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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 ]

3 SQL Query Examples to Create Views Quickly

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There are three kinds of Views in SQL. The three views are Read-only, Force, and Updatable. Views real usage is to hide data. And you need to ensure base tables are present before you create a View. You can call views as logical tables. The advantage of Views is you can show only some of the fields of base tables. What is a View in SQL A view can be constructed with another view so it is called a nested view. You can create or replace an existing view A view can be created without having base tables. This is possible with the FORCE option. #1: Read-Only Views The standard syntax for the view is as follows: CREATE OR replace VIEW invoice_summary AS SELECT vendor_name count(*) AS invoice_count, SUM(invoice_total) AS invoice_total_sum FROM vendor JOIN invoices ON vendors.vendor_id*invoices.vendor_id GROUP BY vendor_name; Notes: You cannot update Read-only Views #2: Force Views CREATE FORCE VIEW products_list AS SELECT product_description, product_price FROM products;