Preface
#The median is a value that divides a set of values into equal upper and lower parts. If the number of list data is an odd number, the data in the middle of the list is the median of the list data; if the number of list data is an even number, the arithmetic mean of the two data in the middle of the list is the median of the list data. In this task, you will be given a non-empty array (X) containing natural numbers. You have to split it into upper and lower parts and find the median.
Input: A list of integers (int) as an array.
Output: median of array (int, float).
Example
get_median([1, 2, 3, 4, 5]) == 3 get_median([3, 1, 2, 5, 3]) == 3 get_median([1, 300, 2, 200, 1]) == 2 get_median([3, 6, 20, 99, 10, 15]) == 12.5
#How to use: The median is used in probability theory and statistics. It has skewed distribution Remarkable value. For example: We want to know the average wealth of people from a set of data - 100 people earn $100 a month, and 10 people earn $1,000,000 a month. If we calculate the average, we get $91,000. This is a strange value that doesn't show us what's really going on at all. So in this case, the median will give us more useful values and better description.
Premise:<strong> </strong>1 < len(data) ≤ 1000 all(0 ≤ x < 10 ** 6 for x in data)
Common method:
Sort the list and calculate the median according to whether the list length is an odd number or an even number.
def get_median(data): data = sorted(data) size = len(data) if size % 2 == 0: # 判断列表长度为偶数 median = (data[size//2]+data[size//2-1])/2 data[0] = median if size % 2 == 1: # 判断列表长度为奇数 median = data[(size-1)//2] data[0] = median return data[0]
Best method:
This solution is very clever, it uses Take the property that the sum of the inverses is 1, and get the median of the list through the negative index of the list.
Explanation of return (data[half] + data[~half]) / 2
:
Get the sequence after sorting [1,2,3,4,5,6], the list length is an even number, and the median is determined by the two middle elements of the list, 3 (index 2) and 4 (index 3). The negative index of element 4 is -3, which is exactly the inverse of index 2.
After sorting, the sequence [1,2,3,4,5] is obtained. The length of the list is an odd number, and the median is determined by the middle element 3 of the list (index is 2, negative index is -3). Still compliant with code.
def get_median(data): data.sort() half = len(data) // 2 return (data[half] + data[~half]) / 2
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