Big Data Figure
Date that article was published: September 8, 2022
The Top Programming Languages article describes the most important programming languages to know within the data science industry in 2022. The article lists the top five programming languages and then goes into detail about each language and why it is so important to the practice of data science. In the following section, I will include the five programming languages included in the article and brief summaries of the author’s reasoning behind including each language.
Java is the most widely used and well-liked programming language. It is also typically regarded as one of the most popular for data analytics.
Some Java advantages are:
* User-friendly
* Portable and automated memory management for quick debugging
* Ability to design visually engaging content
* Many libraries
C++ is known as the “fastest programming language” and is perfect for applications where time is important. Common uses of C++ is for data-science based applications such as cloud software, business software, and banking software.
Python is the most widely-used programming language
for data science due to its simplicity and flexibility. In addition,
there are a large number of data science libraries available to Python
data analysts such as:
* Numpy
* Pandas
* Scikit Learn
* Matplotlib
SQL and NoSQL are languages used to query, handle, and process relational databases, the most important piece of data science.
R is used primarily primarily for analytical tasks
as it is able to handle large and complicated amounts of data. Common
packages used in R are:
* Ggplot2
* Dplyr