Reasons to Learn Python for Data Science

With the advancement of the internet and computers, companies started to store their data. The database helps them to keep track of all sorts of data. In 2010, companies started focusing on the processing of this data. Since data is converted to information, companies wanted to know what insights it can offer. They felt the requirement of people who can analyze the data. There, data science came into play. It offered jobs like data analyst, data scientist, BI developers, etc. Since then, data science started gaining popularity. According to the survey conducted by Glassdoor, data science was the highest-paid field in 2016. The survey was based on the people working on the data science field and their income growth. People who wish to start a career in this domain often find Python for data science course beneficial to upgrade their skills.

So, let’s try to understand what Python actually is, and why you should learn it for a data science career.

What is Python?

Python is a high-level programming language used for developing web-applications, data science, creating software prototypes, etc. It was created by Guido van Rossum in 1991. The later versions of Python were developed by Python software foundation. Python 2 and Python 3 are two major versions. The syntaxes of Python are easier to understand, thus making it low-maintenance. Python supports modules and packages, hence it becomes easy to write programs in modules and reuse it.

According to the research conducted by StackOverflow in 2016, the users of Python have surprisingly grown since 2012. Comparatively, the users of other programming languages such as java, javascript, PHP, c++, C#  remained almost the same.

Reasons to learn Python
The top reasons to learn Python are the following:

Python codes are simpler

Python codes are simpler than other programming languages. It is high-level, interpreted and resembles the English language. Thus, it becomes easier for people to remember all the syntaxes and write it. The codes of Python are not complex, which makes it more efficient. That is the reason developers and students prefer it.   

Python is used for web development

Frameworks allow you to develop websites. So some popular frameworks such as Django, Flask, Pylons, etc. are written in Python. Thus it becomes easier for developers to make websites. Websites such as Spotify, Pinterest, Instagram, yelp, Mozilla, etc.are developed from Python. For implementing smaller projects, micro frameworks such as Flask and Bottle can be used.  

Multiple libraries

Every programming language consists of libraries. Libraries consist of program codes that are used more often. The compiler automatically links the program with those functions that the program calls. So, Python has numerous open-source libraries that can be used for different purposes. Django and Flask are popularly used for web development. Numpy and Scipy are used for data science. TensorFlow, Scikit learn, Keras, pandas, etc are popularly used for machine learning algorithms and data science.  

Data science

Python is majorly used for data science. Python helps to create advanced algorithms to predict outcomes. Various libraries such as panda, NumPy, SciPy, etc are used.   

Pandas is used for data analysis. It imports the data from the excel spreadsheet and performs the analysis.  

NumPy consists of advanced numerical functions. It was the earliest libraries of Python. The functions of NumPy are also reflected in pandas.  

SciPy is used for scientific calculations. The other libraries of Python are used for statistical calculations and machine learning purposes.  


Automation allows an organization to do repetitive tasks without much human effort. So Python is beneficial for performing automation. Python can be used as a scripting language, which allows for automated testing of software. The machine reads the codes and then executes it. It checks errors during runtime.   

Artificial intelligence

Just like data science, artificial intelligence is also seen growing. We can now get some AI-powered gadgets. Some of the libraries of Python can be utilized for getting insights and making decisions. The libraries used for this purpose are OpenCV, Keras, and TensorFlow. They are equipped with machine learning algorithms.  

User interface

Python is also used for creating GUI and other desktop applications. Small and other online projects are also built with Python. The library Tkinter used for this purpose. Some android gaming applications are built using the library Pygame.  

Over to You

The above reason clearly explains that Python has become an integral part of high technologies. So, if you want to build your career in data science and web development, then it is important to learn Python. Python developers and data scientists get a good amount of salaries. Python has its applications in different areas. So, start by taking up an online course in Python for data science. Enrolling in a course will help you get trained from industry experts and gain a strong grasp of the language. So, learn Python and build your career in different aspects of technology jobs.