检查键是否以子串的形式存在于行中 [英] check if key is present in the row as a substring

问题描述

我有字典

myDict = {
'apple': 'FULL FORM',
'ball' : 'NEW'
}

然后是一个数据框:

myCol
..
new apple
netball
hello

我想遍历col myCol 的所有行以及字典的所有键，以查看我的任何键是否在行值中作为子字符串出现.如果是，我想获取键值并将其附加到列表中.例如，键值"apple"作为子行出现在我的第一行新苹果"中，因此我想提取键值"apple"

I want to iterate over all rows of col myCol and all the keys of my dictionary to see if any of my keys are present as a substring in the row value. If yes, I want to obtain the key value and append it to a list. For example, the key value 'apple' comes as a substring in my first row 'new apple', so I want to extract the key value 'apple'

我正在尝试此操作，但是由于我得到了所有未找到"信息，因此迭代似乎不起作用

I am trying this but the iteration doesn't seem to work since I get all 'Not Founds'

myList = []
for index, row in df.iterrows():
        for key, value in myDict.items():  
            if key in row['myCol'].lower():
                mylist.append(key)
        else:
            print(row['myCol'].lower())
            mylist.append('Not Found')
print(mylist) 

推荐答案

您的解决方案应通过 break 进行更改:

Your solution should be changed with break:

myList = []
for index, row in df.iterrows():
        for key, value in myDict.items():  
            if key in row['myCol'].lower():
                myList.append(key)
                break
        else:
            print(row['myCol'].lower())
            myList.append('Not Found')
print(myList) 
['apple', 'ball', 'Not Found']

或使用 按字典键的Series.str.extract ，对于正则表达式或，用 | 连接，如果未生成匹配项，则缺少值，因此将其替换由 Series.fillna 并将 Series 转换为列表:

Or use Series.str.extract by keys of dictionary with join by | for regex or, if no match is generated missing value, so replace it by Series.fillna and convert Series to list:

myList = (df['myCol'].str.extract(f'({"|".join(myDict.keys())})', expand=False, case=False)
                     .fillna('Not Found')
                     .tolist())

print(myList) 
['apple', 'ball', 'Not Found']

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