使用字符串格式的 DataFrame 索引作为类的实例

Question

创建 DataFrame 和类后，我想使用索引作为创建类的实例。听起来很奇怪，但让我解释一下：D

例如我有这个 Dataframe df:

  Name 'Jane' 'Max'

  Age   25     20 

Name 和Age 是字符串类型的索引。 我想将它转换为一个对象，以便我可以将它用作“I_am_a_class”类的实例，如下所示：

  df.index[0]
  output: 'Name'

  df.index[0] = I_am_a_class(attributes) 
  df.index[1] = I_am_a_class(attributes)

这不起作用，因为df.index[0] 是字符串格式。 我想知道是否有办法将df.index 转换为适当的格式，以便实现这一点？

Answer 1

编辑：感谢您解释您的目标是什么。如果您的数据框中只有几个条目，您可以执行以下操作：

import pandas as pd

class legend():
    def __init__(self,unit,meaning):
        self.unit= unit
        self.meaning= meaning
    
    
df = pd.DataFrame(
    data = {
        'unit':['m/s','Pa'],
        'meaning':['distance moved divided by the time','force divided by the area'], 
    },
    index=['velocity','pressure'],
)

velocity = legend(df.loc['velocity','unit'], df.loc['velocity','meaning'])
pressure = legend(df.loc['pressure','unit'], df.loc['pressure','meaning'])


print(velocity.unit)
print(velocity.meaning)

如果您的数据框中的行数过多或数量不定，因此您无法像上面那样手动创建变量，并且如果您出于某种原因真的不想使用字典，那么您可以执行以下操作，但不赞成：

import pandas as pd

class Legend():
    def __init__(self,unit,meaning):
        self.unit= unit
        self.meaning= meaning
    
    
df = pd.DataFrame(
    data = {
        'unit':['m/s','Pa'],
        'meaning':['distance moved divided by the time','force divided by the area'], 
    },
    index=['velocity','pressure'],
)

#If you REALLY don't want to use a dictionary you can use exec to create arbitrary variable names
#This is bad practice in python. You can read more about it at the link below
#https://stackoverflow.com/questions/5036700/how-can-you-dynamically-create-variables-via-a-while-loop
for i,r in df.iterrows():
    exec('{} = Legend("{}","{}")'.format(i,r['unit'],r['meaning']))


print(velocity.unit)
print(velocity.meaning)