在 For 循环中调用不同的 DataFrame

Question

I am trying to use a for loop where a different DataFrame should be used in each iteration. It is the f'forecast_{s} below which is the problem.

What I want is that first, the DataFrame forecast_24 should be used, then forecast_168 etc. I can't understand why this is not working. Does it have to do with that a string can't call the DataFrame?

from sklearn.metrics import mean_squared_error
from sklearn.metrics import mean_absolute_error

naive_list = list(['24', '168', 'standard', 'custom'])

  
error = np.zeros((1,8))
for column, i, p, s in zip(df, range(1,5), range(8), naive_list):
    rmse = mean_squared_error(df[column].iloc[500:], f'forecast_{s}'[column].iloc[500:], squared=False)
    mae = mean_absolute_error(df[column].iloc[500:], f'forecast_{s}'[column].iloc[500:])
    error[p,2*p:2*p+2] = [rmse, mae]

TypeError: string indices must be integers

Answer 1

If I understand this correctly, you are trying to access the value forecast_24[column] at the first iteration of the loop and so on. Could you maybe do this instead:

naive_list = list([forecast_24, forecast_168, forecast_standard, forecast_custom])