From 37a33a9104d85424a0125ea4bab613d20d0ebdc6 Mon Sep 17 00:00:00 2001 From: robjhyndman Date: Tue, 25 Jun 2024 07:48:17 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20robjhynd?= =?UTF-8?q?man/fpp3package@9a88d2ecefafef140888cbdb1f7f6e0b51640e56=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- index.html | 6 +++--- pkgdown.yml | 2 +- search.json | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/index.html b/index.html index 203ff61..06553c2 100644 --- a/index.html +++ b/index.html @@ -93,9 +93,9 @@

Usage
  • dplyr, for data manipulation.
  • -tidyr, to easily tidy data using spread() and gather().
    • +tidyr, to tidy data.
  • -lubridate, for date/times.
    • +lubridate, for dates/times.
  • ggplot2, for data visualisation.
  • @@ -110,7 +110,7 @@

    Usage

    You also get a condensed summary of conflicts with other packages you have loaded:

     library(fpp3)
-#> ── Attaching packages ─────────────────────────────────────── fpp3 0.5.0.9000 ──
+#> ── Attaching packages ──────────────────────────────────────────── fpp3 1.0.0 ──
 #> ✔ tibble      3.2.1     ✔ tsibble     1.1.4
 #> ✔ dplyr       1.1.4     ✔ tsibbledata 0.4.1
 #> ✔ tidyr       1.3.1     ✔ feasts      0.3.2
diff --git a/pkgdown.yml b/pkgdown.yml
index d12c2af..d6333d0 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,7 +2,7 @@ pandoc: 3.1.11
 pkgdown: 2.0.9
 pkgdown_sha: ~
 articles: {}
-last_built: 2024-06-25T07:46Z
+last_built: 2024-06-25T07:48Z
 urls:
   reference: https://pkg.robjhyndman.com/fpp3package/reference
   article: https://pkg.robjhyndman.com/fpp3package/articles
diff --git a/search.json b/search.json
index f60e4a0..413b1ee 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://pkg.robjhyndman.com/fpp3package/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Rob Hyndman. Author, maintainer, copyright holder. George Athanasopoulos. Contributor. Mitchell O'Hara-Wild. Contributor. Nuwani Palihawadana. Contributor. Shanika Wickramasuriya. Contributor. RStudio. Copyright holder.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Hyndman R (2024). fpp3: Data \"Forecasting: Principles Practice\" (3rd Edition). R package version 1.0.0,  https://github.com/robjhyndman/fpp3package, https://OTexts.com/fpp3/, https://pkg.robjhyndman.com/fpp3package/.","code":"@Manual{,   title = {fpp3: Data for \"Forecasting: Principles and Practice\" (3rd Edition)},   author = {Rob Hyndman},   year = {2024},   note = {R package version 1.0.0,  https://github.com/robjhyndman/fpp3package, https://OTexts.com/fpp3/},   url = {https://pkg.robjhyndman.com/fpp3package/}, }"},{"path":[]},{"path":"https://pkg.robjhyndman.com/fpp3package/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Data for ","text":"fpp3 package contains data used book Forecasting: Principles Practice (3rd edition) Rob J Hyndman George Athanasopoulos. also loads several packages needed analysis described book. packages work tidyverse set packages, sharing common data representations API design. Additional data sets used book also included.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Data for ","text":"can install stable version CRAN. can install development version Github","code":"install.packages('fpp3', dependencies = TRUE) # install.packages(\"remotes\") remotes::install_github(\"robjhyndman/fpp3package\")"},{"path":"https://pkg.robjhyndman.com/fpp3package/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Data for ","text":"library(fpp3) load following packages: tibble, tibbles, modern re-imagining data frames. dplyr, data manipulation. tidyr, easily tidy data using spread() gather(). lubridate, date/times. ggplot2, data visualisation. tsibble, tsibbles, time series version tibble. tsibbledata, various time series data sets form tsibbles. feasts, features statistics time series. fable, fitting models producing forecasts. also get condensed summary conflicts packages loaded:","code":"library(fpp3) #> ── Attaching packages ─────────────────────────────────────── fpp3 0.5.0.9000 ── #> ✔ tibble      3.2.1     ✔ tsibble     1.1.4 #> ✔ dplyr       1.1.4     ✔ tsibbledata 0.4.1 #> ✔ tidyr       1.3.1     ✔ feasts      0.3.2 #> ✔ lubridate   1.9.3     ✔ fable       0.3.4 #> ✔ ggplot2     3.5.1     ✔ fabletools  0.4.2 #> ── Conflicts ───────────────────────────────────────────────── fpp3_conflicts ── #> ✖ lubridate::date()    masks base::date() #> ✖ dplyr::filter()      masks stats::filter() #> ✖ tsibble::intersect() masks base::intersect() #> ✖ tsibble::interval()  masks lubridate::interval() #> ✖ dplyr::lag()         masks stats::lag() #> ✖ tsibble::setdiff()   masks base::setdiff() #> ✖ tsibble::union()     masks base::union()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_accommodation.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian accommodation data — aus_accommodation","title":"Australian accommodation data — aus_accommodation","text":"aus_accommodation quarterly `tsibble` containing data Australian tourist accommodation short-term non-residential accommodation 15 rooms, 1998 Q1 - 2016 Q2. data set also contains Australian Consumer Price Index (CPI) period. Takings millions Australian dollars, Occupancy percentage rooms occupied, CPI index value 100 2012 Q1.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_accommodation.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian accommodation data — aus_accommodation","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_accommodation.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian accommodation data — aus_accommodation","text":"Australian Bureau Statistics, Cat 8635.0, Table 10, Cat 6401.0, Table 1.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_accommodation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian accommodation data — aus_accommodation","text":"","code":"aus_accommodation #> # A tsibble: 592 x 5 [1Q] #> # Key:       State [8] #>       Date State                        Takings Occupancy   CPI #>                                        #>  1 1998 Q1 Australian Capital Territory    24.3      65    67   #>  2 1998 Q2 Australian Capital Territory    22.3      59    67.4 #>  3 1998 Q3 Australian Capital Territory    22.5      58    67.5 #>  4 1998 Q4 Australian Capital Territory    24.4      59    67.8 #>  5 1999 Q1 Australian Capital Territory    23.7      58    67.8 #>  6 1999 Q2 Australian Capital Territory    25.4      61    68.1 #>  7 1999 Q3 Australian Capital Territory    28.2      66    68.7 #>  8 1999 Q4 Australian Capital Territory    25.8      60    69.1 #>  9 2000 Q1 Australian Capital Territory    27.3      60.9  69.7 #> 10 2000 Q2 Australian Capital Territory    30.1      64.7  70.2 #> # ℹ 582 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_airpassengers.html","id":null,"dir":"Reference","previous_headings":"","what":"Air Transport Passengers Australia — aus_airpassengers","title":"Air Transport Passengers Australia — aus_airpassengers","text":"Total annual air passengers (millions) including domestic international aircraft passengers air carriers registered Australia. 1970-2016.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_airpassengers.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Air Transport Passengers Australia — aus_airpassengers","text":"Annual time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_airpassengers.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Air Transport Passengers Australia — aus_airpassengers","text":"World Bank.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_airpassengers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Air Transport Passengers Australia — aus_airpassengers","text":"","code":"aus_airpassengers #> # A tsibble: 47 x 2 [1Y] #>     Year Passengers #>           #>  1  1970       7.32 #>  2  1971       7.33 #>  3  1972       7.80 #>  4  1973       9.38 #>  5  1974      10.7  #>  6  1975      11.1  #>  7  1976      10.9  #>  8  1977      11.3  #>  9  1978      12.1  #> 10  1979      13.0  #> # ℹ 37 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_arrivals.html","id":null,"dir":"Reference","previous_headings":"","what":"International Arrivals to Australia — aus_arrivals","title":"International Arrivals to Australia — aus_arrivals","text":"Quarterly international arrivals Australia Japan, New Zealand, UK US.  1981Q1 - 2012Q3.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_arrivals.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"International Arrivals to Australia — aus_arrivals","text":"Quarterly time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_arrivals.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"International Arrivals to Australia — aus_arrivals","text":"Tourism Research Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_arrivals.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"International Arrivals to Australia — aus_arrivals","text":"","code":"aus_arrivals #> # A tsibble: 508 x 3 [1Q] #> # Key:       Origin [4] #>    Quarter Origin Arrivals #>             #>  1 1981 Q1 Japan     14763 #>  2 1981 Q2 Japan      9321 #>  3 1981 Q3 Japan     10166 #>  4 1981 Q4 Japan     19509 #>  5 1982 Q1 Japan     17117 #>  6 1982 Q2 Japan     10617 #>  7 1982 Q3 Japan     11737 #>  8 1982 Q4 Japan     20961 #>  9 1983 Q1 Japan     20671 #> 10 1983 Q2 Japan     12235 #> # ℹ 498 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian births data — aus_births","title":"Australian births data — aus_births","text":"Number births Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian births data — aus_births","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian births data — aus_births","text":"Australian Bureau Statistics. https://www.abs.gov.au/statistics/people/population/births-australia/2022","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian births data — aus_births","text":"aus_births monthly `tsibble` one measured variable: January 1975 December 2021 6 states 2 territories Australia, indexed : #' series uniquely identified using key:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian births data — aus_births","text":"","code":"aus_births #> # A tsibble: 4,512 x 3 [1M] #> # Key:       State [8] #>    State    Month Births #>           #>  1 ACT   1975 Jan    320 #>  2 ACT   1975 Feb    333 #>  3 ACT   1975 Mar    342 #>  4 ACT   1975 Apr    348 #>  5 ACT   1975 May    336 #>  6 ACT   1975 Jun    374 #>  7 ACT   1975 Jul    372 #>  8 ACT   1975 Aug    354 #>  9 ACT   1975 Sep    361 #> 10 ACT   1975 Oct    337 #> # ℹ 4,502 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian women fertility rate — aus_fertility","title":"Australian women fertility rate — aus_fertility","text":"aus_fertility yearly `tsibble` one measured variable:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian women fertility rate — aus_fertility","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian women fertility rate — aus_fertility","text":"Australian Bureau Statistics. ","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian women fertility rate — aus_fertility","text":"series uniquely identified using two keys: based calendar year registration data. covers period 1975--2022.