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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 Dictionary Vs List With Examples

Dictionary and List we use interchangeably in Python to store values. For beginners, both look the same. In reality, they both differ. Here are the differences.

Dictionary Vs Lists


Values in lists are accessed by means of integers called indices, which indicate where in the list a given value is found.

Dictionaries access values by means of integers, strings, or other Python objects called keys, which indicate where in the dictionary a given value is found. 

In other words, both lists and dictionaries provide indexed access to arbitrary values, but the set of items that can be used as dictionary indices is much larger than, and contains, the set of items that can be used as list indices.
 
Also, the mechanism that dictionaries use to provide indexed access is quite different from that used by lists. Both lists and dictionaries can store objects of any type.

Values stored in a list are implicitly ordered by their positions in the list because the indices that access these values are consecutive integers. You may or may not care about this ordering, but you can use it if desired.
 
Values stored in a dictionary are not implicitly ordered relative to one another because dictionary keys aren’t just numbers. 

Note that if you’re using a dictionary but also care about the order of the items (the order in which they were added, that is), you can use an ordered dictionary, which is a dictionary subclass that can be imported from the collections module.


You can also define an order on the items in a dictionary by using another data structure (often a list) to store such an ordering explicitly; this won’t change the fact that basic dictionaries have no implicit (built-in) ordering.


Python Dictionary Vs List With Examples


How to use list and dictionary


In spite of the differences between them, the use of dictionaries and lists often appears to be the same.
As a start, an empty dictionary is created much like an empty list, but with curly braces instead of square brackets:

>>> x = []
>>> y = {}

Here, the first line creates a new, empty list and assigns it to x. The second line creates a new, empty dictionary and assigns it to y.

How to Assign Values Dictionary and List.


After you create a dictionary, you may store values in it as though it were a list:

>>> y[0] = 'Hello'
>>> y[1] = 'Goodbye'

Even in these assignments, there’s already a significant operational difference between the dictionary and list usage.


Trying to do the same thing with a list would result in an error because, in Python, it’s illegal to assign to a position in a list that doesn’t exist. For example, if you try to assign to the 0th element of the list x, you receive an error:

>>> x[0] = 'Hello'
Traceback (innermost last):
  File "<stdin>", line 1, in ?
IndexError: list assignment index out of range


This isn’t a problem with dictionaries; new positions in dictionaries are created as necessary. Having stored some values in the dictionary, now you can access and use them:

>>> print(y[0])
Hello

>>> y[1] + ", Friend."
'Goodbye, Friend.'

All in all, this makes a dictionary look pretty much like a list. Now for the big difference. Store (and use) some values under keys that aren’t integers:

>>> y["two"] = 2
>>> y["pi"] = 3.14
>>> y["two"] * y["pi"]

This is definitely something that can’t be done with lists! Whereas list indices must be integers, dictionary keys are much less restricted; they may be numbers, strings, or one of a wide range of other Python objects.


References.

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