Data Science with Python

Data Science with Python: Introduction 

Welcome to this series of articles on “Data Science with Python. “In this series, we will learn and explore Data Science with Python programming language. 

Data is the gold of today’s digital world, and it is available in various forms. With the massive amounts of information produced these days, data science’s popularity has grown. As a result, the companies have started implementing data science techniques to grow their business with high Return On Investment(ROI) and superb client satisfaction.  

Before going deep, let’s learn the basics of Python and Data Science.   

Table of Contents

  1. Introduction to Data Science
    • Data Scientist’s Skills
  2. Introduction to Python 
    • Why learn Python for Data Science?
  3. System Setup for Data Science with Python
  4. End Notes

Introduction to Data Science

Data Science deals with massive volumes of data using several tools, algorithms, and techniques to search out the hidden patterns in the data and derive meaningful insights to build businesses. The data used for analysis can come from many different sources and are available in various formats. With Data Science’s assistance, data information can be derived quickly and represented beautifully.  

Data Scientist’s Skills

Data Scientist's Skills

Image: Data Scientist’s Skills

Three sets of skills are required to become a data scientist.

  1. Computer Science

    Programming skills and database knowledge come under the computer science skill set. The programming language can be Python, or R. SQL is a widely used query language for databases in data science.

  2. Mathematics and Statistics

    Data Scientists need to learn all mathematics basics like linear algebra, matrix, probability, and statistics.

  3. Domain expertise

    Data Science is implemented in many verticals. Therefore, knowledge of these verticals is required to take out the best in data science.

If you want to become a Data Scientist, click here to know the complete skill set required.

Introduction to Python

Image Source

Python is the most used language for data science and an established language for general computing and scientific computing. A lot over it, it’s being continuously upgraded in the form of a new addition to its libraries aimed toward different programming needs. So let’s write a simple program in Python.

# This program prints Hello, world !!
print(“Hello, World !!”OUTPUT>>Hello, World !!

In this simple code snipping, we can understand how easy it is to use and learn Python. 

Why learn Python for Data Science?

Several other languages are also available to process data and learn from data science. Still, Python is the most used programming language for Data Science. Learn Python for data science because-

  • Python is simple to learn and code and can smoothly handle highly complicated mathematical processes. 
  • Python fits very well in all needs for Data Science.
  • Python is used extensively in the industry.
  • Python is platform-free, which means that the same code Python will run in different environments.  
  • Python offers the best packages for Data Science and Artificial Intelligence like Numpy, Pandas, SciPy, Matplotlib, sci-kit-learn, and TensorFlow for deep learning.
  • For interactive data analysis and modeling, iPython notebooks are available.

System Setup for Data Science with Python

We need to set up an environment for Data Science with Python to learn and explore more.

Anaconda is the leading open platform for data science powered by Python. Download and install Anaconda using the link per your system requirement(Windows, macOS, or Linux).

Python 3.6 works very well with Anaconda. Install Python as per system requirements using the link or install Python3.6 using the conda command from the command prompt window.

conda install python=3.6

Note: Set’ PATH environment variable’ for Anaconda.

After a successful setup, open the Jupyter Notebook and enjoy Python programming with lots of data.

End Notes

This article discussed Data Science and Python, with steps to set up its environment. In the following article, we will dive into data science with Python. So, get your system ready before reaching the next piece to have hands-on experience.

Stay Tuned!!

Keep learning and keep implementing!!

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