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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 ]

Tableau, JMP, Advizor, and Spot-fire - Visualization Tools

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We are in a Bigdata world. Data presentation is very critical now a days. Data is generating from multiple sources. What is data visualization? Visualization tools have evolved so far that many people don’t realize the capabilities that exist. Tools like Tableau, JMP, Advizor, and Spot-fire help analytic professionals and business users move beyond graphics that simply illustrate a story that has already been developed. Visualization tools Visualization tools enable the analytic professional or business user to develop a new story in an interactive, visual paradigm. Today’s visualization tools allow multiple tabs of graphs and charts to be linked to the underlying data. Even more important, the tabs, graphs, and charts can be linked to each other. If a user clicks on the bar for the Northeast region, all the other graphs will instantaneously adjust and show only Northeast data as well. Also Read | The all about Tibco Spotfire reporting These new tools might be thought of