Unable to plot ts, posting sample data

General
1

Hi all,
I am trying to plot time series after importing the data from csv to R.
now, the issue is:
the data needs to be read by Rows and not by columns.
when I am putting, Row header which is a product ID, it is taking the column value.
pasting the same code here.

rm(list = ls())

#set directory
setwd("d:\\Users\\AFG")

install.packages("reprex")
library(plyr)
# load required packages
library(readr)
library(dplyr)
library(ggplot2)
library(forecast)
library(reprex)

# import data
sales <- read.csv("SalesHistoryTop50SKU-reprex.csv", header = TRUE, blank.lines.skip = TRUE)

# reading sales 
sales 

# convert our sales data to a time series object
sales <- ts(sales$Article_ID, frequency = 9, start = c(2016,1))
class(sales)

plot(sales)
reprex()

here is the sample data.

Capture
Capture1004×228 8.06 KB

tried using reprex, but it is not working, and R studio is restarting everytime.

Goal: I want to read the data row wise. for the 8 weeks, and then forecast next 3 weeks data. for all the Article_ID individually. firstly I want to do it for 1. Then, i will try to use a loop to do it for other articles.

2

Hi @rdubai,

if your data is weekly, then frequency = 52, not 9. And weekly data is even more tricky because some years have 53 weeks, so you don't have a fixed frequency which makes things even messier.

3

Hi Valeri, my actual data will be h = 52. but here just to paste in the community, i removed rest of the data nd kept only 9 weeks.
you have valid point of 53 weeks. But for now, I want to run the code error free and see the result. Later we can modify and make it better. please advice.

4

Regardless of how many weeks you have in the actual dataset, you need to set frequency = 52 because that is the inherent frequency of the data (52 observations per cycle - a year in this case).

To be more clear (I hope), frequency = 9 means that the year is split into 9 equally spaced intervals, which in your case it definitely isn't.

5

ok, I kept the freq: 9 as i removed the rest and have only 9 observation for this demo. ok, I will change it to 52.

6

That is not sample data, that is a screenshot and is not very useful. Can you tell us what problems are you having to properly share sample data?, I think we should fix that first, since it would make things much easier.

7

this is the error i got after doing reprex().

reprex()
Rendering reprex...
Error: callr subprocess failed: Timeout was reached: [api.imgur.com] Connection timed out after 10000 milliseconds

8

I don't have your dataset, but this should work:

set.seed(22)
sales <- data.frame(Article_ID = letters[1:6])
sales[paste0("Week", 1:9)] <- replicate(9, rpois(6, 100))
sales
#   Article_ID Week1 Week2 Week3 Week4 Week5 Week6 Week7 Week8 Week9
# 1          a    94    98   126    98    84    86   110    89    95
# 2          b   100    98    92   102    95    88   132    85    92
# 3          c   105   103   108    94   106    93    98    92    89
# 4          d   106    92   120   104    94   105   103    99    98
# 5          e    96   108   109    96   104   107    88   116    91
# 6          f    99   114    83   108   108   119   102    91   125

sales_ts <- ts(
  t(sales[, -1]),
  frequency = 52,
  class = c("mts", "ts", "matrix")
)
rownames(sales_ts) <- names(sales)[-1]
colnames(sales_ts) <- sales[["Article_ID"]]
sales_ts
# Time Series:
# Start = c(1, 1) 
# End = c(1, 9) 
# Frequency = 52 
#            a   b   c   d   e   f
# 1.000000  94 100 105 106  96  99
# 1.019231  98  98 103  92 108 114
# 1.038462 126  92 108 120 109  83
# 1.057692  98 102  94 104  96 108
# 1.076923  84  95 106  94 104 108
# 1.096154  86  88  93 105 107 119
# 1.115385 110 132  98 103  88 102
# 1.134615  89  85  92  99 116  91
# 1.153846  95  92  89  98  91 125

The key part is this:

sales_ts <- ts(
  t(sales[, -1]),
  frequency = 52,
  class = c("mts", "ts", "matrix")
)

t(sales[, -1]) takes the sales dataset, omits the first column ("Article_ID"), and transposes it so the rows become columns. The resulting dataset is then turned into a time series with frequency of 52. The class = c("mts", "ts", "matrix") part tells the ts() function to make a "matrix time series," where each column is a separate time series. You can read about with help("ts").

Note for the future: To format a code block on this forum, wrap the code lines between two lines of three accent marks:

```
# Formatted like code
1 * 1 + 1 * 1
```

Also, when just sharing a single data object, you can see the code to recreate it with dput(myobject). Just share that code with others for a quick-and-dirty reprex.

2 Likes
9

It seems like you are not allowed to connect to imgur (maybe a restriction on the network you are connecting to) but regardless of this issue, you don't necessarily need to use reprex package to put together a proper reproducible example or even share sample data on a proper format, for the latest you can use datapasta package, see this blog post for a nice explanation.

11

this code worked, I wrote the output in a CSV before the ts(), it is correct. while ts() and forecast function did not work. Keep on getting this:

plot(salesLogHW)
Error in xy.coords(x, y) : 'x' and 'y' lengths differ

12

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