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian women fertility rate — aus_fertility","text":"","code":"aus_fertility #> # A tsibble: 15,120 x 4 [1Y] #> # Key:       Age, Region [315] #>     Year Region    Age    Rate #>            #>  1  1975 Australia 15      7   #>  2  1976 Australia 15      6.6 #>  3  1977 Australia 15      5.7 #>  4  1978 Australia 15      5.5 #>  5  1979 Australia 15      5.1 #>  6  1980 Australia 15      4.8 #>  7  1981 Australia 15      4.8 #>  8  1982 Australia 15      4.7 #>  9  1983 Australia 15      4.9 #> 10  1984 Australia 15      3.8 #> # ℹ 15,110 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":null,"dir":"Reference","previous_headings":"","what":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"aus_inbound monthly `tsibble` one measured variable:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"Tourism Research Australia","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"series uniquely identified using two keys: covering period Jan 2005--Feb 2020.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"","code":"aus_inbound #> # A tsibble: 20,748 x 4 [1M] #> # Key:       Country, Purpose [114] #>       Month Country Purpose  Count #>                #>  1 2005 Jan Canada  Business 0.924 #>  2 2005 Feb Canada  Business 1.04  #>  3 2005 Mar Canada  Business 1.30  #>  4 2005 Apr Canada  Business 1.29  #>  5 2005 May Canada  Business 1.12  #>  6 2005 Jun Canada  Business 0.813 #>  7 2005 Jul Canada  Business 0.881 #>  8 2005 Aug Canada  Business 1.45  #>  9 2005 Sep Canada  Business 1.24  #> 10 2005 Oct Canada  Business 1.24  #> # ℹ 20,738 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian migration data — aus_migration","title":"Australian migration data — aus_migration","text":"Net Overseas Migration (NOM) Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian migration data — aus_migration","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian migration data — aus_migration","text":"Australian Bureau Statistics. . Cat . 310102.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian migration data — aus_migration","text":"aus_migration quarterly `tsibble` one measured variable: 1981 Q2 2023 Q3 6 states 2 territories Australia, indexed : NOM based international traveller's duration stay Australia 12 months , 16 month period. series uniquely identified using key:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian migration data — aus_migration","text":"","code":"aus_migration #> # A tsibble: 1,360 x 3 [1Q] #> # Key:       State [8] #>    Quarter State   NOM #>         #>  1 1981 Q2 ACT    -131 #>  2 1981 Q3 ACT     152 #>  3 1981 Q4 ACT     383 #>  4 1982 Q1 ACT     419 #>  5 1982 Q2 ACT     271 #>  6 1982 Q3 ACT      80 #>  7 1982 Q4 ACT     209 #>  8 1983 Q1 ACT     283 #>  9 1983 Q2 ACT     -31 #> 10 1983 Q3 ACT     199 #> # ℹ 1,350 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian mortality data — aus_mortality","title":"Australian mortality data — aus_mortality","text":"Weekly death counts mortality rates Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian mortality data — aus_mortality","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian mortality data — aus_mortality","text":"https://mortality.org/Data/STMF (Downloaded 29 May 2024)","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian mortality data — aus_mortality","text":"aus_mortality weekly `tsibble` two measured variables: 2015 week 01 2023 week 12 five different age groups plus total, categorised sex. series uniquely identified using three keys: mortality rate defined number deaths per thousand people Australia week.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian mortality data — aus_mortality","text":"","code":"aus_mortality #> # A tsibble: 7,740 x 5 [1W] #> # Key:       Sex, Age [18] #>        Week Sex   Age   Deaths Mortality #>                #>  1 2015 W01 Both  0-14    31.1  0.000360 #>  2 2015 W02 Both  0-14    29.0  0.000334 #>  3 2015 W03 Both  0-14    27.5  0.000318 #>  4 2015 W04 Both  0-14    27.8  0.000321 #>  5 2015 W05 Both  0-14    26.0  0.000300 #>  6 2015 W06 Both  0-14    28.5  0.000330 #>  7 2015 W07 Both  0-14    29.4  0.000339 #>  8 2015 W08 Both  0-14    31.2  0.000361 #>  9 2015 W09 Both  0-14    27.9  0.000322 #> 10 2015 W10 Both  0-14    29.0  0.000334 #> # ℹ 7,730 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":null,"dir":"Reference","previous_headings":"","what":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"aus_outbound monthly `tsibble` one measured variable:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"Tourism Research Australia","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"series uniquely identified using two keys: covering period Jan 2005--Jun 2017.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"","code":"aus_outbound #> # A tsibble: 11,700 x 4 [1M] #> # Key:       Country, Purpose [78] #>       Month Country                               Purpose  Count #>                                              #>  1 2005 Jan China (excl SARs and Taiwan province) Business  5.75 #>  2 2005 Feb China (excl SARs and Taiwan province) Business  4.48 #>  3 2005 Mar China (excl SARs and Taiwan province) Business  7.05 #>  4 2005 Apr China (excl SARs and Taiwan province) Business  9.84 #>  5 2005 May China (excl SARs and Taiwan province) Business  6.05 #>  6 2005 Jun China (excl SARs and Taiwan province) Business  7.11 #>  7 2005 Jul China (excl SARs and Taiwan province) Business  6.56 #>  8 2005 Aug China (excl SARs and Taiwan province) Business  8.35 #>  9 2005 Sep China (excl SARs and Taiwan province) Business  7.97 #> 10 2005 Oct China (excl SARs and Taiwan province) Business  8.68 #> # ℹ 11,690 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian cigarette and tobacco expenditure — aus_tobacco","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"total household expenditure cigarette tobacco consumption (CTC) Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"Australian Bureau Statistics. ","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"aus_tobacco quarterly `tsibble` one value: 1985 Q3 2023 Q4 6 states 2 territories Australia, indexed : prices represented chain volume measure (representation constant prices) billions dollars. series uniquely identified using key:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"","code":"aus_tobacco |> autoplot(Expenditure) + scale_y_log10()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian vehicle sales — aus_vehicle_sales","title":"Australian vehicle sales — aus_vehicle_sales","text":"number new motor vehicles sold Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian vehicle sales — aus_vehicle_sales","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian vehicle sales — aus_vehicle_sales","text":"Australian Bureau Statistics. . Cat . 931401.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian vehicle sales — aus_vehicle_sales","text":"aus_vehicle_sales monthly `tsibble` one measured variable: January 1994 December 2017 Australia, indexed : series uniquely identified using key:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian vehicle sales — aus_vehicle_sales","text":"","code":"aus_vehicle_sales #> # A tsibble: 864 x 3 [1M] #> # Key:       Type [3] #>       Month Type  Count #>          #>  1 1994 Jan Other  5.46 #>  2 1994 Feb Other  7.42 #>  3 1994 Mar Other 10.3  #>  4 1994 Apr Other  8.02 #>  5 1994 May Other 10.2  #>  6 1994 Jun Other 15.8  #>  7 1994 Jul Other  7.36 #>  8 1994 Aug Other  8.40 #>  9 1994 Sep Other  8.13 #> 10 1994 Oct Other  9.17 #> # ℹ 854 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":null,"dir":"Reference","previous_headings":"","what":"Call volume for a large North American commercial bank — bank_calls","title":"Call volume for a large North American commercial bank — bank_calls","text":"Five-minute call volume handled weekdays 7:00am 9:05pm, beginning 3 March 24 October 2003 (164 days).","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Call volume for a large North American commercial bank — bank_calls","text":"Time series class `tsibble` 5 minute intervals.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Call volume for a large North American commercial bank — bank_calls","text":"Jonathan Weinberg","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Call volume for a large North American commercial bank — bank_calls","text":"Weinberg, Brown & Stroud (2007) \"Bayesian forecasting inhomogeneous Poisson process applications call center data\" Journal American Statistical Associiation, 102:480, 1185-1198.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Call volume for a large North American commercial bank — bank_calls","text":"","code":"bank_calls #> # A tsibble: 27,716 x 2 [5m]  #>    DateTime            Calls #>                   #>  1 2003-03-03 07:00:00   111 #>  2 2003-03-03 07:05:00   113 #>  3 2003-03-03 07:10:00    76 #>  4 2003-03-03 07:15:00    82 #>  5 2003-03-03 07:20:00    91 #>  6 2003-03-03 07:25:00    87 #>  7 2003-03-03 07:30:00    75 #>  8 2003-03-03 07:35:00    89 #>  9 2003-03-03 07:40:00    99 #> 10 2003-03-03 07:45:00   125 #> # ℹ 27,706 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/boston_marathon.html","id":null,"dir":"Reference","previous_headings":"","what":"Boston marathon winning times since 1897 — boston_marathon","title":"Boston marathon winning times since 1897 — boston_marathon","text":"Winning times events Boston Marathon. 1897-2019.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/boston_marathon.