在Pandas数据框列中查找元素的索引。

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英文:

Finding the index of an element is list in a Pandas Dataframe column

问题

我需要在 pandas 中执行以下操作:

import pandas as pd

# 创建示例数据帧
data = {'col_a': ['hello'],
        'col_b': [['goodbye', 'how are you', 'hello']],
        'col_c': [['farewell', 'question', 'greeting']]}

df = pd.DataFrame(data)

# 使用 apply 方法获取所需的值
df['col_d'] = df.apply(lambda row: row['col_c'][row['col_b'].index(row['col_a'][0])], axis=1)

# col_d 中包含所需的值

通过这种方式,你可以在 Pandas 中找到所需的值并将其放入一个新的列(在此示例中是 'col_d')。

英文:

I have a pandas dataframe:

col_a            col_b                               col_c  
hello       [goodbye, how are you, hello]   [farewell, question, greeting]

I need to find the value in the list in col_c which has the same index as the value of col_a in the list col_b. So in this case: "hello" has index 2 in [goodbye, how are you, hello]. I need to get the value with index 2 from col_c - in this case "greeting".

How can I do this in pandas?

答案1

得分: 2

你可以使用列表推导式与 zipnext 来实现:

df['out'] = [next((c2 for b2, c2 in zip(b, c) if a in b2), None)
             for a, b, c in zip(df['col_a'], df['col_b'], df['col_c'])]

输出:

   col_a                          col_b                           col_c       out
0  hello  [goodbye, how are you, hello]  [farewell, question, greeting]  greeting
英文:

You can use a list comprehension with zip and next:

df['out'] = [next((c2 for b2, c2 in zip(b, c) if a in b2), None)
             for a, b, c in zip(df['col_a'], df['col_b'], df['col_c'])]

Output:

   col_a                          col_b                           col_c       out
0  hello  [goodbye, how are you, hello]  [farewell, question, greeting]  greeting

答案2

得分: 2

已添加get_result_value(row)函数并实现了逻辑,该函数会根据列b中与列a对应的索引获取结果,并返回列c中的结果。

已附上结果。

data_set = {'col_a': ['hello'],
            'col_b': [['goodbye', 'how are you', 'hello']],
            'col_c': [['farewell', 'question', 'greeting']]}
df = pd.DataFrame(data_set)

def get_result_value(row):
    index = row['col_b'].index(row['col_a'])
    return row['col_c'][index]

print(df.apply(get_result_value, axis=1))

结果:

在Pandas数据框列中查找元素的索引。

英文:

Just added the function for get_result_value(row) and implemented logic as the index will contain column b corresponding to column a then will get a result from the index and column c.

I have attached the result as well.

 data_set = {'col_a': ['hello'],
               'col_b': [['goodbye', 'how are you', 'hello']],
               'col_c': [['farewell', 'question', 'greeting']]}
    df = pd.DataFrame(data_set)
    
    def get_result_value(row):
        index = row['col_b'].index(row['col_a'])
        return row['col_c'][index]
    
    print(df.apply(get_result_value, axis=1))

Result:

在Pandas数据框列中查找元素的索引。

huangapple
  • 本文由 发表于 2023年6月29日 01:09:14
  • 转载请务必保留本文链接:https://go.coder-hub.com/76575348.html
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