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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 ...

5 Top R Vs SAS Differences

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Statistical analysis should know by every software engineer. R is an open source statistical programming language. SAS is licensed analysis suite for statistics. The two are very much popular in Machine learning and data analytics projects. SAS is an Analysis-suite software and R is a programming language. 1. R Language R supports both statistical analysis and Graphics R is an open source project. R is 18th most popular Language R packages are written in C, C++, Java, Python and.Net R is popular in Machine learning, data mining and Statistical analysis projects. a). R Advantages R is flexible since a lot of packages are available. R is best suited for data related projects and  Machine learning . Less cost since it is open source language. R Studio is the best tool to develop R programming modules. Ref: imartcus.org (read more advantages) b). R Disadvantages R language architecture model is out of date. So may not use it for critical applications. R is not suitable for S...