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.
gg$timestamps ← as.POSIXct(gg$timestamps, format = “%Y-%m-%d %H-%M-%S”) #changing “Timestamps” column ‘factor’ to ‘as.POSIXct’.
gg.ts ← xts(x=gg$value, order.by = gg$timestamps) #converting the dataframe to time series (Non Regular Time series)
fitting ← auto.arima(gg.ts) #fitting the time series model using auto.arima
fore ← forecast(fitting, h=30, level = c(80,95)) #Forecasting
I am using plotly to this forecast model (Inspired from here : Multiple chart types in R)
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. Its not showing the timestamp value on x axis 2) the plot is also not coming out.
Please help me. Thank you in advance. Regards,Dhivya