元组对，使用python找到最小值
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Tuple pairs, finding minimum using python
提问by Harry Lime
I want to find the minimum of a list of tuples sorting by a given column. I have some data arranged as a list of 2-tuples for example.
我想找到按给定列排序的元组列表的最小值。例如，我将一些数据排列为 2 元组列表。
data = [ (1, 7.57), (2, 2.1), (3, 1.2), (4, 2.1), (5, 0.01),
(6, 0.5), (7, 0.2), (8, 0.6)]
How may I find the min of the dataset by the comparison of the second number in the tuples only?
如何仅通过比较元组中的第二个数字来找到数据集的最小值？
i.e.
IE
data[0][1] = 7.57
data[1][1] = 2.1
min( data ) = (5, 0.01)
分钟（数据）= (5, 0.01)
min( data )returns (1, 7.57), which I accept is correct for the minimum of index 0, but I want minimum of index 1.
min( data )回报(1, 7.57)，这是我接受的是为最小索引0的是正确的，但我想最少指数1。
采纳答案by Lev Levitsky
In [2]: min(data, key = lambda t: t[1])
Out[2]: (5, 0.01)
or:
或者：
In [3]: import operator
In [4]: min(data, key=operator.itemgetter(1))
Out[4]: (5, 0.01)
回答by user1767754
Even though Lev's answer is correct, I wanted to add the sort Method as well, in case someone is interested in the first nminimas.
One thing to consider is that the minoperation's runtime is O(N)where the sort's is O(N Log N)
即使 Lev 的答案是正确的，我也想添加 sort 方法，以防有人对第一个n最小值感兴趣。需要考虑的一件事是min操作的运行时是O(N)排序所在的位置O(N Log N)
data = [ (1, 7.57), (2, 2.1), (3, 1.2), (4, 2.1), (5, 0.01), (6, 0.5), (7, 0.2), (8, 0.6)]
data.sort(key=lambda x:x[1])
print data
>>> [(5, 0.01), (7, 0.2), (6, 0.5), (8, 0.6), (3, 1.2), (2, 2.1), (4, 2.1), (1, 7.57)]
https://www.ics.uci.edu/~pattis/ICS-33/lectures/complexitypython.txt
https://www.ics.uci.edu/~pattis/ICS-33/lectures/complexitypython.txt
回答by Eric Leschinski
If you're willing to drink the numpy coolaid, you can use these commands to get the tuple in list where item is minimum:
如果你愿意喝 numpy coolaid，你可以使用这些命令来获取列表中 item 最小的元组：
The ingredients that make this work are numpy's advanced array slicing and argsort features.
使这项工作发挥作用的成分是 numpy 的高级数组切片和 argsort 功能。
import numpy as np
#create a python list of tuples and convert it to a numpy ndarray of floats
data = np.array([ (1, 7.57), (2, 2.1), (3, 1.2),
(4, 2.1), (5, 0.01), (6, 0.5), (7, 0.2), (8, 0.6)])
print("data is")
print(data)
#Generate sortIndices from second column
sortIndices = np.argsort(data[:,1])
print("sortIndices using index 1 is:" )
print(sortIndices)
print("The column at index 1 is:")
print(data[:,1])
print("Index 1 put into order using column 1")
print(data[sortIndices,1])
print("The tuples put into order using column 1")
print(data[sortIndices,:])
print("The tuple with minimum value at index 1")
print(data[sortIndices[0],:])
print("The tuple with maximum value at index 1")
print(data[sortIndices[-1],:])
Which prints:
哪个打印：
data is
[[ 1. 7.57]
[ 2. 2.1 ]
[ 3. 1.2 ]
[ 4. 2.1 ]
[ 5. 0.01]
[ 6. 0.5 ]
[ 7. 0.2 ]
[ 8. 0.6 ]]
sortIndices using index 1 is:
[4 6 5 7 2 1 3 0]
The column at index 1 is:
[ 7.57 2.1 1.2 2.1 0.01 0.5 0.2 0.6 ]
Index 1 put into order using column 1
[ 0.01 0.2 0.5 0.6 1.2 2.1 2.1 7.57]
The tuples put into order using column 1
[[ 5. 0.01]
[ 7. 0.2 ]
[ 6. 0.5 ]
[ 8. 0.6 ]
[ 3. 1.2 ]
[ 2. 2.1 ]
[ 4. 2.1 ]
[ 1. 7.57]]
The tuple with minimum value at index 1
[ 5. 0.01]
The tuple with maximum value at index 1
[ 1. 7.57]
