Category "sum"

Given a sequence of integers, return the sum of all the integers that have an even index, multiplied by the integer at the last index

This is my solution and it passes some of the tests, but not all of them. Can anyone help me and explain why? Thank you :) function evenLast(numbers) { let su

Sum array values

I’m making a shipping service app to Shopify and my callback URL have this JSON post using json_decode to make an array. The value I want to sum is grams

Sum in a index/match formula

Could you help me solve the following? I want to return the total sum, not the first match that it finds. My first preference is have indexing and matching wi

Sum in a index/match formula

Could you help me solve the following? I want to return the total sum, not the first match that it finds. My first preference is have indexing and matching wi

How to sum multiple hour : mins in sql?

i need to sum this varchar values. time 1 = '13:06' time 2 = '18:59' time 3 = '14:49' i tryed this. SELECT convert( char(8), dateadd( secon

Retrieve row where sum of column is greater than other column of different table

I have two database tables. First table: | ID | Sub-Name | Marks | 01 | french | 50 | 01 | russian | 50 | 02 | french | 30 | 02 | russian

Sum function with return type large enough to hold result

It's a question from C++ Primer Chapter 16.2.3 (question 16.41): Write a version of sum with a return type that is guaranteed to be large enough to hold t

Fibonacci Numbers - Add odd numbers only - Javascript

So I am trying to develop a formula that will sum all odd Fibonacci numbers up to and including a given number. For example: Given number is 4. Then result sh

How to sum the numbers(Int16) of stored core data - Swift 3

I have stored the letters(String), numbers(Int16) and Date(Date) in the core data. And the filter(NSPredicate) succeeded in organizing only the necessary data.

Pandas: sum DataFrame rows for given columns

I have the following DataFrame: In [1]: df = pd.DataFrame({'a': [1, 2, 3], 'b': [2, 3, 4], 'c': ['dd', 'ee', 'ff'],