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