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Boston marathon winning times since 1897 — boston_marathon","text":"Annual time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/boston_marathon.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Boston marathon winning times since 1897 — boston_marathon","text":"Boston Athletic Association. https://www.baa.org/races/boston-marathon/results/champions","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/boston_marathon.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Boston marathon winning times since 1897 — boston_marathon","text":"","code":"boston_marathon #> # A tsibble: 265 x 5 [1Y] #> # Key:       Event [5] #>    Event                Year Champion            Country       Time       #>                                                  #>  1 Men's open division  1897 John J. McDermott   United States 10510 secs #>  2 Men's open division  1898 Ronald J. MacDonald Canada         9720 secs #>  3 Men's open division  1899 Lawrence Brignolia  United States 10478 secs #>  4 Men's open division  1900 John P. Caffery     Canada         9584 secs #>  5 Men's open division  1901 John P. Caffery     Canada         8963 secs #>  6 Men's open division  1902 Sammy A. Mellor     United States  9792 secs #>  7 Men's open division  1903 John C. Lorden      United States  9689 secs #>  8 Men's open division  1904 Michael Spring      United States  9484 secs #>  9 Men's open division  1905 Frederick Lorz      United States  9505 secs #> 10 Men's open division  1906 Timothy Ford        United States  9945 secs #> # ℹ 255 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":null,"dir":"Reference","previous_headings":"","what":"Monthly Canadian gas production — canadian_gas","title":"Monthly Canadian gas production — canadian_gas","text":"Monthly Canadian gas production, billions cubic metres, January 1960 - February 2005","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Monthly Canadian gas production — canadian_gas","text":"Monthly time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Monthly Canadian gas production — canadian_gas","text":"Hyndman, R.J., Koehler, .B., Ord, J.K., Snyder, R.D., (2008) Forecasting exponential smoothing: state space approach, Springer.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Monthly Canadian gas production — canadian_gas","text":"http://www.exponentialsmoothing.net","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Monthly Canadian gas production — canadian_gas","text":"","code":"canadian_gas #> # A tsibble: 542 x 2 [1M] #>       Month Volume #>          #>  1 1960 Jan  1.43  #>  2 1960 Feb  1.31  #>  3 1960 Mar  1.40  #>  4 1960 Apr  1.17  #>  5 1960 May  1.12  #>  6 1960 Jun  1.01  #>  7 1960 Jul  0.966 #>  8 1960 Aug  0.977 #>  9 1960 Sep  1.03  #> 10 1960 Oct  1.25  #> # ℹ 532 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3-package.html","id":null,"dir":"Reference","previous_headings":"","what":"fpp3: Data for ","title":"fpp3: Data for ","text":"data sets required examples exercises book \"Forecasting: principles practice\" Rob J Hyndman George Athanasopoulos https://OTexts.com/fpp3/. packages required run examples also loaded. Additional data sets used book also included.","code":""},{"path":[]},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"fpp3: Data for ","text":"Maintainer: Rob Hyndman Rob.Hyndman@monash.edu (ORCID) [copyright holder] contributors: George Athanasopoulos [contributor] Mitchell O'Hara-Wild [contributor] Nuwani Palihawadana [contributor] Shanika Wickramasuriya [contributor] RStudio [copyright holder]","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":null,"dir":"Reference","previous_headings":"","what":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"function lists conflicts packages fpp3 collection packages loaded.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"","code":"fpp3_conflicts()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"list object class fpp3_conflicts.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"conflicts deliberately ignored: intersect, union, setequal, setdiff dplyr; intersect, union, setdiff, .difftime lubridate. functions make base equivalents generic, negatively affect existing code.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"","code":"fpp3_conflicts() #> ── Conflicts ───────────────────────────────────────────────── fpp3_conflicts ── #> ✖ lubridate::date()    masks base::date() #> ✖ dplyr::filter()      masks stats::filter() #> ✖ tsibble::intersect() masks base::intersect() #> ✖ tsibble::interval()  masks lubridate::interval() #> ✖ dplyr::lag()         masks stats::lag() #> ✖ tsibble::setdiff()   masks base::setdiff() #> ✖ tsibble::union()     masks base::union()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":null,"dir":"Reference","previous_headings":"","what":"List all packages loaded by fpp3 — fpp3_packages","title":"List all packages loaded by fpp3 — fpp3_packages","text":"List packages loaded fpp3","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List all packages loaded by fpp3 — fpp3_packages","text":"","code":"fpp3_packages(include_self = FALSE)"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List all packages loaded by fpp3 — fpp3_packages","text":"include_self Include fpp3 list?","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List all packages loaded by fpp3 — fpp3_packages","text":"character vector package names.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List all packages loaded by fpp3 — fpp3_packages","text":"","code":"fpp3_packages() #>  [1] \"cli\"         \"crayon\"      \"dplyr\"       \"fable\"       \"fabletools\"  #>  [6] \"feasts\"      \"ggplot2\"     \"lubridate\"   \"purrr\"       \"rstudioapi\"  #> [11] \"tibble\"      \"tidyr\"       \"tsibble\"     \"tsibbledata\""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/guinea_rice.html","id":null,"dir":"Reference","previous_headings":"","what":"Rice production (Guinea) — guinea_rice","title":"Rice production (Guinea) — guinea_rice","text":"Total annual rice production (million metric tons) Guinea. 1970-2011.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/guinea_rice.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Rice production (Guinea) — guinea_rice","text":"Annual time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/guinea_rice.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Rice production (Guinea) — guinea_rice","text":"World Bank.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/guinea_rice.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rice production (Guinea) — guinea_rice","text":"","code":"guinea_rice #> # A tsibble: 42 x 2 [1Y] #>     Year Production #>           #>  1  1970      0.311 #>  2  1971      0.325 #>  3  1972      0.340 #>  4  1973      0.355 #>  5  1974      0.370 #>  6  1975      0.387 #>  7  1976      0.404 #>  8  1977      0.422 #>  9  1978      0.440 #> 10  1979      0.460 #> # ℹ 32 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/insurance.html","id":null,"dir":"Reference","previous_headings":"","what":"Insurance quotations and advertising expenditure — insurance","title":"Insurance quotations and advertising expenditure — insurance","text":"Monthly quotations monthly television advertising expenditure US insurance company. January 2002 April 2005","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/insurance.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Insurance quotations and advertising expenditure — insurance","text":"Monthly time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/insurance.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Insurance quotations and advertising expenditure — insurance","text":"Kindly provided Dave Reilly, Automatic Forecasting Systems.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/insurance.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Insurance quotations and advertising expenditure — insurance","text":"","code":"insurance |>   ggplot(aes(x=TVadverts, y=Quotes)) + geom_point()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/melb_walkers.html","id":null,"dir":"Reference","previous_headings":"","what":"Average daily total pedestrian count in Melbourne — melb_walkers","title":"Average daily total pedestrian count in Melbourne — melb_walkers","text":"Daily average total pedestrian count (across different sensors) thousands 2019-01-01 2024-05-29.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/melb_walkers.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Average daily total pedestrian count in Melbourne — melb_walkers","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/melb_walkers.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Average daily total pedestrian count in Melbourne — melb_walkers","text":"Melbourne Open Data Portal. ","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/melb_walkers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Average daily total pedestrian count in Melbourne — melb_walkers","text":"","code":"autoplot(melb_walkers) #> Plot variable not specified, automatically selected `.vars = Count`"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":null,"dir":"Reference","previous_headings":"","what":"Monthly offences in NSW — nsw_offences","title":"Monthly offences in NSW — nsw_offences","text":"nsw_offences monthly `tsibble` one measured variable:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Monthly offences in NSW — nsw_offences","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Monthly offences in NSW — nsw_offences","text":"NSW Bureau Crime Statistics Research. ","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Monthly offences in NSW — nsw_offences","text":"series uniquely identified using one key: covering period Apr 1995--Dec 2023.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Monthly offences in NSW — nsw_offences","text":"","code":"nsw_offences #> # A tsibble: 7,308 x 3 [1M] #> # Key:       Type [21] #>       Month Type                     Count #>                             #>  1 1995 Jan Abduction and kidnapping    15 #>  2 1995 Feb Abduction and kidnapping    16 #>  3 1995 Mar Abduction and kidnapping    23 #>  4 1995 Apr Abduction and kidnapping    22 #>  5 1995 May Abduction and kidnapping    14 #>  6 1995 Jun Abduction and kidnapping    13 #>  7 1995 Jul Abduction and kidnapping    19 #>  8 1995 Aug Abduction and kidnapping    23 #>  9 1995 Sep Abduction and kidnapping    13 #> 10 1995 Oct Abduction and kidnapping    21 #> # ℹ 7,298 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":null,"dir":"Reference","previous_headings":"","what":"New York childcare data — ny_childcare","title":"New York childcare data — ny_childcare","text":"number employees (thousands) child day care services New York City period period January 1990 April 2024.