javascript: get the maximum, average and minimum value in JSON of an array with objects

I have the following JSON:

```{ "funcionarios":( { "id":0, "nome":"Marcelo", "sobrenome":"Silva", "salario":3200.00, "area":"SM" }, { "id":1, "nome":"Washington", "sobrenome":"Ramos", "salario":2700.00, "area":"UD" }, { "id":2, "nome":"Sergio", "sobrenome":"Pinheiro", "salario":2450.00, "area":"SD" }, { "id":3, "nome":"Bernardo", "sobrenome":"Costa", "salario":3700.00, "area":"SM" }, { "id":4, "nome":"Cleverton", "sobrenome":"Farias", "salario":2750.00, "area":"SD" } }```

To obtain the minimum and maximum salary I used the following function:

``````function sortByAttribute(arr, attribute) {
return arr.sort(function(a, b){
return a(attribute) - b(attribute);
});
``````

Where I then keep the return of the function in a matrix and delete the first index as the lowest salary and the last index as the highest salary. But now I need to average wages, how can I do that? I have no idea.

graphics – Minimum weight vertex cover for directionally weighted bigraphs

I have a graph $$G = (V, E)$$ such that for each edge $$(u, v) in E$$ there is a corresponding edge in the reverse direction $$(v, u) in E$$ so that in fact $$G$$ It is "bi-connected." In addition, the weights are such that $$w (u, v)$$ not necessarily equal to $$w (v, u)$$.

Question 1: Is there a known name for this type of chart?

Perhaps it can be reduced to the problem of weighted vertex coverage "individually" …

Question 2: Would an algorithm for finding the minimum weight vertex coverage be significantly different than for regular (bi-connected) weighted graphs (individually)?

Question 3: Would an approximation algorithm for this graph be different?

Probability: What is the minimum expected distance from Hamming?

If i try $$N$$ binary length chains $$n$$ evenly and independently, in principle I can find the closest Hamming distance between any pair. What is the expected value for this minimum?

If this is difficult to calculate exactly, is it possible to give a good approximation for large $$N gg n$$?

I see this question closely related but with $$N = n$$.

optimization: cover of vertex of minimum weight in \$ G \$ connected with cycles of maximum length \$ 3 \$

Leave $$G = (V, E)$$ be a non-directed weight chart $$w: V rightarrow (0, infty)$$. We want to find an algorithm that finds a vertex cover (that is, a set of vertices so that each edge contains an element of that set)
$$U$$ from $$G$$ minimizing the amount $$w (U) = sum_ {u in U} w (u)$$ Dice
every single cycle in $$G$$ It has a length of at most $$3$$.

We are supposed to use the following fact: given an expansion tree $$T$$ from $$G$$, for all $$uv in E$$, the length of the road in $$T$$ since $$u$$ to $$v$$ it is $$1$$ or $$2$$.

I thought about using a more sophisticated version of the well-known greedy algorithm that finds a vertex cover for a tree without weights (in each iteration, find a leaf and eliminate its father, including all his children, marking the father). However, I could not generalize the underlying principles.

Do you want a prediction about what will happen the next time you raise the minimum wage?

Marked as a favorite, because you are wrong. The payroll is not even close to Arby's biggest expense, it is the commercialization, followed by research and development in cloned soy that vaguely tastes like beef broth, then executive compensation, litigation expenses, insurance premiums, facility maintenance, equipment, and then muuuuuuuuuuuuuuuuuy … the hourly rate for drones, finally followed by ingredient costs.

Anyway, any business that operates with a margin as small as you imagine is a sneeze from bankruptcy.

Maximum and minimum value on disk (NO TIP)

Find the maximum and minimum values ​​of $$f (x, y) = 5x ^ 2 + 6y ^ 2$$ On the disk $$D: x ^ 2 + y ^ 2≤1.$$ (WITHOUT USING LAGRANDE)

How would you ask this question without using LAGRANDE?

Algorithm analysis: How to compare n number of m-dimensional points to each other with a minimum time complexity?

Suppose there are four points (n = 4) that are four dimensions (m = 4). Let's say these points are: A (4,1,1,1), B (3,2,1,1), C (2,3,3,3), D (1,4,4,4). What is the best data structure to compare all points with each other based on their values ​​in the corresponding dimensions? The objective is to have a minimum time complexity. (Practically n >> m).

minimum and maximum word count wordpress post plugin

How to set the minimum and maximum word count in WordPress publication using any code or add-on
Can you suggest