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15 Python Tips : How to Write Code Effectively

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 Here are some Python tips to keep in mind that will help you write clean, efficient, and bug-free code.     Python Tips for Effective Coding 1. Code Readability and PEP 8  Always aim for clean and readable code by following PEP 8 guidelines.  Use meaningful variable names, avoid excessively long lines (stick to 79 characters), and organize imports properly. 2. Use List Comprehensions List comprehensions are concise and often faster than regular for-loops. Example: squares = [x**2 for x in range(10)] instead of creating an empty list and appending each square value. 3. Take Advantage of Python’s Built-in Libraries  Libraries like itertools, collections, math, and datetime provide powerful functions and data structures that can simplify your code.   For example, collections.Counter can quickly count elements in a list, and itertools.chain can flatten nested lists. 4. Use enumerate Instead of Range     When you need both the index ...
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Data Analytics Tutorial for COBOL Programmers

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Mainframe developers look for an alternative IT course to grow in their careers. I have explained in this post how can they use their business knowledge. Data analytics tutorial is a top an alternative for COBOL programmers.

analytics tutorial for COBOL developers

What is Data Analytics

The field of data science is evolving into one of the fastest-growing and most in-demand fields in the world. 

Organizations across industries are looking to make sense of the data they can now collect from new technologies – from predicting the next hot product to determining the risk of an infectious disease outbreak.

Demand and Opportunity

  • According to The New York Times, data science “promises to revolutionize industries from business to government, health care to academia.”
  • As data accumulates, organizations are hiring individuals with the expertise to find meaning in the numbers and drive positive business decisions based on what they learn.
  • It is estimated that by 2018, 4 million to 5 million jobs in the United States will require data analysis skills, and a recent study from the McKinsey Global Institute found “a shortage of the analytical and managerial talent necessary to make the most of Big Data is a significant and pressing challenge (for the U.S.).”
  • Based on the number of job openings, median base salary and career opportunities, Glassdoor has ranked data scientist as the “Best Job in America”.

Who can opt for Data Analytics Tutorial

  1. Strong interest in data science 
  2. Background in intro level statistics 
  3. Programming experience in Python for Data Science 
  4. Understanding of programming concepts such as variables, functions, loops, and basic python data structures like lists and dictionaries
Start Your Free Data analytics Tutorial here.

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