About Data Analysis Using Python
Data analysis is a technique within which data is collected and arranged in order that one will derive useful info from it. In different words, the most purpose of data analysis is to seem at what the data is trying to tell us.for instance, what will the data show or do? What will the data not show or do? In present time Data Analyst is one of the hottest professions of the time and here in our training program you are going to learn how Python is helpful for data analysis. Once you are a Python expert, you will be able to solve any data analysis problem with an ease.
In recent years, a number of libraries have reached maturity, allowing R and Stata users to take advantage of the beauty, flexibility, and performance of Python without sacrificing the functionality these older programs have accumulated over the years.
Why Python For Data Analysis
Python and R are two very popular open-source programming languages for data analysis. Frequently, users debate as to which tool is more valuable, however both languages offer key features and can be used to complement one another. A common perception is that R offers more depth when it comes to data analysis, data modeling and machine learning, but Python is easier to learn and tends to present graphs in a slightly more polished way. There are many more reasons for using Python for Data Analysis which are given below:
- Python is easy to use
- Python is versatile
- Python is better for building analytics tools
- Python has in-built beautiful and efficient data structures
- The Python community is growing
- Python is better for deep learning
- Great number of open source libraries/frameworks/tools available
- Data visualisation with Python