#### Category : max

I am trying to find the list in nested list, which has the maximum number of highest numbers, as shown bellow: test_list = [[200,1,100],[50,120,0],[40,300,0]] desired output = [200,1,100] [200,1,100] is the winner here, as out of its 3 digits, 2 are higher than the other lists 2 numbers. This would not be sequence sensitive however, ..

I need to find the maximum x value in Python of this function that I write through the code: import numpy as np y=np.abs(-np.exp(-x/1068)+np.exp(-x/46)) If I use this: print(max(np.abs(-np.exp(-x/1068)+np.exp(-x/46)))) It prints only the maximum y value. How can I do to have also the maximum x value ? Source: Python..

I have a DataFrame like this: abc def ghi 0 2.3 2.2 3.6 1 3.5 4.0 2.6 2 1.8 2.4 2.5 and I calculte the max of each rows with this code: df_final[‘max_value’] = df_final[[‘abc’, ‘def’, ‘ghi’] max_value 0 3.6 1 4.0 2 2.5 Is there any option to get the column name of each ..

As the code below, I know how to get the item that maximize a function from a list, but I also want to get the maximized value together with the item. In reality I have a very computationally expensive function so I don’t want to run the function again. Here I just use a sigmoid ..

I want to return the max value of a matrix. For example this is my matrix: matrix = [[0, 1, 10, 0, 0], [0, 0, 6, 0, 1], [0, 1, 4, 0, 0]] I want to return the max so here ’10’ This is my code but I have an error: max = 0 for ..

I need to take the difference between revenue and cost and display the top 2 revenue with the whole row displayed. For example here is a text file: Mazda 64333 53333 Merce 74321 54322 BMW 52211 31432 The expected output would be Merce 74321 54322 BMW 52211 31432 Please use simple code. Thank you ðŸ™‚ ..

I would like to find the max in columns in pairs of two I have the following columns: user_id’, ‘fullname’, ’email’, ‘handle’, ‘audience_ethnicities_code0’, ‘audience_ethnicities_weight0’, ‘audience_ethnicities_code1’, ‘audience_ethnicities_weight1’, ‘audience_ethnicities_code2’, ‘audience_ethnicities_weight2’, ‘audience_ethnicities_code3’, ‘audience_ethnicities_weight3′ where code and weigh are related, for example: ==> user_id = ABCD ‘audience_ethnicities_code0’ = asian; ‘audience_ethnicities_weight0’ = 0.4 ‘audience_ethnicities_code1’ = african; ‘audience_ethnicities_weight1’ = 0.2 ‘audience_ethnicities_code2’ ..