Imagine following dataframe is given. I have columns products, custome_demand_date (every week there is new customer demand for products per upcoming months) and months with quantity demand. How can I determine which product has experienced the most frequent changes in customer demand over the months, and sort the products in descending order of frequency of change? I have tried to

# Tag: sorting

## Sorting lists with multiple tie breakers

I have data in an array like so: I want to sort it by the amount of non-10 values, and I also want to sort it in ascending order for rows, and in descending order of number of 10s: Output: I want to implement a tie breaker system so that if the amount of 10s the same, it now orders

## Sort one inside another

I have a class Person that contains names and hobbies. Then there’s a list that contains people. person1 = Person(“MarySmith”, [“dancing”, “biking”, “cooking”]) person2 = … people = [person1, person2,..] I need to return a list of people sorted alphabetically by their name, and also sort their list of hobbies alphabetically. This is what I have so far: This is

## Combine and sort multiple array columns of values A and B where A is the common index

I have a n-long list of arrays. Each array consists of two columns: A) index values between 1-500 B) measured values Each A column is slightly different (i.e. missing or having extra values). I want to create single large array where i) there is single A (index) column consisting of all the index values and ii) all the B (measured

## converting a tree array to a specific string (chemical formulas) (py)

I have a specific kind of array which looks often like this: and I want to convert it to something like Ca3(PO4)2. Could someone help me? I tried a lot of techniques, but the code gets always really messy. I do not know what am i doing wrong. I use python by the way. P.S.: if anything’s wrong, tell me

## Can I sort two related arrays in parallel using python?

I have two NumPy arrays with the shape (74395, 1) storing float values where arr1[0] correlates to arr2[0] and so on. I would like to sort them together in ascending order by the values stored in the second array. As an example: wanted result: How could I do that in python? Answer Use numpy.argsort with numpy.take_along_axis: Output:

## Combine two lists and sort them

Lets say I have two lists. I want to append list2 into list1 and then sort and add a new element at a specific index. I keep getting an error message saying: TypeError: ‘<‘ not supported between instances of ‘list’ and ‘int’ This is what I have tried: Answer Use sorted() if you want to print sorted list:

## Sorting list based on dictionary keys in python

Is there a short way to sort a list based on the order of another dictionary keys? suppose I have: I want to sort the list to be [‘a’,’b’,’c’] based on the order of dic keys. Answer You can create a lookup of keys versus their insertion order in dic. To do so you can write: Using this you can

## What is the time complexity of a bubble sort algorithm applied n times to the same array?

I had this question on a test and i’m trying to understand it: What is the time complexity of this function (in the worst case) assuming that Bubblesort() is the most optimized version of the Bubble Sort algorithm? The options were: Linear Quadratic Cubic I was thinking that the first sort (because it’s the worst case) would be O(len(a)^2) and

## Kth Smallest Element in multiple sorted arrays

Let’s say we have two arrays: array1 = [2,3,6,7,9] array2 = [1,4,8,10] I understood how to find the kth element of two sorted arrays in log(min(m,n)) where m is the length of array1 and n is the length of array2 as follows: But I couldn’t figure out how to extend this to multiple sorted arrays case. For example, given 3