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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 and the value in a loop, enumerate is a more Pyth

Ideas: How Bigadata Helps HR Teams


Big Data is the buzzword of the year. Every leader — whether they’re managing a small team or are at the helm of a multinational corporation with thousands of employees — is wondering how they can use Big Data to better get to know their people, to create a setting that better suits their needs and, in turn, drive recruitment and retention.

As co-authors of The Decoded Company: Know Your Talent Better Than You Know Your Customers, we’ve spent a lot of time thinking about this exact topic. Here are the top five trends you should be thinking about.

  1.  We are living in a data-abundant environment, and it’s changing everything. Gary Hamel, one of the world’s leading thinkers on the topic of management, has written extensively on the topic of the technology of leadership (or what he more accurately calls the technology of human accomplishment).
  2. He believes — and we tend to agree — that this might be the most important technology humanity has ever created. It gives us extraordinary superpowers to organize people into achieving feats that would be otherwise impossible, particularly from an economic perspective. Consider, for example, that Apple has achieved a market cap of $468.99B with 80,300 full-time employees (from its 2013 Annual report), or almost $6m per head.
  3. The challenge is that the management tools we use every day were designed around the assumption that data is expensive to gather and therefore infrequently available. Today’s reality is very different.
  4. Data is abundant and incredibly cheap to gather, store, process, and analyze. This epic shift has led to radically different business models on one hand, but only incremental management philosophy tinkering on the other.
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