Have you ever heard the word Python? Yes, you are right it is a versatile programming language so you knew it. But do you know why it is essential in the world of data? No worries, today we will help you to learn the significance of python language towards data analysis and data science.
Let’s start it without wasting time first we will look into the definitions of each disciple. The definitions will help you to understand it more effectively.
Table of Contents
What is Python?
Let’s understand first what the producer of Python explained about it. As “an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built-in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components.”
This is also known as a general programming language, which means it is applicable for web and desktop application development. Apart from it, it is also widely used in complex numeric and scientific applications.
What is Data Analysis?
There are a number of responsibilities associated with the job of data analysts. It includes data collection, interpretation, analysis, and reporting of the results respectively. Similarly, they have to perform trend analysis of complex data sets, review different kinds of reports and identify the key performance indicators.
Besides, they also work for quality control and do strategic planning for future development and growth. These all are some kinds of repetitive work and maybe the situation varies but the nature of the task remains the same. In this context, the python tool is the most fitted one for all the associated tasks. You need to just understand and use it once then the repetition is very simple in python.
What is Data Science?
Data science is known as an advanced analytics technique that works under scientific principles in order to identify the most valuable information. The insights obtained through data science is used to make rational decision regarding the growth and development of business, firm, or enterprises. It includes operational efficiency, helps to identify opportunities, improves marketing strategies, boosts sales, and is beneficial to get a competitive advantage.
Now you have an overview of both disciplines, you have understood the slight difference between data analysts and data scientists, and also you became aware of the key responsibilities of careers. Now let’s discuss why python is essential for both of them.
Why Python is essential?
This is one of the multi-functional programming languages with plenty of uses in context to complex data sets. There are different characteristics of python that makes it most suitable for both disciplines. Let’s discuss them one by one:
Easy to learn
If you compare it with different programming languages like C++, Ruby, and Java is much more difficult to excel but since python focus on simplicity, clear syntax, and readability, it has become much easier. This is the reason that it is considered the best tool for beginners.
Flexibility
This is one of the most flexible tools that provide many advantages in any type of data interpretation. It includes data models, systematizing data sets, creating ML-powered algorithms, web services, and data mining. This is the reason that it is applicable to both fields of data science and data analysis.
It’s Open Source
It is a community-based model for development which means an open source. It can be used on multiple platforms like windows as well as Linux. It also includes multiple opens sources like python libraries, data manipulation, data visualization, statistics, mathematics, machine learning, and natural language processing
It’s Well-Supported
Speaking about support, so, python has got enormous support. Since it became much more popular globally, it has huge following in academic and industrial circles. This means that you can have plenty of material support at zero cost. The more follower it has the more chances of learning and material.
Teaches the basics
If you are a data scientist so you will observe that overlapping exists between python and data science applications. Hence it will be much easier for the data scientist to learn the concepts, even though you can learn them through a simple tutorial. However, the primary things that a data scientist will get by using python are cleaning, retrieving, visualizing, and building models.
Conclusion
Back to your question that why python is essential? after all the discussion now you may have got an idea regarding the essential components of python. However, the data scientists and data analysts both are doing a pretty tough job. The advantage for them is the repetition of work and tasks so it is good for both of them to utilize the facilities provided by python. In last, as we have discussed the overlapping, I must day this is a competitive advantage for data analysts and data scientists that you already have basic and it would be easy for you to understand.
