seasonality.py

from matplotlib import pyplot as plt
import pandas as pd
from pandas.plotting import autocorrelation_plot
from seasonality.seasonality_plots import plot_by_week

def get_user_data(data, userId):
    try:
        return data.loc[data.index.get_level_values(0) == userId].copy()
    except KeyError:
        print('El usuario ', userId, ' no existe.')
lista = []
df = pd.read_pickle('./pkl/dataset.pkl')
for i in df.index.get_level_values(0).drop_duplicates():
    dfu = get_user_data(df, i).droplevel(0).loc[:,'slevel']
    idx = pd.date_range('2013-03-27 04:00:00', '2013-06-01 3:00:00', freq='h')
    d = pd.DataFrame(index=idx)
    d['slevel'] = dfu
    a = d.isna().sum()
    lista.append(a)
    nulls = d.isna()
    plt.close()
    plt.scatter(list(range(len(idx))),nulls, 0.1, marker='x')
    plt.show()

    d.ffill(inplace=True)


    # Autocorrelation Plot
    plt.close()
    plt.rcParams.update({'figure.figsize':(9,5), 'figure.dpi':120})
    autocorrelation_plot(d.slevel)
    plt.title('{0},{1}'.format(str(i),a))
    plt.show()



    plot_by_week(i)


print(a)