Python is a programming language that helps in handling your data in different course of actions. It plays a vital role in the fields of Machine Learning and Artificial Intelligence. Thus, it is used worldwide.
We live in a digital world where we depend on technology-driven electronic devices. Data is the primary aspect of every business. It is important to collect, process, and analyze the data quickly and accurately. Processing and handling of large volumes of data is not only time consuming but also a costly affair. This is where data science industry comes into picture. It facilitates the entire data handling process since it resolves, understands and executes the data in less time and give smart solutions that helps the organisation take strategic decisions.
Why phyton is a better option to use instead of other programming languages for Data Analysis?
- Python is an object-oriented language that helps to streamline large, and complex data sets.
- No programming background is required to use python for data Analyst.
- Python is easy to learn with respect to other languages like C++, java, etc. It is less time-consuming as we just need to write few lines to complete the code (I would say it’s like a laymen’s language) to perform an operation.
- Phyton is widely recognized because of its clear syntax and readability.
- Python is built with open-source big libraries to use the functionality.
- You can use the external modules (which are written by someone else) in your program and it gives you the flexibility to do the different complex operations. For example, if you want to play a soundtrack using Python, you need to import an external module i.e., “Play sound”.
- It helps in Data Visualization, Statistics, Manipulations, Machine Learning Algorithms, and many more. These approaches make it popular globally and help the Data Analyst to meet the possibilities.
- Python is easily accessible since it is free software.