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"New York childcare data — ny_childcare","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"New York childcare data — ny_childcare","text":"U.S. Bureau Labor Statistics Federal Reserve Bank St. Louis, Employees: Education Health Services: Child Care Services New York City, NY retrieved FRED, Federal Reserve Bank St. Louis; , 30 May 2024.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"New York childcare data — ny_childcare","text":"ny_childcare monthly `tsibble` two columns:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"New York childcare data — ny_childcare","text":"","code":"ny_childcare #> # A tsibble: 412 x 2 [1M] #>       Month Count #>         #>  1 1990 Jan  14.1 #>  2 1990 Feb  14.1 #>  3 1990 Mar  14.2 #>  4 1990 Apr  14   #>  5 1990 May  14   #>  6 1990 Jun  14   #>  7 1990 Jul  13.3 #>  8 1990 Aug  13.2 #>  9 1990 Sep  13.9 #> 10 1990 Oct  14.1 #> # ℹ 402 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/otexts_views.html","id":null,"dir":"Reference","previous_headings":"","what":"OTexts page views — otexts_views","title":"OTexts page views — otexts_views","text":"Daily page views OTexts website  recorded Google analytics.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/otexts_views.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"OTexts page views — otexts_views","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/otexts_views.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"OTexts page views — otexts_views","text":"otexts_views daily `tsibble` two columns:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/otexts_views.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"OTexts page views — otexts_views","text":"","code":"otexts_views #> # A tsibble: 1,561 x 2 [1D] #>    Date       Pageviews #>              #>  1 2018-01-01      2.13 #>  2 2018-01-02      4.07 #>  3 2018-01-03      6.27 #>  4 2018-01-04      5.96 #>  5 2018-01-05      6.34 #>  6 2018-01-06      4.13 #>  7 2018-01-07      3.70 #>  8 2018-01-08      5.92 #>  9 2018-01-09      7.38 #> 10 2018-01-10      7.81 #> # ℹ 1,551 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/prices.html","id":null,"dir":"Reference","previous_headings":"","what":"Price series for various commodities — prices","title":"Price series for various commodities — prices","text":"Annual prices eggs, chicken, copper, nails, oil wheat. Eggs, chicken, nails, oil copper $US; wheat British pounds. prices adjusted inflation.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/prices.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Price series for various commodities — prices","text":"Annual time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/prices.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Price series for various commodities — prices","text":"Makridakis, Wheelwright Hyndman (1998) *Forecasting: methods applications*, John Wiley & Sons: New York. Chapter 9.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/prices.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Price series for various commodities — prices","text":"","code":"prices |> autoplot(wheat) #> Warning: Removed 1 row containing missing values or values outside the scale range #> (`geom_line()`)."},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/souvenirs.html","id":null,"dir":"Reference","previous_headings":"","what":"Sales for a souvenir shop — souvenirs","title":"Sales for a souvenir shop — souvenirs","text":"Monthly sales souvenir shop wharf beach resort town Queensland, Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/souvenirs.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Sales for a souvenir shop — souvenirs","text":"Monthly time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/souvenirs.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Sales for a souvenir shop — souvenirs","text":"Makridakis, Wheelwright Hyndman (1998) *Forecasting: methods applications*, John Wiley & Sons: New York. Exercise 5.8.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/souvenirs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sales for a souvenir shop — souvenirs","text":"","code":"souvenirs |> autoplot(Sales)"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_change.html","id":null,"dir":"Reference","previous_headings":"","what":"Percentage changes in economic variables in the USA. — us_change","title":"Percentage changes in economic variables in the USA. — us_change","text":"us_change quarterly `tsibble` containing percentage changes quarterly personal consumption expenditure, personal disposable income, production, savings unemployment rate US, 1970 2016. Original $ values chained 2012 US dollars.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_change.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Percentage changes in economic variables in the USA. — us_change","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_change.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Percentage changes in economic variables in the USA. — us_change","text":"Federal Reserve Bank St Louis.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_change.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Percentage changes in economic variables in the USA. — us_change","text":"","code":"us_change #> # A tsibble: 198 x 6 [1Q] #>    Quarter Consumption Income Production Savings Unemployment #>                                 #>  1 1970 Q1       0.619  1.04      -2.45    5.30         0.9   #>  2 1970 Q2       0.452  1.23      -0.551   7.79         0.5   #>  3 1970 Q3       0.873  1.59      -0.359   7.40         0.5   #>  4 1970 Q4      -0.272 -0.240     -2.19    1.17         0.700 #>  5 1971 Q1       1.90   1.98       1.91    3.54        -0.100 #>  6 1971 Q2       0.915  1.45       0.902   5.87        -0.100 #>  7 1971 Q3       0.794  0.521      0.308  -0.406        0.100 #>  8 1971 Q4       1.65   1.16       2.29   -1.49         0     #>  9 1972 Q1       1.31   0.457      4.15   -4.29        -0.200 #> 10 1972 Q2       1.89   1.03       1.89   -4.69        -0.100 #> # ℹ 188 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_employment.html","id":null,"dir":"Reference","previous_headings":"","what":"US monthly employment data — us_employment","title":"US monthly employment data — us_employment","text":"us_employment monthly `tsibble` containing US employment data January 1939 June 2019. `Series_ID` represents different sectors economy.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_employment.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"US monthly employment data — us_employment","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_employment.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"US monthly employment data — us_employment","text":"U.S. Bureau Labor Statistics","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_employment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"US monthly employment data — us_employment","text":"","code":"us_employment #> # A tsibble: 143,412 x 4 [1M] #> # Key:       Series_ID [148] #>       Month Series_ID     Title         Employed #>                              #>  1 1939 Jan CEU0500000001 Total Private    25338 #>  2 1939 Feb CEU0500000001 Total Private    25447 #>  3 1939 Mar CEU0500000001 Total Private    25833 #>  4 1939 Apr CEU0500000001 Total Private    25801 #>  5 1939 May CEU0500000001 Total Private    26113 #>  6 1939 Jun CEU0500000001 Total Private    26485 #>  7 1939 Jul CEU0500000001 Total Private    26481 #>  8 1939 Aug CEU0500000001 Total Private    26848 #>  9 1939 Sep CEU0500000001 Total Private    27468 #> 10 1939 Oct CEU0500000001 Total Private    27830 #> # ℹ 143,402 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_gasoline.html","id":null,"dir":"Reference","previous_headings":"","what":"US finished motor gasoline product supplied. — us_gasoline","title":"US finished motor gasoline product supplied. — us_gasoline","text":"Weekly data beginning Week 6, 1991, ending Week 3, 2017. Units \"million barrels per day\".","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_gasoline.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"US finished motor gasoline product supplied. — us_gasoline","text":"Time series object class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_gasoline.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"US finished motor gasoline product supplied. — us_gasoline","text":"US Energy Information Administration.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_gasoline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"US finished motor gasoline product supplied. — us_gasoline","text":"","code":"us_gasoline #> # A tsibble: 1,355 x 2 [1W] #>        Week Barrels #>          #>  1 1991 W06    6.62 #>  2 1991 W07    6.43 #>  3 1991 W08    6.58 #>  4 1991 W09    7.22 #>  5 1991 W10    6.88 #>  6 1991 W11    6.95 #>  7 1991 W12    7.33 #>  8 1991 W13    6.78 #>  9 1991 W14    7.50 #> 10 1991 W15    6.92 #> # ℹ 1,345 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/news/index.html","id":"fpp3-100","dir":"Changelog","previous_headings":"","what":"fpp3 1.0.0","title":"fpp3 1.0.0","text":"aus_births aus_fertility aus_inbound aus_mortality aus_migration aus_outbound aus_tobacco aus_vehicle_sales melb_walkers nsw_offences ny_childcare otexts_views","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/news/index.html","id":"fpp3-03","dir":"Changelog","previous_headings":"","what":"fpp3 0.3","title":"fpp3 0.3","text":"CRAN release: 2020-06-07 Updated objects work tsibble v0.9.0 Added series titles us_employment","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/news/index.html","id":"fpp3-02","dir":"Changelog","previous_headings":"","what":"fpp3 0.2","title":"fpp3 0.2","text":"CRAN release: 2020-03-15 Added aus_arrivals data set.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/news/index.html","id":"fpp3-01","dir":"Changelog","previous_headings":"","what":"fpp3 0.1","title":"fpp3 0.1","text":"CRAN release: 2019-10-09 Initial version based tidyverse package Hadley Wickham. data ported fpp2. New data sets include us_employment.","code":""}]
