def getDataFrame(dataframe, needDisplay=False): idx = dataframe.timestamp.values y = dataframe.y.values df = addHeader (idx,y) if (needDisplay): dtime = [dt.datetime.fromtimestamp(int(x)).strftime('%Y-%m-%d %H:%M:%S') for x in idx ] dtime1 = [parse(d) for d in dtime] df_display =addHeader (dtime1, y) return df, df_display return df, None
def convertTSToDataFrame(valuesList, convertTime=False, metricName='y', isProphet=False): ts_idx = [] ts = [] vals = [] valueslength = len(valuesList) for i in range(valueslength): if convertTime: ts.append(dt.utcfromtimestamp(int(valuesList[i][0]))) ts_idx.append(valuesList[i][0]) vals.append(float(valuesList[i][1])) if isProphet: return addHeader(ts_idx, vals, ts, False) return addHeader(ts_idx, vals)
def formatData(result, dateFormat=True): if result.timeseries is not None: for entry in result.timeseries: data = np.array(entry.data) idx = pd.Series(data[:,0]) y = data[:,1] if (dateFormat) : dtime = [dt.datetime.fromtimestamp(int(x)).strftime('%Y-%m-%d %H:%M:%S') for x in idx ] dtime1 = [parse(d) for d in dtime] df = addHeader(dtime1,y) else: #lidx = [math.floor(x) for x in idx] df = addHeader(idx, y) return df
def formatData(result): if result.timeseries is not None: for entry in result.timeseries: data = np.array(entry.data) idx = pd.Series(data[:, 0]) dtime = [ dt.datetime.fromtimestamp(int(x)).strftime('%Y-%m-%d %H:%M:%S') for x in idx ] dtime1 = [parse(d) for d in dtime] y = data[:, 1] df = addHeader(dtime1, y) return df
def convertToProphetDF(dataframe): idx = dataframe.index.get_values() p_utc = [datetime.utcfromtimestamp(int(d)) for d in idx] df_prophet = addHeader (idx, dataframe.y.values, p_utc,False) return df_prophet
def dataframe_substract(df1,df2,time_diff=86400): newdf1= addHeader(df1.index+time_diff, df1.y.values) df = newdf1.merge(df2, how='inner' , left_index=True, right_index=True) df['y']=df.apply(lambda row: row.y_x-row.y_y, axis=1) return df