Convert a Pandas DataFrame into a list of objects

Option 1: make Reading inherit from collections.MutableMapping and implement the necessary methods of that base class. Seems like a lot of work.

Option 2: Call Reading() in a list comprehension:

>>> import pandas as pd
>>> 
>>> df = pd.DataFrame({
...     'HourOfDay': [5, 10],
...     'Percentage': [0.25, 0.40]
... })
>>> 
>>> class Reading(object):
...     def __init__(self, HourOfDay: int = 0, Percentage: float = 0):
...         self.HourOfDay = int(HourOfDay)
...         self.Percentage = Percentage
...     def __repr__(self):
...         return f'{self.__class__.__name__}> (hour {self.HourOfDay}, pct. {self.Percentage})'
... 
>>> 
>>> readings = [Reading(**kwargs) for kwargs in df.to_dict(orient='records')]
>>> 
>>> 
>>> readings
[Reading> (hour 5, pct. 0.25), Reading> (hour 10, pct. 0.4)]

From docs:

into: The collections.Mapping subclass used for all Mappings in the return value. Can be the actual class or an empty instance of the mapping type you want. If you want a collections.defaultdict, you must pass it initialized.

having data frame with two column HourOfDay and Percentage, and parameterized constructor of your class you could define a list of Object like this:

 class Reading:

   def __init__(self, h, p):
       self.HourOfDay = h 
       self.Percentage = p 

 listOfReading= [(Reading(row.HourOfDay,row.Percentage)) for index, row in df.iterrows() ]