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Python map() and lambda() Use Cases and Examples

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 In Python, map() and lambda functions are often used together for functional programming. Here are some examples to illustrate how they work. Python map and lambda top use cases 1. Using map() with lambda The map() function applies a given function to all items in an iterable (like a list) and returns a map object (which can be converted to a list). Example: Doubling Numbers numbers = [ 1 , 2 , 3 , 4 , 5 ] doubled = list ( map ( lambda x: x * 2 , numbers)) print (doubled) # Output: [2, 4, 6, 8, 10] 2. Using map() to Convert Data Types Example: Converting Strings to Integers string_numbers = [ "1" , "2" , "3" , "4" , "5" ] integers = list ( map ( lambda x: int (x), string_numbers)) print (integers) # Output: [1, 2, 3, 4, 5] 3. Using map() with Multiple Iterables You can also use map() with more than one iterable. The lambda function can take multiple arguments. Example: Adding Two Lists Element-wise list1 = [ 1 , 2 , 3 ]

These are energy analytics top areas to focus

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Energy Analytics is a new area started recently. The below are the key points in analytics. According to Siemens, Outsource your energy data management as a service and benefit from regular analyses performed by our energy experts. Evaluations show that this service makes it possible to easily achieve savings potential of as much as 5 percent. Headlines of energy analytics Market Forecast: Energy Data & Analytics Energy Data Management & Analytics Business Skills Big Data in an Utilities Environment: Real Case Studies Advantages of Big Data & Analytics: Smart Metering & Cloud Computing Innovative Solutions & Technologies Data Analytics in a Smart Grid Perspective - DONG Energy Case Study Big Data in the TSO Business Achieving Benefits From Smart Meters Deployment With Advanced Analytics - Return on Experience From Large Scale Deployments in the US Smart Grid Cybersecurity, Frameworks and Standards Adopting Open Source Software in Energy Anal