+[{"path":"https://pkg.robjhyndman.com/fpp3package/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Rob Hyndman. Author, maintainer, copyright holder. George Athanasopoulos. Contributor. Mitchell O'Hara-Wild. Contributor. Nuwani Palihawadana. Contributor. Shanika Wickramasuriya. Contributor. RStudio. Copyright holder.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Hyndman R (2024). fpp3: Data \"Forecasting: Principles Practice\" (3rd Edition). R package version 1.0.0,  https://github.com/robjhyndman/fpp3package, https://OTexts.com/fpp3/, https://pkg.robjhyndman.com/fpp3package/.","code":"@Manual{,   title = {fpp3: Data for \"Forecasting: Principles and Practice\" (3rd Edition)},   author = {Rob Hyndman},   year = {2024},   note = {R package version 1.0.0,  https://github.com/robjhyndman/fpp3package, https://OTexts.com/fpp3/},   url = {https://pkg.robjhyndman.com/fpp3package/}, }"},{"path":[]},{"path":"https://pkg.robjhyndman.com/fpp3package/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Data for ","text":"fpp3 package contains data used book Forecasting: Principles Practice (3rd edition) Rob J Hyndman George Athanasopoulos. also loads several packages needed analysis described book. packages work tidyverse set packages, sharing common data representations API design. Additional data sets used book also included.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Data for ","text":"can install stable version CRAN. can install development version Github","code":"install.packages('fpp3', dependencies = TRUE) # install.packages(\"remotes\") remotes::install_github(\"robjhyndman/fpp3package\")"},{"path":"https://pkg.robjhyndman.com/fpp3package/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Data for ","text":"library(fpp3) load following packages: tibble, tibbles, modern re-imagining data frames. dplyr, data manipulation. tidyr, tidy data. lubridate, dates/times. ggplot2, data visualisation. tsibble, tsibbles, time series version tibble. tsibbledata, various time series data sets form tsibbles. feasts, features statistics time series. fable, fitting models producing forecasts. also get condensed summary conflicts packages loaded:","code":"library(fpp3) #> ── Attaching packages ──────────────────────────────────────────── fpp3 1.0.0 ── #> ✔ tibble      3.2.1     ✔ tsibble     1.1.4 #> ✔ dplyr       1.1.4     ✔ tsibbledata 0.4.1 #> ✔ tidyr       1.3.1     ✔ feasts      0.3.2 #> ✔ lubridate   1.9.3     ✔ fable       0.3.4 #> ✔ ggplot2     3.5.1     ✔ fabletools  0.4.2 #> ── Conflicts ───────────────────────────────────────────────── fpp3_conflicts ── #> ✖ lubridate::date()    masks base::date() #> ✖ dplyr::filter()      masks stats::filter() #> ✖ tsibble::intersect() masks base::intersect() #> ✖ tsibble::interval()  masks lubridate::interval() #> ✖ dplyr::lag()         masks stats::lag() #> ✖ tsibble::setdiff()   masks base::setdiff() #> ✖ tsibble::union()     masks base::union()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_accommodation.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian accommodation data — aus_accommodation","title":"Australian accommodation data — aus_accommodation","text":"aus_accommodation quarterly `tsibble` containing data Australian tourist accommodation short-term non-residential accommodation 15 rooms, 1998 Q1 - 2016 Q2. data set also contains Australian Consumer Price Index (CPI) period. Takings millions Australian dollars, Occupancy percentage rooms occupied, CPI index value 100 2012 Q1.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_accommodation.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian accommodation data — aus_accommodation","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_accommodation.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian accommodation data — aus_accommodation","text":"Australian Bureau Statistics, Cat 8635.0, Table 10, Cat 6401.0, Table 1.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_accommodation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian accommodation data — aus_accommodation","text":"","code":"aus_accommodation #> # A tsibble: 592 x 5 [1Q] #> # Key:       State [8] #>       Date State                        Takings Occupancy   CPI #>                                        #>  1 1998 Q1 Australian Capital Territory    24.3      65    67   #>  2 1998 Q2 Australian Capital Territory    22.3      59    67.4 #>  3 1998 Q3 Australian Capital Territory    22.5      58    67.5 #>  4 1998 Q4 Australian Capital Territory    24.4      59    67.8 #>  5 1999 Q1 Australian Capital Territory    23.7      58    67.8 #>  6 1999 Q2 Australian Capital Territory    25.4      61    68.1 #>  7 1999 Q3 Australian Capital Territory    28.2      66    68.7 #>  8 1999 Q4 Australian Capital Territory    25.8      60    69.1 #>  9 2000 Q1 Australian Capital Territory    27.3      60.9  69.7 #> 10 2000 Q2 Australian Capital Territory    30.1      64.7  70.2 #> # ℹ 582 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_airpassengers.html","id":null,"dir":"Reference","previous_headings":"","what":"Air Transport Passengers Australia — aus_airpassengers","title":"Air Transport Passengers Australia — aus_airpassengers","text":"Total annual air passengers (millions) including domestic international aircraft passengers air carriers registered Australia. 1970-2016.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_airpassengers.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Air Transport Passengers Australia — aus_airpassengers","text":"Annual time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_airpassengers.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Air Transport Passengers Australia — aus_airpassengers","text":"World Bank.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_airpassengers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Air Transport Passengers Australia — aus_airpassengers","text":"","code":"aus_airpassengers #> # A tsibble: 47 x 2 [1Y] #>     Year Passengers #>           #>  1  1970       7.32 #>  2  1971       7.33 #>  3  1972       7.80 #>  4  1973       9.38 #>  5  1974      10.7  #>  6  1975      11.1  #>  7  1976      10.9  #>  8  1977      11.3  #>  9  1978      12.1  #> 10  1979      13.0  #> # ℹ 37 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_arrivals.html","id":null,"dir":"Reference","previous_headings":"","what":"International Arrivals to Australia — aus_arrivals","title":"International Arrivals to Australia — aus_arrivals","text":"Quarterly international arrivals Australia Japan, New Zealand, UK US.  1981Q1 - 2012Q3.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_arrivals.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"International Arrivals to Australia — aus_arrivals","text":"Quarterly time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_arrivals.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"International Arrivals to Australia — aus_arrivals","text":"Tourism Research Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_arrivals.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"International Arrivals to Australia — aus_arrivals","text":"","code":"aus_arrivals #> # A tsibble: 508 x 3 [1Q] #> # Key:       Origin [4] #>    Quarter Origin Arrivals #>             #>  1 1981 Q1 Japan     14763 #>  2 1981 Q2 Japan      9321 #>  3 1981 Q3 Japan     10166 #>  4 1981 Q4 Japan     19509 #>  5 1982 Q1 Japan     17117 #>  6 1982 Q2 Japan     10617 #>  7 1982 Q3 Japan     11737 #>  8 1982 Q4 Japan     20961 #>  9 1983 Q1 Japan     20671 #> 10 1983 Q2 Japan     12235 #> # ℹ 498 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian births data — aus_births","title":"Australian births data — aus_births","text":"Number births Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian births data — aus_births","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian births data — aus_births","text":"Australian Bureau Statistics. https://www.abs.gov.au/statistics/people/population/births-australia/2022","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian births data — aus_births","text":"aus_births monthly `tsibble` one measured variable: January 1975 December 2021 6 states 2 territories Australia, indexed : #' series uniquely identified using key:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_births.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian births data — aus_births","text":"","code":"aus_births #> # A tsibble: 4,512 x 3 [1M] #> # Key:       State [8] #>    State    Month Births #>           #>  1 ACT   1975 Jan    320 #>  2 ACT   1975 Feb    333 #>  3 ACT   1975 Mar    342 #>  4 ACT   1975 Apr    348 #>  5 ACT   1975 May    336 #>  6 ACT   1975 Jun    374 #>  7 ACT   1975 Jul    372 #>  8 ACT   1975 Aug    354 #>  9 ACT   1975 Sep    361 #> 10 ACT   1975 Oct    337 #> # ℹ 4,502 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian women fertility rate — aus_fertility","title":"Australian women fertility rate — aus_fertility","text":"aus_fertility yearly `tsibble` one measured variable:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian women fertility rate — aus_fertility","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian women fertility rate — aus_fertility","text":"Australian Bureau Statistics. ","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian women fertility rate — aus_fertility","text":"series uniquely identified using two keys: based calendar year registration data. covers period 1975--2022.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_fertility.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian women fertility rate — aus_fertility","text":"","code":"aus_fertility #> # A tsibble: 15,120 x 4 [1Y] #> # Key:       Age, Region [315] #>     Year Region    Age    Rate #>            #>  1  1975 Australia 15      7   #>  2  1976 Australia 15      6.6 #>  3  1977 Australia 15      5.7 #>  4  1978 Australia 15      5.5 #>  5  1979 Australia 15      5.1 #>  6  1980 Australia 15      4.8 #>  7  1981 Australia 15      4.8 #>  8  1982 Australia 15      4.7 #>  9  1983 Australia 15      4.9 #> 10  1984 Australia 15      3.8 #> # ℹ 15,110 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":null,"dir":"Reference","previous_headings":"","what":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"aus_inbound monthly `tsibble` one measured variable:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"Tourism Research Australia","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"series uniquely identified using two keys: covering period Jan 2005--Feb 2020.