python pandas数据框架创建列，如果一列中包含的字符串列表

发布于 2025-02-13 03:54:16 字数 729 浏览 0 评论 0原文

鉴于此DF：

data = {'Description':  ['with milk and orange', 'champagne', 'BANANA', 'bananas and apple', 'fafsa Lemons', 'GIN LEMON'],
        'Amount': ['10', '20', '10', '5', '9', '15']}
df = pd.DataFrame(data)
print (df)

以及以下矢量：

Fruits = ['apple','banana','lemon', 'orange']

如何获得“水果”列？（搜索列描述中矢量水果的所有元素，如果说明中包含在列中的“水果”中）

datanew = {'Description':  ['with milk and orange', 'champagne', 'BANANA', 'bananas and apple', 'fafsa Lemons', 'GIN LEMON'],
        'Amount': ['10', '20', '10', '5', '9', '15'],
        'Fruit':  ['orange', '', 'banana', 'banana-apple', 'lemon', 'lemon'],
       
       }
df2 = pd.DataFrame(datanew)
print (df2)

原文

given this df:

data = {'Description':  ['with milk and orange', 'champagne', 'BANANA', 'bananas and apple', 'fafsa Lemons', 'GIN LEMON'],
        'Amount': ['10', '20', '10', '5', '9', '15']}
df = pd.DataFrame(data)
print (df)

and the following vector:

Fruits = ['apple','banana','lemon', 'orange']

how to obtain the column 'Fruit'? (search for all the elements of the vector Fruits in the column description and add them in the Column 'fruit' if contained in Description)

datanew = {'Description':  ['with milk and orange', 'champagne', 'BANANA', 'bananas and apple', 'fafsa Lemons', 'GIN LEMON'],
        'Amount': ['10', '20', '10', '5', '9', '15'],
        'Fruit':  ['orange', '', 'banana', 'banana-apple', 'lemon', 'lemon'],
       
       }
df2 = pd.DataFrame(datanew)
print (df2)

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栀梦 2025-02-20 03:54:16

这是使用str.findall（）的另一种方法

(df.assign(Fruit = df['Description'].str.lower()
.str.findall('|'.join(Fruits))
.str.join('-')))

            Description Amount         Fruit
0  with milk and orange     10        orange
1             champagne     20              
2                BANANA     10        banana
3     bananas and apple      5  banana-apple
4          fafsa Lemons      9         lemon
5             GIN LEMON     15         lemon

Here is another way by using str.findall()

(df.assign(Fruit = df['Description'].str.lower()
.str.findall('|'.join(Fruits))
.str.join('-')))

            Description Amount         Fruit
0  with milk and orange     10        orange
1             champagne     20              
2                BANANA     10        banana
3     bananas and apple      5  banana-apple
4          fafsa Lemons      9         lemon
5             GIN LEMON     15         lemon

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娜些时光，永不杰束 2025-02-20 03:54:16

您可以使用 > 和 A>：

import re
df['Fruit'] = (df['Description']
               .str.extractall(f"({'|'.join(Fruits)})", flags=re.I)
               .groupby(level=0).agg('-'.join)[0]
               .str.lower()
              )

输出：

            Description Amount         Fruit
0  with milk and orange     10        orange
1             champagne     20           NaN
2                BANANA     10        banana
3     bananas and apple      5  banana-apple
4          fafsa Lemons      9         lemon
5             GIN LEMON     15         lemon

You can use str.extractall and groupby.agg:

import re
df['Fruit'] = (df['Description']
               .str.extractall(f"({'|'.join(Fruits)})", flags=re.I)
               .groupby(level=0).agg('-'.join)[0]
               .str.lower()
              )

output:

            Description Amount         Fruit
0  with milk and orange     10        orange
1             champagne     20           NaN
2                BANANA     10        banana
3     bananas and apple      5  banana-apple
4          fafsa Lemons      9         lemon
5             GIN LEMON     15         lemon

回复收藏 0 原文

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