Python 在嵌套列表的第二列中查找最大值？
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Finding max value in the second column of a nested list?
提问by davelupt
I have a list like this:
我有一个这样的清单：
alkaline_earth_values = [['beryllium', 4], ['magnesium', 12],['calcium', 20],
['strontium', 38], ['barium', 56], ['radium', 88]]
If I simply use the max(list)method, it will return the answer 'strontium', which would be correct if I was trying to find the max name, however I'm trying to return the element whose integer is highest.
如果我只是使用该max(list)方法，它将返回 answer 'strontium'，如果我试图找到 max name，这将是正确的，但是我试图返回整数最高的元素。
采纳答案by kynnysmatto
max(alkaline_earth_values, key=lambda x: x[1])
The reason this works is because the keyargument of the maxfunction specifies a function that is called when maxwants to know the value by which the maximum element will be searched. maxwill call that function for each element in the sequence. And lambda x: x[1]creates a small function which takes in a list and returns the first (counting starts from zero) element. So
这样做的原因是因为max函数的key参数指定了一个函数，当max想知道将搜索最大元素的值时调用该函数。max将为序列中的每个元素调用该函数。并创建一个小函数，它接受一个列表并返回第一个（从零开始计数）元素。所以lambda x: x[1]
k = lambda x: x[1]
is the same as saying
和说一样
def k(l):
return l[1]
but shorter and nice to use in situations like this.
但在这种情况下使用更短而且很好用。
回答by Ignacio Vazquez-Abrams
Use the keyargument.
使用key参数。
max(alk..., key=operator.itemgetter(1))
回答by uytda
it is rather tricky to assume that an item in a list is actually still a number. If the numbers have become strings, the max()will return the 'value' with the highest first number:
假设列表中的项目实际上仍然是一个数字是相当棘手的。如果数字已成为字符串，max()则将返回具有最高第一个数字的“值”：
alkaline_earth_values = [['beryllium', '9'], ['magnesium', '12'],['calcium', '20'],
['strontium', '38'], ['barium', '56'], ['radium', '88']]
max(alkaline_earth_values, key=lambda x: x[1])
returns ['beryllium', '9']
回报 ['beryllium', '9']
max(alkaline_earth_values, key=lambda x: float(x[1]))
will do the trick, when you are sure it will be a number
会做的伎俩，当你确定这将是一个数字
回答by Peter M?lgaard Pallesen
For high speed consider pandas or numpy:
对于高速，请考虑 pandas 或 numpy：
Import pandas as pd
alkaline_earth_values = [['beryllium', 4], ['magnesium', 12],['calcium', 20],
['strontium', 38], ['barium', 56], ['radium', 88]]
pd.DataFrame(alkaline_earth_values)[1].max()
