execution. Also, while dealing with large multi-dimensional arrays, Data Scientists will find it easy to work with NumPy.

  • Pandas

Most of the budding Data Scientists make use of Pandas for data manipulation & other analysis operations on Big Data. Also, most of the experienced Data Science experts will be relying on Panda when it comes to manipulating large volumes of structured data. It has significant data structures that make manipulation of numerical tables and time series data a lot easier. It also supports data wrangling & data visualization operations.

  • Matplotlib

When it comes to performing Data Visualization operations, most of the Data Scientists are very much comfortable in working with Matplolib. Using this library, Data Scientists can make use of various approaches & techniques to visualize data more effectively. Also, by using Matplotlib, depicting visuals in the form of interactive graphs, pie charts, histograms, and other professional-grade figures becomes a lot easier.

Apart from these, other libraries like Scipy, Scikit-learn are among the most extensively used libraries in Python for Data Science. Not just Data Science, the applications of Python can also be seen in the Web Development industry, Gaming, VFX, Application Development & across many other areas. Become a skilled expert in Python programming by joining for the best-rated Python training program offered by Kelly Technologies.

Leave a Reply

Your email address will not be published. Required fields are marked *