Python: the language of the future

Data scientists around the world are making Python a key component of their programming toolbelt for three reasons. First, Python is a quick language to learn. Second, Python is a high-level language. Third, Python has a huge library of data science tools to select from.

Python provides a quick starter for new language learners, providing a more intuitive, high-level language than competitors like R. For data science, there are a number of languages that can be used, including R. Despite the fact that the R programming language is one that is widely used and built specifically for statistical computing and a host of other statistical calculations, the fact is that according to Eremenko (a data science instructor for Udemy), R is an incredibly hard language to learn upfront. Those who start with Python quickly realize that they can be performing operations in no time (Eremenko, 2020).

Python is a high-level language that allows algorithms, web scraping, and other essential data functions to be done with ease. Python allows data scientists to focus on data rather than on menial tasks like allocating a specific part of memory. For this reason, Python is preferable to languages like C++ that require high amounts of specific instruction. Web scraping tools, like Beautiful Soup, allow for some of the quickest access to data out of any language. The ease of using these tools, their constant improvement, and the quick turnover in data make Python such a compelling language in data science.

This has led to a large number of programmers using Python, allowing the creation of programming libraries, which make the work of finding data, analyzing it, and drawing appropriate conclusions from it to be surprisingly easy to do. Because programmers like to simplify their jobs, many teams develop programming libraries that can be used for a variety of purposes. Data scientists were quick to integrate Python because they recognized the value of its ability to quickly analyze data, and thus a huge library of data science tools was developed.

Anyone interested in getting into data analytics should take a serious look at what Python has to offer. Python is an easy, yet powerful language to learn. It is both high-level and extremely functional. Python’s functionality has made it an industry standard that by all indications will remain useful and prolific into the foreseeable future.

References

Eremenko, K. (2020, April 29). Udemy.

Retrieved July 2020, from R vs. Python - which is best? ]  

Udemy.com:

https://blog.udemy.com/r-vs-python-which-is-best