[R] Warning message: Removed 888 rows containing missing values or values outside the scale range (`geom_line()`)

[roslinazairimah zakaria]

Dear all,
I tried to rerun the examples given by Hyndman in otexts but keep on
getting errors and I have searched through google but no solution yet.

Thank you in advance for any help given.

library(fpp3)
library(lubridate)
library(xts)
library(fabletools)
library(ggplot2)
library(dplyr)
library(gridExtra)

> dput(head(new_us_retail_employment,100))structure(list(Month = structure(c(-11323, -11292, -11264, -11233,
-11203, -11172, -11142, -11111, -11080, -11050, -11019, -10989,
-10958, -10927, -10898, -10867, -10837, -10806, -10776, -10745,
-10714, -10684, -10653, -10623, -10592, -10561, -10533, -10502,
-10472, -10441, -10411, -10380, -10349, -10319, -10288, -10258,
-10227, -10196, -10168, -10137, -10107, -10076, -10046, -10015,
-9984, -9954, -9923, -9893, -9862, -9831, -9803, -9772, -9742,
-9711, -9681, -9650, -9619, -9589, -9558, -9528, -9497, -9466,
-9437, -9406, -9376, -9345, -9315, -9284, -9253, -9223, -9192,
-9162, -9131, -9100, -9072, -9041, -9011, -8980, -8950, -8919,
-8888, -8858, -8827, -8797, -8766, -8735, -8707, -8676, -8646,
-8615, -8585, -8554, -8523, -8493, -8462, -8432, -8401, -8370,
-8342, -8311), class = c("yearmonth", "vctrs_vctr")), Series_ID =
c("CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001", "CEU0500000001",
"CEU0500000001", "CEU0500000001", "CEU0500000001"), Title = c("Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private", "Total Private",
"Total Private", "Total Private", "Total Private"), Employed = c(25338,
25447, 25833, 25801, 26113, 26485, 26481, 26848, 27468, 27830,
27740, 27886, 26847, 26902, 27205, 27255, 27535, 27765, 27789,
28332, 29007, 29399, 29619, 30221, 29402, 29671, 30079, 30610,
31379, 31999, 32545, 33014, 33417, 33457, 33367, 33552, 32660,
32739, 33240, 33764, 34203, 34624, 35065, 35460, 35771, 35852,
35867, 36209, 35494, 35627, 35955, 36212, 36202, 36608, 36637,
36628, 36584, 36658, 36810, 36815, 36018, 35973, 35948, 35833,
35768, 35949, 35861, 35828, 35652, 35555, 35597, 35850, 35229,
35290, 35411, 35161, 35024, 35065, 34769, 34490, 32760, 32833,
33354, 33755, 33656, 33092, 34240, 34997, 35409, 36074, 36474,
37139, 37532, 37637, 38045, 38351, 37510, 37495, 37720, 37686
)), class = c("tbl_ts", "tbl_df", "tbl", "data.frame"), row.names = c(NA,
-100L), key = structure(list(Series_ID = "CEU0500000001", .rows =
structure(list(
    1:100), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr",
"list"))), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA,
-1L), .drop = TRUE), index = structure("Month", ordered = TRUE),
index2 = "Month", interval = structure(list(
    year = 0, quarter = 0, month = 1, week = 0, day = 0, hour = 0,
    minute = 0, second = 0, millisecond = 0, microsecond = 0,
    nanosecond = 0, unit = 0), .regular = TRUE, class = c("interval",
"vctrs_rcrd", "vctrs_vctr")))



# Decomposition
new_us_retail_employment <- na.omit(us_retail_employment) # data cleaning

new_us_retail_employment |>
  model(
    classical_decomposition(Employed, type = "additive")
  ) |>
  components() |>
  autoplot() +xlab("Year") +
  ggtitle("Classical additive decomposition of total
                  US retail employment")

> new_us_retail_employment |>+   model(+     classical_decomposition(Employed, type = "additive")+   ) |>+   components() |>+   autoplot() +xlab("Year") ++   ggtitle("Classical additive decomposition of total+                   US retail employment")Warning message:Removed 888 rows containing missing values or values outside the scale range (`geom_line()`)



-- 
*Roslinazairimah Zakaria*
*Tel: +609-5492370; Fax. No.+609-5492766*

*Email: roslinazairimah using ump.edu.my <roslinazairimah using ump.edu.my>;
roslinaump using gmail.com <roslinaump using gmail.com>*
Faculty of Industrial Sciences & Technology
University Malaysia Pahang
Lebuhraya Tun Razak, 26300 Gambang, Pahang, Malaysia

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