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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 ]

Top IT Skills 2015

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IT spending for security technologies will increase 46% in 2015, with cloud computing increasing 42% and business analytics investments up 38%. Enterprise investments in storage will increase 36%, and for wireless and mobile, 35%. IT spending for security technologies will increase 46% in 2015, with cloud computing increasing 42% and business analytics investments up 38%. Cloud computing initiatives are the most important project for the majority of IT departments today (16%) and are expected to cause the most disruption in the future. IDG predicts the majority of cloud computing’s disruption will be focused on improving service and generating new revenue streams. These and other key take-aways are from recent IDG Enterprise research titled Computerworld Forecast Study 2015. The goal of the study was to determine IT priorities for 2015 in areas such as spending, staffing and technology.  Computerworld spoke with 194 respondents, 55% of which are from the executive IT roles. 1