[R] How to get the date generated by the forecast function as another field in a data frame
Paul Bernal
paulbernal07 at gmail.com
Wed Mar 15 17:24:10 CET 2017
Hello Rui,
I have attached the .csv file, I will attach it again.
Please let me know if you can access it.
Cheers,
Paul
2017-03-15 11:05 GMT-05:00 Rui Barradas <ruipbarradas at sapo.pt>:
> Hello,
>
> Since we don't have access to file ContainerDataNEW.csv I cannot say for
> sure but it seems that those dates are the rownames so you could try
>
> rownames(TSSeriesModel1Forecast)
>
> and see what it gives. Or I might be completely mistaken.
>
> Hope this helps,
>
> Rui Barradas
>
>
> Em 15-03-2017 15:50, Paul Bernal escreveu:
>
>> Dear all,
>>
>> I am currently using R for windows Version 3.3.3 (I will provide the
>> sessionInfo() output below)
>>
>> library("Rcmdr")
>>>
>> Loading required package: splines
>> Loading required package: RcmdrMisc
>> Loading required package: car
>> Loading required package: sandwich
>>
>> Rcmdr Version 2.3-2
>>
>> library(forecast)
>>>
>>> library(tseries)
>>>
>>
>> 'tseries' version: 0.10-35
>>
>> 'tseries' is a package for time series analysis and computational
>> finance.
>>
>> See 'library(help="tseries")' for details.
>>
>> library(stats)
>>>
>>> library(stats4)
>>>
>>> Data<-read.csv("ContainerDataNEW.csv")
>>>
>>> TSData<-ts(Data[,1], start=c(1985,10), frequency=12)
>>>
>>> TSeriesModel1<-ets(TSData)
>>>
>>> TSSeriesModel1Forecast<-forecast(TSeriesModel1,h=24)
>>>
>>
>> Now the output from forecasts is the following:
>>
>> Point Forecast Lo 80 Hi 80 Lo 95
>> Hi 95
>> Apr 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>> May 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>> Jun 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>> Jul 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>> Aug 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>> Sep 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>> Oct 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>> Nov 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>> Dec 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>> Jan 2018 67.62845 30.73747 104.5194 11.20856 124.0483
>> Feb 2018 67.62845 30.73747 104.5194 11.20856 124.0483
>> Mar 2018 67.62845 30.73747 104.5194 11.20856 124.0483
>> Apr 2018 67.62845 30.73747 104.5194 11.20856 124.0483
>> May 2018 67.62845 30.73747 104.5194 11.20856 124.0483
>> Jun 2018 67.62845 30.73747 104.5194 11.20856 124.0483
>> Jul 2018 67.62845 30.73747 104.5194 11.20856 124.0484
>> Aug 2018 67.62845 30.73747 104.5194 11.20856 124.0484
>> Sep 2018 67.62845 30.73747 104.5194 11.20856 124.0484
>> Oct 2018 67.62845 30.73747 104.5194 11.20856 124.0484
>> Nov 2018 67.62845 30.73747 104.5194 11.20856 124.0484
>> Dec 2018 67.62845 30.73747 104.5194 11.20856 124.0484
>> Jan 2019 67.62845 30.73747 104.5194 11.20856 124.0484
>> Feb 2019 67.62845 30.73747 104.5194 11.20856 124.0484
>> Mar 2019 67.62845 30.73747 104.5194 11.20856 124.0484
>>
>> However, as you can see, the first "column" contains the dates for the
>> forecasts, but it appears as a field with no name.
>>
>> What I would like to do is to get those dates, add them as an additional
>> column to the forecasts so that when I use the data.frame(Forecasts) I can
>> have a result in this fashion:
>>
>> Date Point Forecast Lo 80 Hi 80 Lo 95
>> Hi 95
>> Apr 2017 67.62845 30.73747 104.5194 11.20856 124.0483
>>
>> Is there a way to do this?
>>
>> Here is the sessionInfo() output:
>>
>> sessionInfo()
>>>
>> R version 3.3.3 (2017-03-06)
>> Platform: x86_64-w64-mingw32/x64 (64-bit)
>> Running under: Windows 8.1 x64 (build 9600)
>>
>> locale:
>> [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United
>> States.1252 LC_MONETARY=English_United States.1252 LC_NUMERIC=C
>> LC_TIME=English_United States.1252
>>
>> attached base packages:
>> [1] stats4 splines stats graphics grDevices utils datasets
>> methods base
>>
>> other attached packages:
>> [1] tseries_0.10-35 forecast_8.0 Rcmdr_2.3-2 RcmdrMisc_1.0-5
>> sandwich_2.3-4 car_2.1-3
>>
>> loaded via a namespace (and not attached):
>> [1] Rcpp_0.12.7 lattice_0.20-34 tcltk2_1.2-11
>> class_7.3-14 zoo_1.7-13 lmtest_0.9-35 relimp_1.0-5
>> assertthat_0.1 digest_0.6.11 R6_2.2.0
>> plyr_1.8.4
>>
>> [12] acepack_1.4.1 MatrixModels_0.4-1 e1071_1.6-7
>> httr_1.2.1
>> ggplot2_2.2.0 lazyeval_0.2.0 AzureML_0.2.13
>> curl_2.2 uuid_0.1-2 readxl_0.1.1 minqa_1.2.4
>>
>> [23] data.table_1.10.4 SparseM_1.74 fracdiff_1.4-2
>> nloptr_1.0.4 rpart_4.1-10 Matrix_1.2-8 lme4_1.1-12
>> stringr_1.1.0 foreign_0.8-67 munsell_0.4.3
>> base64enc_0.1-3
>> [34] mgcv_1.8-17 htmltools_0.3.5 tcltk_3.3.3
>> nnet_7.3-12 tibble_1.2 gridExtra_2.2.1 htmlTable_1.7
>> quadprog_1.5-5 Hmisc_4.0-2 codetools_0.2-15
>> XML_3.98-1.4
>> [45] MASS_7.3-45 grid_3.3.3 nlme_3.1-131
>> jsonlite_1.1 gtable_0.2.0 magrittr_1.5 scales_0.4.1
>> stringi_1.1.2 timeDate_3012.100 latticeExtra_0.6-28
>> Formula_1.2-1
>> [56] RColorBrewer_1.1-2 tools_3.3.3 abind_1.4-5
>> parallel_3.3.3 pbkrtest_0.4-6 survival_2.40-1
>> colorspace_1.3-0 cluster_2.0.5 miniCRAN_0.2.7 knitr_1.15
>> quantreg_5.29
>>
>>>
>>>
>> I have also attached the file that I used to train the model and generate
>> forecasts.
>>
>> Any help will be greatly appreciated,
>>
>> Best regards,
>>
>> Paul
>> ______________________________________________
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
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