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g1001_1100.s1093_statistics_from_a_large_sample.readme.md Maven / Gradle / Ivy

1093\. Statistics from a Large Sample

Medium

You are given a large sample of integers in the range `[0, 255]`. Since the sample is so large, it is represented by an array `count` where `count[k]` is the **number of times** that `k` appears in the sample.

Calculate the following statistics:

*   `minimum`: The minimum element in the sample.
*   `maximum`: The maximum element in the sample.
*   `mean`: The average of the sample, calculated as the total sum of all elements divided by the total number of elements.
*   `median`:
    *   If the sample has an odd number of elements, then the `median` is the middle element once the sample is sorted.
    *   If the sample has an even number of elements, then the `median` is the average of the two middle elements once the sample is sorted.
*   `mode`: The number that appears the most in the sample. It is guaranteed to be **unique**.

Return _the statistics of the sample as an array of floating-point numbers_ `[minimum, maximum, mean, median, mode]`_. Answers within_ 10-5 _of the actual answer will be accepted._

**Example 1:**

**Input:** count = [0,1,3,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]

**Output:** [1.00000,3.00000,2.37500,2.50000,3.00000]

**Explanation:** The sample represented by count is [1,2,2,2,3,3,3,3].

The minimum and maximum are 1 and 3 respectively.

The mean is (1+2+2+2+3+3+3+3) / 8 = 19 / 8 = 2.375.

Since the size of the sample is even, the median is the average of the two middle elements 2 and 3, which is 2.5.

The mode is 3 as it appears the most in the sample.

**Example 2:**

**Input:** count = [0,4,3,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]

**Output:** [1.00000,4.00000,2.18182,2.00000,1.00000]

**Explanation:** The sample represented by count is [1,1,1,1,2,2,2,3,3,4,4].

The minimum and maximum are 1 and 4 respectively.

The mean is (1+1+1+1+2+2+2+3+3+4+4) / 11 = 24 / 11 = 2.18181818... (for display purposes, the output shows the rounded number 2.18182).

Since the size of the sample is odd, the median is the middle element 2.

The mode is 1 as it appears the most in the sample.

**Constraints:**

*   `count.length == 256`
*   0 <= count[i] <= 109
*   1 <= sum(count) <= 109
*   The mode of the sample that `count` represents is **unique**.