将列值匹配到dict [英] Match column values to dict

问题描述

我有一个字典和一个数据框，如下面的示例v和df.我想搜索df中的项目，并返回具有与dict中的值相同的最大字段值数量的项目.在这种情况下，它应该是项目3.我只是无法安静地直奔它.如果任何人有一个巧妙的方法来执行此操作或任何提示，将不胜感激.

I have a dict and a dataframe like the examples v and df below. I want to search through the items in df and return the item that has the maximum number of field values in common with the values in the dict. In this case it would be item 3. I was thinking maybe using apply with a lambda function, or transposing the df. I just can't quiet get my head around it. If anyone has a slick way to do this or any tips they're greatly appreciated.

输入:

v={'size':1,'color':red}

df:

item size color
2    2    red
3    1    red

Output:
3

推荐答案

另一种解决方案是使用字典而不是数据框:

An alternative solution is to work with dictionaries instead of dataframes:

v = {'size': 1, 'color': 'red'}

match_count = {}

fields = df.columns[1:]

for k, value in df.to_dict(orient='index').items():
    match_count[value['item']] = sum(value[i] == v[i] for i in fields & v.keys())

结果

print(match_count)
# {2: 1, 3: 2}

res = max(match_count.items(), key=lambda x: x[1])

print(res)
# (3, 2)

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