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

Jim Lemon drjimlemon at gmail.com
Thu Apr 27 23:49:32 CEST 2017


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
>
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>
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