在python中查找相对于列表col2中的值的col1中的最大值

Question

我是python新手。我想找到col2相对于列表col1中的“man”、“women”和“people”的最大值。例如，['men', 12, '1946-Truman.txt'], ['women', 7, '1946-Truman.txt']和['people', 49, '1946-Truman.txt']包含男性、女性和人群的col2的最大值。在

一种可能的解决方案是将这个元组列表转换为三个单独的数组，分别用于男性、女性和人群，然后从所有数组中找到最大值。但是，我想要一个更好的解决方案。在

数据：

[['men', 2, '1945-Truman.txt']
['women', 2, '1945-Truman.txt']
['people', 10, '1945-Truman.txt']
['men', 12, '1946-Truman.txt']
['women', 7, '1946-Truman.txt']
['people', 49, '1946-Truman.txt']
['men', 7, '1947-Truman.txt']
['women', 2, '1947-Truman.txt']
['people', 12, '1947-Truman.txt']
['men', 4, '1948-Truman.txt']
['women', 1, '1948-Truman.txt']
['people', 22, '1948-Truman.txt']
['men', 2, '1949-Truman.txt']
['women', 1, '1949-Truman.txt']
['people', 15, '1949-Truman.txt']
['men', 6, '1950-Truman.txt']
['women', 2, '1950-Truman.txt']
['people', 15, '1950-Truman.txt']
['men', 8, '1951-Truman.txt']
['women', 2, '1951-Truman.txt']
['people', 9, '1951-Truman.txt']
['men', 3, '1953-Eisenhower.txt']
['women', 0, '1953-Eisenhower.txt']
['people', 17, '1953-Eisenhower.txt']]

提前谢谢。在

Answer 1

您可以使用pandas包。 通过定义数据帧：

import pandas as pd
df = pd.DataFrame([['men', 2, '1945-Truman.txt'],
                   ['women', 2, '1945-Truman.txt'],
                   ['people', 10, '1945-Truman.txt'],
                   ['men', 12, '1946-Truman.txt'],
                    ['women', 7, '1946-Truman.txt'],
                   ['people', 49, '1946-Truman.txt'],
                   ['men', 7, '1947-Truman.txt'],
                   ['women', 2, '1947-Truman.txt'],
                   ['people', 12, '1947-Truman.txt'],
                   ['men', 4, '1948-Truman.txt'],
                   ['women', 1, '1948-Truman.txt'],
                   ['people', 22, '1948-Truman.txt'],
                   ['men', 2, '1949-Truman.txt'],
                   ['women', 1, '1949-Truman.txt'],
                   ['people', 15, '1949-Truman.txt'],
                   ['men', 6, '1950-Truman.txt'],
                   ['women', 2, '1950-Truman.txt'],
                   ['people', 15, '1950-Truman.txt'],
                   ['men', 8, '1951-Truman.txt'],
                   ['women', 2, '1951-Truman.txt'],
                   ['people', 9, '1951-Truman.txt'],
                   ['men', 3, '1953-Eisenhower.txt'],
                   ['women', 0, '1953-Eisenhower.txt'],
                   ['people', 17, '1953-Eisenhower.txt']])

那么

^{pr2}$

返回

0 
men       12
women      7
people    49
Name: 1, dtype: int64

这就是你想要的吗？在

Answer 2

如果您使用的列表包括：

lst=[['men', 2123, '1945-Truman.txt'],
['women', 2, '1945-Truman.txt'],
['people', 10, '1945-Truman.txt'],
['men', 12, '1946-Truman.txt'],
['women', 7, '1946-Truman.txt'],
['people', 49, '1946-Truman.txt'],
['men', 7, '1947-Truman.txt'],
['women', 2, '1947-Truman.txt']]

然后可以使用以下代码。在

^{pr2}$

这将进入名为lst的位列表中的每个列表，并找到男性、女性和人员的最大值。在

Answer 3

pandas是一个很好的选择，但是您可以使用max和{}：

men = max(data, key=lambda x: x[1] if x[0] == 'men' else 0)
women = max(data, key=lambda x: x[1] if x[0] == 'women' else 0)
people = max(data, key=lambda x: x[1] if x[0] == 'people' else 0)