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_inbound.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Monthly short term (<1 year) visitor arrivals to Australia — aus_inbound","text":"","code":"aus_inbound #> # A tsibble: 20,748 x 4 [1M] #> # Key:       Country, Purpose [114] #>       Month Country Purpose  Count #>                #>  1 2005 Jan Canada  Business 0.924 #>  2 2005 Feb Canada  Business 1.04  #>  3 2005 Mar Canada  Business 1.30  #>  4 2005 Apr Canada  Business 1.29  #>  5 2005 May Canada  Business 1.12  #>  6 2005 Jun Canada  Business 0.813 #>  7 2005 Jul Canada  Business 0.881 #>  8 2005 Aug Canada  Business 1.45  #>  9 2005 Sep Canada  Business 1.24  #> 10 2005 Oct Canada  Business 1.24  #> # ℹ 20,738 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian migration data — aus_migration","title":"Australian migration data — aus_migration","text":"Net Overseas Migration (NOM) Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian migration data — aus_migration","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian migration data — aus_migration","text":"Australian Bureau Statistics. . Cat . 310102.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian migration data — aus_migration","text":"aus_migration quarterly `tsibble` one measured variable: 1981 Q2 2023 Q3 6 states 2 territories Australia, indexed : NOM based international traveller's duration stay Australia 12 months , 16 month period. series uniquely identified using key:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_migration.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian migration data — aus_migration","text":"","code":"aus_migration #> # A tsibble: 1,360 x 3 [1Q] #> # Key:       State [8] #>    Quarter State   NOM #>         #>  1 1981 Q2 ACT    -131 #>  2 1981 Q3 ACT     152 #>  3 1981 Q4 ACT     383 #>  4 1982 Q1 ACT     419 #>  5 1982 Q2 ACT     271 #>  6 1982 Q3 ACT      80 #>  7 1982 Q4 ACT     209 #>  8 1983 Q1 ACT     283 #>  9 1983 Q2 ACT     -31 #> 10 1983 Q3 ACT     199 #> # ℹ 1,350 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian mortality data — aus_mortality","title":"Australian mortality data — aus_mortality","text":"Weekly death counts mortality rates Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian mortality data — aus_mortality","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian mortality data — aus_mortality","text":"https://mortality.org/Data/STMF (Downloaded 29 May 2024)","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian mortality data — aus_mortality","text":"aus_mortality weekly `tsibble` two measured variables: 2015 week 01 2023 week 12 five different age groups plus total, categorised sex. series uniquely identified using three keys: mortality rate defined number deaths per thousand people Australia week.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_mortality.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian mortality data — aus_mortality","text":"","code":"aus_mortality #> # A tsibble: 7,740 x 5 [1W] #> # Key:       Sex, Age [18] #>        Week Sex   Age   Deaths Mortality #>                #>  1 2015 W01 Both  0-14    31.1  0.000360 #>  2 2015 W02 Both  0-14    29.0  0.000334 #>  3 2015 W03 Both  0-14    27.5  0.000318 #>  4 2015 W04 Both  0-14    27.8  0.000321 #>  5 2015 W05 Both  0-14    26.0  0.000300 #>  6 2015 W06 Both  0-14    28.5  0.000330 #>  7 2015 W07 Both  0-14    29.4  0.000339 #>  8 2015 W08 Both  0-14    31.2  0.000361 #>  9 2015 W09 Both  0-14    27.9  0.000322 #> 10 2015 W10 Both  0-14    29.0  0.000334 #> # ℹ 7,730 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":null,"dir":"Reference","previous_headings":"","what":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"aus_outbound monthly `tsibble` one measured variable:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"Tourism Research Australia","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"series uniquely identified using two keys: covering period Jan 2005--Jun 2017.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_outbound.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Monthly short term (<1 year) resident departures in Australia — aus_outbound","text":"","code":"aus_outbound #> # A tsibble: 11,700 x 4 [1M] #> # Key:       Country, Purpose [78] #>       Month Country                               Purpose  Count #>                                              #>  1 2005 Jan China (excl SARs and Taiwan province) Business  5.75 #>  2 2005 Feb China (excl SARs and Taiwan province) Business  4.48 #>  3 2005 Mar China (excl SARs and Taiwan province) Business  7.05 #>  4 2005 Apr China (excl SARs and Taiwan province) Business  9.84 #>  5 2005 May China (excl SARs and Taiwan province) Business  6.05 #>  6 2005 Jun China (excl SARs and Taiwan province) Business  7.11 #>  7 2005 Jul China (excl SARs and Taiwan province) Business  6.56 #>  8 2005 Aug China (excl SARs and Taiwan province) Business  8.35 #>  9 2005 Sep China (excl SARs and Taiwan province) Business  7.97 #> 10 2005 Oct China (excl SARs and Taiwan province) Business  8.68 #> # ℹ 11,690 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian cigarette and tobacco expenditure — aus_tobacco","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"total household expenditure cigarette tobacco consumption (CTC) Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"Australian Bureau Statistics. ","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"aus_tobacco quarterly `tsibble` one value: 1985 Q3 2023 Q4 6 states 2 territories Australia, indexed : prices represented chain volume measure (representation constant prices) billions dollars. series uniquely identified using key:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_tobacco.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian cigarette and tobacco expenditure — aus_tobacco","text":"","code":"aus_tobacco |> autoplot(Expenditure) + scale_y_log10()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":null,"dir":"Reference","previous_headings":"","what":"Australian vehicle sales — aus_vehicle_sales","title":"Australian vehicle sales — aus_vehicle_sales","text":"number new motor vehicles sold Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Australian vehicle sales — aus_vehicle_sales","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Australian vehicle sales — aus_vehicle_sales","text":"Australian Bureau Statistics. . Cat . 931401.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Australian vehicle sales — aus_vehicle_sales","text":"aus_vehicle_sales monthly `tsibble` one measured variable: January 1994 December 2017 Australia, indexed : series uniquely identified using key:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/aus_vehicle_sales.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Australian vehicle sales — aus_vehicle_sales","text":"","code":"aus_vehicle_sales #> # A tsibble: 864 x 3 [1M] #> # Key:       Type [3] #>       Month Type  Count #>          #>  1 1994 Jan Other  5.46 #>  2 1994 Feb Other  7.42 #>  3 1994 Mar Other 10.3  #>  4 1994 Apr Other  8.02 #>  5 1994 May Other 10.2  #>  6 1994 Jun Other 15.8  #>  7 1994 Jul Other  7.36 #>  8 1994 Aug Other  8.40 #>  9 1994 Sep Other  8.13 #> 10 1994 Oct Other  9.17 #> # ℹ 854 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":null,"dir":"Reference","previous_headings":"","what":"Call volume for a large North American commercial bank — bank_calls","title":"Call volume for a large North American commercial bank — bank_calls","text":"Five-minute call volume handled weekdays 7:00am 9:05pm, beginning 3 March 24 October 2003 (164 days).","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Call volume for a large North American commercial bank — bank_calls","text":"Time series class `tsibble` 5 minute intervals.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Call volume for a large North American commercial bank — bank_calls","text":"Jonathan Weinberg","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Call volume for a large North American commercial bank — bank_calls","text":"Weinberg, Brown & Stroud (2007) \"Bayesian forecasting inhomogeneous Poisson process applications call center data\" Journal American Statistical Associiation, 102:480, 1185-1198.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/bank_calls.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Call volume for a large North American commercial bank — bank_calls","text":"","code":"bank_calls #> # A tsibble: 27,716 x 2 [5m]  #>    DateTime            Calls #>                   #>  1 2003-03-03 07:00:00   111 #>  2 2003-03-03 07:05:00   113 #>  3 2003-03-03 07:10:00    76 #>  4 2003-03-03 07:15:00    82 #>  5 2003-03-03 07:20:00    91 #>  6 2003-03-03 07:25:00    87 #>  7 2003-03-03 07:30:00    75 #>  8 2003-03-03 07:35:00    89 #>  9 2003-03-03 07:40:00    99 #> 10 2003-03-03 07:45:00   125 #> # ℹ 27,706 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/boston_marathon.html","id":null,"dir":"Reference","previous_headings":"","what":"Boston marathon winning times since 1897 — boston_marathon","title":"Boston marathon winning times since 1897 — boston_marathon","text":"Winning times events Boston Marathon. 1897-2019.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/boston_marathon.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Boston marathon winning times since 1897 — boston_marathon","text":"Annual time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/boston_marathon.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Boston marathon winning times since 1897 — boston_marathon","text":"Boston Athletic Association. https://www.baa.org/races/boston-marathon/results/champions","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/boston_marathon.