Python is currently the most popular programming language in the world. Many developers feel as though the interpreted programming language with its simple syntax and flexible language is simply the best on the market. But apart from that, even new developers and amateur coders are using Python as their first programming language. This is due to its platform independence and simple user-friendly UI.
Professionals at Cornell University put it well when they said, “Python uses English keywords, and as a result is simple, readable, and maintainable. It’s easily integrated with other programming languages, and supports functional and structure programming, as well as Object Oriented Programming (OOP). Not to mention there is a thriving ecosystem: open source libraries, frameworks and expert community make any problem a temporary one. Also working in Python’s favor is the versatility of the language. Sometimes dubbed the ‘Swiss-Army Knife’ of programming, Python isn’t tied to just one discipline, but can support many, including data analysis, web applications, gaming and automation.”
Python however must keep evolving and listening to the demands of its user base to stay at the top of the industry. As tech is changing so quickly and the needs of DevOps vary from project to project, staying relevant and continually advancing is of the utmost importance.
PyPl The Most Requested Feature
The managers and developers of Python are currently on the lookout for potential programmers who are willing to build a new feature for the Python Packaging Index (PyPI). What Python wants is organizational accounts which are basically an account management system that allows for the consolidation of multiple AWS accounts.
In other words, a PyPI is where a developer will be able to get libraries from the Python Software Foundation. A library in Python is a collection of related modules that contain bundles of code that can be replicated and used in a variety of different programs and applications. These libraries make coding in Python extremely simple in comparison to counterparts such as C++ and Java. These competitors instead require developers to add a classpath before gaining access to or using a library.
Looking at how a dataframe is used, an example of how to rename columns in the Pandas dataframe provides an excellent overview. The first method for renaming a column in the Pandas dataframe is to use the rename () function. This method is rather useful for developers who need to rename some selected columns to specify the important information that will be used in these renamed columns. Secondly, a programmer can also rename columns by assigning a completely new list of column names.