class AnomalyFrame():
  def __init__(self):
    self.df = pd.DataFrame(columns=['alarm_at','error','actual'])

  def add_anomaly(self,index,error,actual):
    new_anomaly= {'alarm_at':index,'error':error, 'actual':actual}
    self.df=self.df.append(new_anomaly, ignore_index=True)

  def append_anomalyframe(self,df, predicted):
    error = abs(df['count_emails']-predicted)
    anomalies = df.iloc[detect_anomalies(error)]
    new_df = pd.DataFrame(data={'alarm_at':anomalies.index, 'error':error.iloc[detect_anomalies(error)], 'actual':anomalies['count_emails']})
    self.df=self.df.append(new_df,ignore_index=True)

  def agg(self,freq):
    return self.df.resample(freq, on='alarm_at').count().rename(columns={'alarm_at':'#anomalies'}).drop(columns=['error','actual'],axis=1)

  def info(self, freq):
    fig= plt.figure(figsize=(40,15))
    new_df = self.agg(freq)
    print(new_df.sort_values(by=['#anomalies'],ascending=False).head())
    sb.lineplot(x=new_df.index, y=new_df['#anomalies'])
    plt.show()


  def __repr__(self):
    print(self.df.tail(10))
    return ""