mydatasetI have this data set which consists of two attributes i.e Year(2016,2017,2018) and Month(JAN TO DEC). The data set contains the average sales value for all the months for the years 2016, 2017 & 2018. Now when I import this data set, it shows that the data set is a "data.frame" . However I want it to be in "ts" . Then I ran this command
data.ts<- as.ts(myData)
to convert my data into "ts". The result is as follows:
class(data.ts)
[1] "mts" "ts" "matrix"
Now, I want my data set to be in "ts" only, meaning when I run the command class(data.ts). It should show "ts" only. How can I convert my data in "ts" only? And does this "mts" and "matrix" matters or not?
Also, when I plot my data using the command
plot(data.ts)
It shows a plot in which Time is on x-axis while Year and Sales are on y-axis. On the other hand, I want to plot a graph which shows the Year in x axis and Sales values of Months on y-axis.
How do I arrange my data such that when I import the dataset, it is already in ts? Or is there any other way to do it? Also, how to arrange the dataset that it shows the Year on x axis by default. I'm really confused as all the videos that I have seen on YouTube has their data already in "ts". Also, their plot shows Year on x-axis. Hope I have made myself clear. Any help would be appreciated.
How can I plot the graph such that Year is on x axis?
Reorder the data in a single variable:
data=as.matrix(data)
data= as.data.frame(t(data))
names(data)=c('x2016','x2017','x2018')
series=c(data$x2016,data$x2017,data$x2018)
Then take just index accordingly to the start point and the frequency of data. In your case looks like monthly from 2016 hence:
data.ts=ts(series ,start=c(2016,1), frequency=12)
plot(data.ts)
Related
Apologies for a question on something which is probably very straightforward. I am very new to R.
I have a dataframe which contains dates in a year,month,day format e.g. "2020-05-28". I wanted to stratify the data at month level, so I used the "floor_date" function. However, now the dates read as "2020-05-01" etc. This is absolutely fine for the data set itself, but I am creating epidemiological curves and want to change the dates to "2020-05" etc. on the legend. Could anyone provide some guidance on how to do this? I can't simply replace the pattern "01" with a blank as I need to keep 01 on month level (January) visible.
My data contains several measurements in one day. It is stored in CSV-file and looks like this:
enter image description here
The V1 column is factor type, so I'm adding a extra column which is date-time -type: vd$Vdate <- as_datetime(vd$V1) :
enter image description here
Then I'm trying to convert the vd-data into time series: vd.ts<- ts(vd, frequency = 365)
But then the dates are gone:
enter image description here
I just cannot get it what I am doing wrong! Could someone help me, please.
Your dates are gone because you need to build the ts dataframe from your variables (V1, ... V7) disregarding the date field and your ts command will order R to structure the dates.
Also, I noticed that you have what is seems like hourly data, so you need to provide the frequency that is appropriate to your time not 365. Considering what you posted your frequency seems to be a bit odd. I recommend finding a way to establish the frequency correctly. For example, if I have hourly data for 365 days of the year then I have a frequency of 365.25*24 (0.25 for the leap years).
So the following is just as an example, it still won't work properly with what I see (it is limited view of your dataset so I am not sure 100%)
# Build ts data (univariate)
vs.ts <- ts(vd$V1, frequency = 365, start = c(2019, 4)
# check to see if it is structured correctly
print(vd.ts, calendar = T)
Finally my time series is working properly. I used
ts <- zoo(measurements, date_times)
and I found out that the date_times was supposed to be converted with as_datetime() as otherwise they were character type. The measurements are converted into data.frame type.
i have a data with date(2015)with mm/dd/yy format and sales. I need to predict sales for 2016 with the given data. I just know, I need to use time series forecasting. However no idea. Since, many examples have only year like(1960,1970,..) my data has only one year with several months. Don't know how to plot too. can you give me a clear structure how to proceed?
Assuming that the date is in string and in the format mm/dd/yy
convert string into date by using this code
a <- "07/23/15"
b <- as.Date(a, format = "%m/%d/%y")
fullYear <- format(b,'%Y') // to get 2015 as year
halfYear <- format(b, '%y') //to get 15 as year
After this you can work on
I have found the solution. Converted sales figure into time series format.
plotted the data and seen whether there is any trend/Seasonality.
Since the data has only trend applied holts exponential smoothing under forecast package. Sales of 2016 has been found and plotted.
I want to get a panel data set into zoo so that it catches both month and year. My data set looks like this.
and the data can be downloaded from HERE.
The best way I could do is,
dat<-read.csv("dat_lag.csv")
zdat <- read.zoo(dat, format="%d/%m/%Y")
However, I could do this by including column 1- Date and column 4- Day in my data set. Is there any clever way to get both month and year into zoo using R without including the Date and Day columns? Thanks, in advance for any help.
I am trying to create a plot of weekly data. Though this is not the exact problem I am having it illustrates it well. Basically imagine you want to make a plot of 1,2,....,7 for for 7 weeks from Jan 1 2015. So basically my plot should just be a line that trends upward but instead I get 7 different lines. I tried the code (and some other to no avail). Help would be greatly appreciated.
startDate = "2015-01-01"
endDate = "2015-02-19"
y=c(1,2,3,4,5,6,7)
tsy=ts(y,start=as.Date(startDate),end=as.Date(endDate))
plot(tsy)
You are plotting both the time and y together as individual plots.
Instead use:
plot(y)
lines(y)
Also, create a date column based on the specifics you gave which will be a time series. From here you can add the date on the x-axis to easily see how your variable changes over time.
To make your life easier I think your first step should be to create a (xts) time series object (install/load the xts-package), then it is a piece of cake to plot, subset or do whatever you like with the series.
Build your vector of dates as a sequence with start/end date:
seq( as.Date("2011-07-01"), by=1, len=7)
and your data vector: 1:7
a one-liner builds and plots the above time series object:
plot(as.xts(1:7,order.by=seq( as.Date("2011-07-01"), by=1, len=7)))