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SQL Query: 3 Methods for Calculating Cumulative SUM

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SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences. Using Window Functions (e.g., PostgreSQL, SQL Server, Oracle) SELECT id, value, SUM(value) OVER (ORDER BY id) AS cumulative_sum  FROM your_table; This query uses the SUM() window function with the OVER clause to calculate the cumulative sum of the value column ordered by the id column. Using Subqueries (e.g., MySQL, SQLite): SELECT t1.id, t1.value, SUM(t2.value) AS cumulative_sum FROM your_table t1 JOIN your_table t2 ON t1.id >= t2.id GROUP BY t1.id, t1.value ORDER BY t1.id; This query uses a self-join to calculate the cumulative sum. It joins the table with itself, matching rows where the id in the first table is greater than or

Python Set comprehension - How to Use it Read now

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In python, Set does not allow duplicates, and  you can't modify an existing set with a comprehension. But using the Set comprehension you can create a new Set. Set Comprehension  In addition, the comprehension must result in a valid set.  Likewise Dictionary, a set does not allow entries of the same value. If you try to add values to the set that are already there, it will replace the old one with the new one. Explained syntax Set comprehensions using the {} syntax only exist in Python 3. Before that, you'll have to use the set() function to create and work with sets. You might guess, therefore, that one of the best uses of a set is to eliminate duplicates. In fact, this is one of the most basic forms of set comprehension. Given a list, we can duplicate it as a list with a simple list comprehension like this: Details of logic if we change the list comprehension to a set comprehension, we get the same result, but as a set. That means without duplicates. list_copy = [x for x in o