[R] Problem in conversion of regulate time series and forecasting using Date Time [Timestamp values]:R

[Dhivya Narayanasamy]

Hi Jim,

Thank you for the reply. 'gg.ts' is actually the object name of the time
series I am using here.  Also I have changed my timestamp class from factor
to POSIXct  (gg$timestamps <- as.POSIXct(gg$timestamps, format = "%Y-%m-%d
%H-%M-%S") . When i plot this time series on graph, the x axis scales shows
random value rather than showing timestamp value. Is there any way to
correct the graph to make it show the timestamp value on x axis?  I use
plotly function for plotting.

Regards| Mit freundlichen Grüßen,

Dhivya Narayanasamy

Contact No: +91-8438505020

On Fri, Apr 28, 2017 at 3:19 AM, Jim Lemon <drjimlemon at gmail.com> wrote:

> Hi Dhivya,
> I'm not that familiar with the "gg.ts" function, but you are passing
> character values to the "frequency" and "start" arguments. If there is
> no automatic conversion to numeric values, that would cause the error.
> Similarly, your "timestamps" variable may have been read in as a
> factor, which often causes trouble with date conversions. Try
> as.character(gg$timestamps) instead of just gg$timestamps.
>
> Jim
>
>
> On Thu, Apr 27, 2017 at 4:51 PM, Dhivya Narayanasamy
> <dhiv.shreya at gmail.com> wrote:
> > Hi,
> > I am new to R. Kindly help me with the plot that gives wrong x-axis
> > values.  I have a data frame "gg", that looks like this:
> >
> >> head(gg)
> >
> >            timestamps      value
> > 1 2017-04-25 16:52:00 -0.4120000
> > 2 2017-04-25 16:53:00 -0.4526667
> > 3 2017-04-25 16:54:00 -0.4586667
> > 4 2017-04-25 16:55:00 -0.4606667
> > 5 2017-04-25 16:56:00 -0.5053333
> > 6 2017-04-25 16:57:00 -0.5066667
> >
> > I need to plot this as a Time series data to do forecasting. The steps
> are
> > as follows:
> >
> > 1) gg$timestamps <- as.POSIXct(gg$timestamps, format = "%Y-%m-%d
> %H-%M-%S")
> >  #changing "Timestamps" column 'factor' to 'as.POSIXct'.
> >
> > 2) gg.ts <- xts(x=gg$value, order.by = gg$timestamps) #converting the
> > dataframe to time series (Non Regular Time series)
> >
> > 3) fitting <- auto.arima(gg.ts) #fitting the time series model using
> > auto.arima
> >
> > 4) fore <- forecast(fitting, h=30, level = c(80,95))  #Forecasting
> >
> > 5) I am using plotly to this forecast model (Inspired from here :
> > https://plot.ly/r/graphing-multiple-chart-types/#
> plotting-forecast-objects)
> >
> > plot_ly() %>%
> >   add_lines(x = time(gg.ts), y = gg.ts,
> >             color = I("black"), name = "observed") %>%
> >   add_ribbons(x = time(fore$mean), ymin = fore$lower[, 2], ymax =
> > fore$upper[, 2],
> >               color = I("gray95"), name = "95% confidence") %>%
> >   add_ribbons(x = time(fore$mean), ymin = fore$lower[, 1], ymax =
> > fore$upper[, 1],
> >               color = I("gray80"), name = "80% confidence") %>%
> >   add_lines(x = time(fore$mean), y = fore$mean, color = I("blue"), name =
> > "prediction")
> >
> >
> > The plot comes out wrong: 1) x axis labels are wrong. It shows some
> > irrelevant values on axis. 2) the plot is not coming out.
> > Also I tried to convert "gg.ts" to a regulate time series which throws
> > error :
> >
> >> gg.xts <- ts(gg.ts, frequency = '1', start = ('2017-04-25 16:52:00'))
> > Error in 1/frequency : non-numeric argument to binary operator
> >
> > Please help me how to use Date Time values in converting to regulate time
> > series for forecasting.
> >
> >
> > Regards
> >> Dhivya
> >
> >         [[alternative HTML version deleted]]
> >
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