In [14]:

    

import loadForecast as lf
import pandas as pd
%matplotlib inline


    

In [5]:

    

df = pd.read_csv('data/test/COAST.csv', parse_dates=['dates'])
df['year'] = df.dates.dt.year

years = [2002]
acc_dict = {}
for y in df.year.unique()[1:]:
    years.append(y)
    df_c = df[df['year'].isin(years)]
    all_X = lf.makeUsefulDf(df_c)
    all_y = df_c['load']
    _, accuracy = lf.neural_net_predictions(all_X, all_y)
    r = accuracy
    r.update({'years': years})
    acc_dict[len(years)] = r


    

In [10]:

    

y = pd.DataFrame(acc_dict).T


    

In [16]:

    

y['test'][1:].plot()


    

    
Out[16]:





<matplotlib.axes._subplots.AxesSubplot at 0x147523fd0>






    

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