Python is a high-level language used in different types of problem-solving. Python falls in the category of programming languages like C, C++, Perl, and Java. Python is an interpreted programming language. Python programs are interpreted by Python Interpreter one line at a time. The Python programs can be interpreted as a single command in command line mode or as a script saved as .py program. In the topic of how to install Python in Windows, you can prepare your system for Python Coding. Before Coding in Python you must learn about Python Features
Characteristics of Python Coding Language
Used for Data Science Programming
Python is widely accepted and used as a programming tool for Data Science Applications. It has a huge library of packages and tools that can be imported for such applications.
No Licensing Issues and Huge User Community
Python has developed immensely since its creation. No licensing issues lead to its wide acceptance and growth of a big user community.
Python comes with good support of packages listed here which empower different genre of programmers
- Numpy for matrix or numerical analysis
- Scipy for Scientiﬁc computing like image processing
- Sklearn for Machine learning
- Matplotlib for Plotting and visualization of large datasets
- Opencv to implement Computer vision in applications of AI
- Pandas for Data analysis of big data
- caﬀe, theano, Minerva for Deep neural networks
- spyder for scientiﬁc python development environment
Low Learning Curve
Programmers who are already conversant in any programming language will find Python quite easy to learn and master. A large number of functions in packages reduces the development time.
Programs are written just like any procedural language but the program blocks are defined with indentation. No curly blocks or special symbols are used for program blocks or conditional or looping blocks.
Before you start coding in Python, you must select a suitable editor tool. You can also use the default Idle Interface. There numerous editors available to create and manage your Python Programs. You can read from here and select the one that looks easy to you.