[英]Finding max value in the second column of a nested list?
I have a list like this:我有一个这样的列表:
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
max(list)
方法,它将返回答案'strontium'
,如果我试图找到 max name ,这将是正确的,但是我试图返回 integer 最高的元素。
max(alkaline_earth_values, key=lambda x: x[1])
The reason this works is because the key argument of the max function specifies a function that is called when max wants to know the value by which the maximum element will be searched.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 will call that function for each element in the sequence.
max将为序列中的每个元素调用该函数。 And
lambda x: x[1]
creates a small function which takes in a list and returns the first (counting starts from zero) element.并且
lambda x: x[1]
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。 So所以
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。
使用key
参数。
max(alk..., key=operator.itemgetter(1))
it is rather tricky to assume that an item in a list is actually still a 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。 If the numbers have become strings, the
max()
will return the 'value' with the highest first number:如果数字已成为字符串,则
max()
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']
返回
['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
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()
You could convert your list of lists to a Counter
and the call the .most_common()
method.您可以将列表列表转换为
Counter
并调用.most_common()
方法。 This easily allow you to find the maximum or top n values:这很容易让您找到最大值或前 n 个值:
>>> from collections import Counter
>>> Counter(dict(alkaline_earth_values)).most_common(1)
[('radium', 88)]
>>> Counter(dict(alkaline_earth_values)).most_common(3)
[('radium', 88), ('barium', 56), ('strontium', 38)]
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