How Knowledge in Python Helps to Learn Data Science from Scratch?

 

How Knowledge in Python Helps to Learn Data Science from Scratch?

  • Python is regarded as the number one language by analytics professionals, as in 2018 66% of them stated that they use Python daily for data science operations.
  • Python overtook R as reported on KDNuggets’ annual poll of data scientists’ which was about most used tools by data analysts and scientists, in 2017.
  • The premier platform for data science competitions, Kaggle reported that Python overtook R, in 2016
  • The average annual salary of a data scientist at a mid-career, in India, is around INR 815,668, according to PayScale.
  • According to Quanthub, in 2020, there are three times as many job listings in data science as job searches for the same.

 

The above facts reveal how widely Python is used by Data Scientists across the globe. With the increasing development in the Python ecosystem, this trend is anticipated to grow in the coming years. 

 

Also, it emphasizes the fact that the demand for data scientists is tremendously outstripping the supply. Eventually, there is a surge in the candidates looking for a Data Science with Python course for making themselves eligible for the positions in Data Science and having a career in this ever-growing field. 

Python Overview

Let’s see how the producers of python define it.

“Python is an interpreted, object-oriented, high-level programming language with dynamic semantics, it’s 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.”

 

Python is a general-purpose programming language which means that you can use it for the development of both web and desktop applications. You can also use it in the development of scientific and complex numeric applications. This shows how versatile Python is, and thus it is considered to be one of the fastest-growing programming languages.

 

Being a multi-purpose language, Python is widely used in Data science as well. Data Scientist is termed as the hottest job of this century. One thing to remember is that expertise in Python can let you learn Data Science from scratch.

Data Science Overview

Data Science is an interdisciplinary field that involves using scientific methods, processes, systems, and algorithms in order to extract meaningful information and insights from structured or unstructured data. Data Science is primarily used for making decisions and predictions by utilizing three techniques namely predictive casual analytics, prescriptive analytics, and machine learning.


Why is Python Preferred over Other Tools for Data Science?

Across the industries, Python is referred to as one of the most used tools by data scientists. Python can be an ideal choice for data scientists when you need to incorporate statistical code into production databases or when you are required to integrate the data with web-based applications. 

 

Some of the packages of Python are specifically tailored for certain functions which include pandas, NumPy, and SciPy. As a Data Scientist, when you need to work on various machine learning tasks, you can find scikit-learn a valuable tool. When you require graphics and other visuals in your project, Matplotlib is an excellent package available. 

 

The features of Python that make it the most favorites of a Data scientist are:

  • It is easier for programmers to read as its syntaxes are elegant and easy.
  • There is a substantial standard library and community support.
  • It is an expressive language that can be embedded into applications to make an interface for programming.
  • Python in its interactive mode makes it simple to test codes.
  • It allows you to run the code anywhere, including Windows, Linux, UNIX, and Mac OS X.
  • In some of the categories, it is free to use.

Most Commonly used Python Libraries for Data Science

As mentioned earlier, some of the libraries of Python are specifically designed for use in Data Science. They are:


NumPy

NumPy stands for Numerical Python. It provides mathematical functions to handle large dimensional arrays. It also provides functions for Metrics, Linear Algebra, and Arrays. It facilitates vectorization of operations on the NumPy array type that improves performance and speeds up the execution. NumPy makes it easy to work with huge multidimensional arrays and matrices.

Matplotlib

It is a Python library that is useful in Data Visualization. Data visualization and descriptive analysis are very important for most organizations. Matplotlib is a library that provides you with various methods to visualize data effectively. It allows the quick formation of line graphs, pie charts, and other professional figures. 

You can customize every aspect of the figure using Matplotlib.

Pandas

One of the most popular libraries in Python, used for data manipulation and analysis is Pandas. It provides functions for the manipulation of a large amount of structured data. For analysis purposes, it provides the easiest methods. It provides perfect tools for data wrangling. The two data structures in Pandas are Series and DataFrame for handling and storage of one-dimensional and two-dimensional data respectively.

SciPy

As the name suggests, it is a Python library for data science when scientific computing is required. It contains sub-modules for optimization, integration, linear algebra, interpolation, signal and image processing, FFT, ODE solvers, Statmodel, and other common functions in science and engineering. 

Scikit-learn

It is a famous Python library for machine learning. It provides different algorithms and functions to be used in machine learning. It is built on NumPy, Matplotlib, and SciPy. It provides you with very simple tools for data analysis and data mining. Scikit-learn helps to deploy popular algorithms on huge datasets and solve real-world problems. 

 

You can see that there are so many libraries in Python that make it the most preferred language for Data Science.

Bottom Line

Data Science is referred to as the ‘sexiest-job’ by data scientists and analysts. Today Python is becoming an increasingly necessary skill for many data science positions. To enhance your career in this domain, you can take up an online training course in Python for Data Science. 

 

There are many benefits of going through these bootcamps. You can learn at your own pace and that too in your own choice of mode of learning. It may be a blended learning approach, instructor-led, or online training. Get yourself registered now to make your career skyrocket in Data Science.

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