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 <drjimle...@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.shr...@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]] > > > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/ > posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