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Boston marathon winning times since 1897 — boston_marathon","text":"","code":"boston_marathon #> # A tsibble: 265 x 5 [1Y] #> # Key:       Event [5] #>    Event                Year Champion            Country       Time       #>                                                  #>  1 Men's open division  1897 John J. McDermott   United States 10510 secs #>  2 Men's open division  1898 Ronald J. MacDonald Canada         9720 secs #>  3 Men's open division  1899 Lawrence Brignolia  United States 10478 secs #>  4 Men's open division  1900 John P. Caffery     Canada         9584 secs #>  5 Men's open division  1901 John P. Caffery     Canada         8963 secs #>  6 Men's open division  1902 Sammy A. Mellor     United States  9792 secs #>  7 Men's open division  1903 John C. Lorden      United States  9689 secs #>  8 Men's open division  1904 Michael Spring      United States  9484 secs #>  9 Men's open division  1905 Frederick Lorz      United States  9505 secs #> 10 Men's open division  1906 Timothy Ford        United States  9945 secs #> # ℹ 255 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":null,"dir":"Reference","previous_headings":"","what":"Monthly Canadian gas production — canadian_gas","title":"Monthly Canadian gas production — canadian_gas","text":"Monthly Canadian gas production, billions cubic metres, January 1960 - February 2005","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Monthly Canadian gas production — canadian_gas","text":"Monthly time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Monthly Canadian gas production — canadian_gas","text":"Hyndman, R.J., Koehler, .B., Ord, J.K., Snyder, R.D., (2008) Forecasting exponential smoothing: state space approach, Springer.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Monthly Canadian gas production — canadian_gas","text":"http://www.exponentialsmoothing.net","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/canadian_gas.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Monthly Canadian gas production — canadian_gas","text":"","code":"canadian_gas #> # A tsibble: 542 x 2 [1M] #>       Month Volume #>          #>  1 1960 Jan  1.43  #>  2 1960 Feb  1.31  #>  3 1960 Mar  1.40  #>  4 1960 Apr  1.17  #>  5 1960 May  1.12  #>  6 1960 Jun  1.01  #>  7 1960 Jul  0.966 #>  8 1960 Aug  0.977 #>  9 1960 Sep  1.03  #> 10 1960 Oct  1.25  #> # ℹ 532 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3-package.html","id":null,"dir":"Reference","previous_headings":"","what":"fpp3: Data for ","title":"fpp3: Data for ","text":"data sets required examples exercises book \"Forecasting: principles practice\" Rob J Hyndman George Athanasopoulos https://OTexts.com/fpp3/. packages required run examples also loaded. Additional data sets used book also included.","code":""},{"path":[]},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"fpp3: Data for ","text":"Maintainer: Rob Hyndman Rob.Hyndman@monash.edu (ORCID) [copyright holder] contributors: George Athanasopoulos [contributor] Mitchell O'Hara-Wild [contributor] Nuwani Palihawadana [contributor] Shanika Wickramasuriya [contributor] RStudio [copyright holder]","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":null,"dir":"Reference","previous_headings":"","what":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"function lists conflicts packages fpp3 collection packages loaded.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"","code":"fpp3_conflicts()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"list object class fpp3_conflicts.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"conflicts deliberately ignored: intersect, union, setequal, setdiff dplyr; intersect, union, setdiff, .difftime lubridate. functions make base equivalents generic, negatively affect existing code.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_conflicts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Conflicts between fpp3 packages and other packages — fpp3_conflicts","text":"","code":"fpp3_conflicts() #> ── Conflicts ───────────────────────────────────────────────── fpp3_conflicts ── #> ✖ lubridate::date()    masks base::date() #> ✖ dplyr::filter()      masks stats::filter() #> ✖ tsibble::intersect() masks base::intersect() #> ✖ tsibble::interval()  masks lubridate::interval() #> ✖ dplyr::lag()         masks stats::lag() #> ✖ tsibble::setdiff()   masks base::setdiff() #> ✖ tsibble::union()     masks base::union()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":null,"dir":"Reference","previous_headings":"","what":"List all packages loaded by fpp3 — fpp3_packages","title":"List all packages loaded by fpp3 — fpp3_packages","text":"List packages loaded fpp3","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"List all packages loaded by fpp3 — fpp3_packages","text":"","code":"fpp3_packages(include_self = FALSE)"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"List all packages loaded by fpp3 — fpp3_packages","text":"include_self Include fpp3 list?","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"List all packages loaded by fpp3 — fpp3_packages","text":"character vector package names.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/fpp3_packages.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"List all packages loaded by fpp3 — fpp3_packages","text":"","code":"fpp3_packages() #>  [1] \"cli\"         \"crayon\"      \"dplyr\"       \"fable\"       \"fabletools\"  #>  [6] \"feasts\"      \"ggplot2\"     \"lubridate\"   \"purrr\"       \"rstudioapi\"  #> [11] \"tibble\"      \"tidyr\"       \"tsibble\"     \"tsibbledata\""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/guinea_rice.html","id":null,"dir":"Reference","previous_headings":"","what":"Rice production (Guinea) — guinea_rice","title":"Rice production (Guinea) — guinea_rice","text":"Total annual rice production (million metric tons) Guinea. 1970-2011.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/guinea_rice.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Rice production (Guinea) — guinea_rice","text":"Annual time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/guinea_rice.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Rice production (Guinea) — guinea_rice","text":"World Bank.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/guinea_rice.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Rice production (Guinea) — guinea_rice","text":"","code":"guinea_rice #> # A tsibble: 42 x 2 [1Y] #>     Year Production #>           #>  1  1970      0.311 #>  2  1971      0.325 #>  3  1972      0.340 #>  4  1973      0.355 #>  5  1974      0.370 #>  6  1975      0.387 #>  7  1976      0.404 #>  8  1977      0.422 #>  9  1978      0.440 #> 10  1979      0.460 #> # ℹ 32 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/insurance.html","id":null,"dir":"Reference","previous_headings":"","what":"Insurance quotations and advertising expenditure — insurance","title":"Insurance quotations and advertising expenditure — insurance","text":"Monthly quotations monthly television advertising expenditure US insurance company. January 2002 April 2005","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/insurance.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Insurance quotations and advertising expenditure — insurance","text":"Monthly time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/insurance.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Insurance quotations and advertising expenditure — insurance","text":"Kindly provided Dave Reilly, Automatic Forecasting Systems.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/insurance.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Insurance quotations and advertising expenditure — insurance","text":"","code":"insurance |>   ggplot(aes(x=TVadverts, y=Quotes)) + geom_point()"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/melb_walkers.html","id":null,"dir":"Reference","previous_headings":"","what":"Average daily total pedestrian count in Melbourne — melb_walkers","title":"Average daily total pedestrian count in Melbourne — melb_walkers","text":"Daily average total pedestrian count (across different sensors) thousands 2019-01-01 2024-05-29.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/melb_walkers.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Average daily total pedestrian count in Melbourne — melb_walkers","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/melb_walkers.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Average daily total pedestrian count in Melbourne — melb_walkers","text":"Melbourne Open Data Portal. ","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/melb_walkers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Average daily total pedestrian count in Melbourne — melb_walkers","text":"","code":"autoplot(melb_walkers) #> Plot variable not specified, automatically selected `.vars = Count`"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":null,"dir":"Reference","previous_headings":"","what":"Monthly offences in NSW — nsw_offences","title":"Monthly offences in NSW — nsw_offences","text":"nsw_offences monthly `tsibble` one measured variable:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Monthly offences in NSW — nsw_offences","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Monthly offences in NSW — nsw_offences","text":"NSW Bureau Crime Statistics Research. ","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Monthly offences in NSW — nsw_offences","text":"series uniquely identified using one key: covering period Apr 1995--Dec 2023.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/nsw_offences.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Monthly offences in NSW — nsw_offences","text":"","code":"nsw_offences #> # A tsibble: 7,308 x 3 [1M] #> # Key:       Type [21] #>       Month Type                     Count #>                             #>  1 1995 Jan Abduction and kidnapping    15 #>  2 1995 Feb Abduction and kidnapping    16 #>  3 1995 Mar Abduction and kidnapping    23 #>  4 1995 Apr Abduction and kidnapping    22 #>  5 1995 May Abduction and kidnapping    14 #>  6 1995 Jun Abduction and kidnapping    13 #>  7 1995 Jul Abduction and kidnapping    19 #>  8 1995 Aug Abduction and kidnapping    23 #>  9 1995 Sep Abduction and kidnapping    13 #> 10 1995 Oct Abduction and kidnapping    21 #> # ℹ 7,298 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":null,"dir":"Reference","previous_headings":"","what":"New York childcare data — ny_childcare","title":"New York childcare data — ny_childcare","text":"number employees (thousands) child day care services New York City period period January 1990 April 2024.