给定一个整数列表,我想找到哪个数字最接近我输入的数字:

>>> myList = [4, 1, 88, 44, 3]
>>> myNumber = 5
>>> takeClosest(myList, myNumber)
...
4

有什么快速的方法吗?


当前回答

遍历列表并将当前最接近的数字与abs(currentNumber - myNumber)进行比较:

def takeClosest(myList, myNumber):
    closest = myList[0]
    for i in range(1, len(myList)):
        if abs(i - myNumber) < closest:
            closest = i
    return closest

其他回答

如果我可以补充@Lauritz的回答

为了不出现运行错误 不要忘记在bisect_left行之前添加一个条件:

if (myNumber > myList[-1] or myNumber < myList[0]):
    return False

所以完整的代码看起来像这样:

from bisect import bisect_left

def takeClosest(myList, myNumber):
    """
    Assumes myList is sorted. Returns closest value to myNumber.
    If two numbers are equally close, return the smallest number.
    If number is outside of min or max return False
    """
    if (myNumber > myList[-1] or myNumber < myList[0]):
        return False
    pos = bisect_left(myList, myNumber)
    if pos == 0:
            return myList[0]
    if pos == len(myList):
            return myList[-1]
    before = myList[pos - 1]
    after = myList[pos]
    if after - myNumber < myNumber - before:
       return after
    else:
       return before
def closest(list, Number):
    aux = []
    for valor in list:
        aux.append(abs(Number-valor))

    return aux.index(min(aux))

这段代码将为您提供列表中与number最接近的数字的索引。

KennyTM给出的解决方案是最好的,但在您不能使用它的情况下(如brython),这个函数将完成工作

def find_nearest(array, value):
    array = np.asarray(array)
    idx = (np.abs(array - value)).argmin()
    return array[idx]

通过使用

price_near_to=find_nearest(df['Close'], df['Close'][-2])

遍历列表并将当前最接近的数字与abs(currentNumber - myNumber)进行比较:

def takeClosest(myList, myNumber):
    closest = myList[0]
    for i in range(1, len(myList)):
        if abs(i - myNumber) < closest:
            closest = i
    return closest
def takeClosest(myList, myNumber):
    newlst = []
    for i in myList:
        newlst.append(i - myNumber)
    lstt = [abs(ele) for ele in newlst]
    print(myList[lstt.index(min(lstt))])

myList = [4, 1, 88, 44, 3]
myNumber = 5
takeClosest(myList,myNumber)