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"New York childcare data — ny_childcare","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"New York childcare data — ny_childcare","text":"U.S. Bureau Labor Statistics Federal Reserve Bank St. Louis, Employees: Education Health Services: Child Care Services New York City, NY retrieved FRED, Federal Reserve Bank St. Louis; , 30 May 2024.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"New York childcare data — ny_childcare","text":"ny_childcare monthly `tsibble` two columns:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/ny_childcare.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"New York childcare data — ny_childcare","text":"","code":"ny_childcare #> # A tsibble: 412 x 2 [1M] #>       Month Count #>         #>  1 1990 Jan  14.1 #>  2 1990 Feb  14.1 #>  3 1990 Mar  14.2 #>  4 1990 Apr  14   #>  5 1990 May  14   #>  6 1990 Jun  14   #>  7 1990 Jul  13.3 #>  8 1990 Aug  13.2 #>  9 1990 Sep  13.9 #> 10 1990 Oct  14.1 #> # ℹ 402 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/otexts_views.html","id":null,"dir":"Reference","previous_headings":"","what":"OTexts page views — otexts_views","title":"OTexts page views — otexts_views","text":"Daily page views OTexts website  recorded Google analytics.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/otexts_views.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"OTexts page views — otexts_views","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/otexts_views.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"OTexts page views — otexts_views","text":"otexts_views daily `tsibble` two columns:","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/otexts_views.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"OTexts page views — otexts_views","text":"","code":"otexts_views #> # A tsibble: 1,561 x 2 [1D] #>    Date       Pageviews #>              #>  1 2018-01-01      2.13 #>  2 2018-01-02      4.07 #>  3 2018-01-03      6.27 #>  4 2018-01-04      5.96 #>  5 2018-01-05      6.34 #>  6 2018-01-06      4.13 #>  7 2018-01-07      3.70 #>  8 2018-01-08      5.92 #>  9 2018-01-09      7.38 #> 10 2018-01-10      7.81 #> # ℹ 1,551 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/prices.html","id":null,"dir":"Reference","previous_headings":"","what":"Price series for various commodities — prices","title":"Price series for various commodities — prices","text":"Annual prices eggs, chicken, copper, nails, oil wheat. Eggs, chicken, nails, oil copper $US; wheat British pounds. prices adjusted inflation.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/prices.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Price series for various commodities — prices","text":"Annual time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/prices.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Price series for various commodities — prices","text":"Makridakis, Wheelwright Hyndman (1998) *Forecasting: methods applications*, John Wiley & Sons: New York. Chapter 9.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/prices.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Price series for various commodities — prices","text":"","code":"prices |> autoplot(wheat) #> Warning: Removed 1 row containing missing values or values outside the scale range #> (`geom_line()`)."},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/souvenirs.html","id":null,"dir":"Reference","previous_headings":"","what":"Sales for a souvenir shop — souvenirs","title":"Sales for a souvenir shop — souvenirs","text":"Monthly sales souvenir shop wharf beach resort town Queensland, Australia.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/souvenirs.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Sales for a souvenir shop — souvenirs","text":"Monthly time series class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/souvenirs.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Sales for a souvenir shop — souvenirs","text":"Makridakis, Wheelwright Hyndman (1998) *Forecasting: methods applications*, John Wiley & Sons: New York. Exercise 5.8.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/souvenirs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Sales for a souvenir shop — souvenirs","text":"","code":"souvenirs |> autoplot(Sales)"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_change.html","id":null,"dir":"Reference","previous_headings":"","what":"Percentage changes in economic variables in the USA. — us_change","title":"Percentage changes in economic variables in the USA. — us_change","text":"us_change quarterly `tsibble` containing percentage changes quarterly personal consumption expenditure, personal disposable income, production, savings unemployment rate US, 1970 2016. Original $ values chained 2012 US dollars.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_change.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Percentage changes in economic variables in the USA. — us_change","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_change.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Percentage changes in economic variables in the USA. — us_change","text":"Federal Reserve Bank St Louis.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_change.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Percentage changes in economic variables in the USA. — us_change","text":"","code":"us_change #> # A tsibble: 198 x 6 [1Q] #>    Quarter Consumption Income Production Savings Unemployment #>                                 #>  1 1970 Q1       0.619  1.04      -2.45    5.30         0.9   #>  2 1970 Q2       0.452  1.23      -0.551   7.79         0.5   #>  3 1970 Q3       0.873  1.59      -0.359   7.40         0.5   #>  4 1970 Q4      -0.272 -0.240     -2.19    1.17         0.700 #>  5 1971 Q1       1.90   1.98       1.91    3.54        -0.100 #>  6 1971 Q2       0.915  1.45       0.902   5.87        -0.100 #>  7 1971 Q3       0.794  0.521      0.308  -0.406        0.100 #>  8 1971 Q4       1.65   1.16       2.29   -1.49         0     #>  9 1972 Q1       1.31   0.457      4.15   -4.29        -0.200 #> 10 1972 Q2       1.89   1.03       1.89   -4.69        -0.100 #> # ℹ 188 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_employment.html","id":null,"dir":"Reference","previous_headings":"","what":"US monthly employment data — us_employment","title":"US monthly employment data — us_employment","text":"us_employment monthly `tsibble` containing US employment data January 1939 June 2019. `Series_ID` represents different sectors economy.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_employment.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"US monthly employment data — us_employment","text":"Time series class `tsibble`","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_employment.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"US monthly employment data — us_employment","text":"U.S. Bureau Labor Statistics","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_employment.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"US monthly employment data — us_employment","text":"","code":"us_employment #> # A tsibble: 143,412 x 4 [1M] #> # Key:       Series_ID [148] #>       Month Series_ID     Title         Employed #>                              #>  1 1939 Jan CEU0500000001 Total Private    25338 #>  2 1939 Feb CEU0500000001 Total Private    25447 #>  3 1939 Mar CEU0500000001 Total Private    25833 #>  4 1939 Apr CEU0500000001 Total Private    25801 #>  5 1939 May CEU0500000001 Total Private    26113 #>  6 1939 Jun CEU0500000001 Total Private    26485 #>  7 1939 Jul CEU0500000001 Total Private    26481 #>  8 1939 Aug CEU0500000001 Total Private    26848 #>  9 1939 Sep CEU0500000001 Total Private    27468 #> 10 1939 Oct CEU0500000001 Total Private    27830 #> # ℹ 143,402 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_gasoline.html","id":null,"dir":"Reference","previous_headings":"","what":"US finished motor gasoline product supplied. — us_gasoline","title":"US finished motor gasoline product supplied. — us_gasoline","text":"Weekly data beginning Week 6, 1991, ending Week 3, 2017. Units \"million barrels per day\".","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_gasoline.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"US finished motor gasoline product supplied. — us_gasoline","text":"Time series object class `tsibble`.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_gasoline.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"US finished motor gasoline product supplied. — us_gasoline","text":"US Energy Information Administration.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/reference/us_gasoline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"US finished motor gasoline product supplied. — us_gasoline","text":"","code":"us_gasoline #> # A tsibble: 1,355 x 2 [1W] #>        Week Barrels #>          #>  1 1991 W06    6.62 #>  2 1991 W07    6.43 #>  3 1991 W08    6.58 #>  4 1991 W09    7.22 #>  5 1991 W10    6.88 #>  6 1991 W11    6.95 #>  7 1991 W12    7.33 #>  8 1991 W13    6.78 #>  9 1991 W14    7.50 #> 10 1991 W15    6.92 #> # ℹ 1,345 more rows"},{"path":"https://pkg.robjhyndman.com/fpp3package/news/index.html","id":"fpp3-100","dir":"Changelog","previous_headings":"","what":"fpp3 1.0.0","title":"fpp3 1.0.0","text":"aus_births aus_fertility aus_inbound aus_mortality aus_migration aus_outbound aus_tobacco aus_vehicle_sales melb_walkers nsw_offences ny_childcare otexts_views","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/news/index.html","id":"fpp3-03","dir":"Changelog","previous_headings":"","what":"fpp3 0.3","title":"fpp3 0.3","text":"CRAN release: 2020-06-07 Updated objects work tsibble v0.9.0 Added series titles us_employment","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/news/index.html","id":"fpp3-02","dir":"Changelog","previous_headings":"","what":"fpp3 0.2","title":"fpp3 0.2","text":"CRAN release: 2020-03-15 Added aus_arrivals data set.","code":""},{"path":"https://pkg.robjhyndman.com/fpp3package/news/index.html","id":"fpp3-01","dir":"Changelog","previous_headings":"","what":"fpp3 0.1","title":"fpp3 0.1","text":"CRAN release: 2019-10-09 Initial version based tidyverse package Hadley Wickham. data ported fpp2. New data sets include us_employment.","code":""}]