| Title: | Data for "Forecasting: Principles and Practice" (3rd Edition) |
| Version: | 1.0.1 |
| Description: | All data sets required for the examples and exercises in the book "Forecasting: principles and practice" by Rob J Hyndman and George Athanasopoulos https://OTexts.com/fpp3/. All packages required to run the examples are also loaded. Additional data sets not used in the book are also included. |
| License: | GPL-3 |
| URL: | https://pkg.robjhyndman.com/fpp3/, https://github.com/robjhyndman/fpp3, https://OTexts.com/fpp3/ |
| BugReports: | https://github.com/robjhyndman/fpp3/issues |
| Depends: | R (≥ 4.1.0) |
| Imports: | cli (≥ 1.0.0), crayon (≥ 1.3.4), dplyr (≥ 0.7.4), fable (≥ 0.3.0), fabletools (≥ 0.3.0), feasts (≥ 0.1.7), ggplot2 (≥ 3.1.1), lubridate (≥ 1.7.4), purrr (≥ 0.2.4), rstudioapi (≥ 0.7), tibble (≥ 1.4.2), tidyr (≥ 0.8.3), tsibble (≥ 0.9.3), tsibbledata (≥ 0.2.0) |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.3.2 |
| NeedsCompilation: | no |
| Packaged: | 2024-09-18 01:10:06 UTC; hyndman |
| Author: | Rob Hyndman  [aut,
cre, cph],
George Athanasopoulos [ctb],
Mitchell O'Hara-Wild [ctb],
Nuwani Palihawadana [ctb],
Shanika Wickramasuriya [ctb],
RStudio [cph] |
| Maintainer: | Rob Hyndman <Rob.Hyndman@monash.edu> |
| Repository: | CRAN |
| Date/Publication: | 2024-09-18 02:20:02 UTC |
fpp3: Data for "Forecasting: Principles and Practice" (3rd Edition)
Description
All data sets required for the examples and exercises in the book "Forecasting: principles and practice" by Rob J Hyndman and George Athanasopoulos https://OTexts.com/fpp3/. All packages required to run the examples are also loaded. Additional data sets not used in the book are also included.
Author(s)
Maintainer: Rob Hyndman Rob.Hyndman@monash.edu (ORCID) [copyright holder]
Other contributors:
George Athanasopoulos [contributor]
Mitchell O'Hara-Wild [contributor]
Nuwani Palihawadana [contributor]
Shanika Wickramasuriya [contributor]
RStudio [copyright holder]
See Also
Useful links:
Report bugs at https://github.com/robjhyndman/fpp3/issues
Australian accommodation data
Description
aus_accommodation contains quarterly data on Australian tourist accommodation
from short-term non-residential accommodation with 15 or more rooms, 1998 Q1 - 2016 Q2.
The data set also contains the Australian Consumer Price Index (CPI) for the same period.
Takings are in millions of Australian dollars,
Occupancy is a percentage of rooms occupied,
CPI is an index with value 100 in 2012 Q1.
Format
Time series of class 'tsibble'
Source
Australian Bureau of Statistics, Cat No 8635.0, Table 10, and Cat No 6401.0, Table 1.
Examples
aus_accommodation
Air Transport Passengers Australia
Description
Total annual air passengers (in millions) including domestic and international aircraft passengers of air carriers registered in Australia. 1970-2016.
Format
Annual time series of class 'tsibble'.
Source
World Bank.
Examples
aus_airpassengers
International Arrivals to Australia
Description
Quarterly international arrivals to Australia from Japan, New Zealand, UK and the US. 1981Q1 - 2012Q3.
Format
Quarterly time series of class 'tsibble'.
Source
Tourism Research Australia.
Examples
aus_arrivals
Australian births data
Description
Number of births in Australia.
Format
Time series of class 'tsibble'
Details
aus_births contains monthly data with one measured variable:
Births: | Number of births |
from January 1975 to December 2021 for the 6 states and 2 territories of Australia, indexed by:
Month: | Year-month. |
#' Each series is uniquely identified using the key:
State: The state or territory. |
Source
Australian Bureau of Statistics. https://www.abs.gov.au/statistics/people/population/births-australia/2022
Examples
aus_births
Australian fertility rates
Description
aus_fertility contains annual data on one measured variable:
| Rate: | Fertility rate (per thousand women) |
Format
Time series of class 'tsibble'
Details
Each series is uniquely identified using two keys:
| Region: | Australia, states and territories |
| Age: | Age of the woman |
based on calendar year of registration data. It covers the period from 1975–2022.
Source
Australian Bureau of Statistics. https://www.abs.gov.au/statistics/people/population/births-australia/2022
Examples
aus_fertility
Monthly short term (<1 year) visitor arrivals to Australia
Description
aus_inbound contains monthly data with one measured variable:
| Count: | Number of individuals arriving in Australia |
Format
Time series of class 'tsibble'
Details
Each series is uniquely identified using two keys:
| County: | Country of stay/residence |
| Purpose: | Purpose of travel |
covering the period from Jan 2005–Feb 2020.
Source
Tourism Research Australia
Examples
aus_inbound
Australian migration data
Description
Net Overseas Migration (NOM) to Australia.
Format
Time series of class 'tsibble'
Details
aus_migration contains quarterly data with one measured variable:
NOM: | The net gain or loss of population through immigration to Australia and emigration from Australia |
from 1981 Q2 to 2023 Q3 for the 6 states and 2 territories of Australia, indexed by:
Quarter: | Year-quarter. |
NOM is based on an international traveller's duration of stay being in or out of Australia for 12 months or more, over a 16 month period.
Each series is uniquely identified using the key:
State: The state or territory. |
Source
Australian Bureau of Statistics. https://www.abs.gov.au/statistics/people/population/national-state-and-territory-population/dec-2023. Cat No. 310102.
Examples
aus_migration
Australian mortality data
Description
Weekly death counts and mortality rates in Australia.
Format
Time series of class 'tsibble'
Details
aus_mortality contains weekly data with two measured variables:
Deaths: | Death count |
Mortality: | Mortality rate |
from 2015 week 01 to 2023 week 12 for five different age groups plus the total, categorised by sex.
Each series is uniquely identified using three keys:
Sex: | Sex of the individual: Male, Female, or Both |
Age: | Age group of the individual |
The mortality rate is defined as the number of deaths per thousand people in Australia in each week.
Source
https://mortality.org/Data/STMF (Downloaded on 29 May 2024)
Examples
aus_mortality
Monthly short term (<1 year) resident departures in Australia
Description
aus_outbound contains monthly data with one measured variable:
| Count: | Number of individuals departing Australia |
Format
Time series of class 'tsibble'
Details
Each series is uniquely identified using two keys:
| County: | Destination |
| Purpose: | Purpose of travel |
covering the period from Jan 2005–Jun 2017.
Source
Tourism Research Australia
Examples
aus_outbound
Australian cigarette and tobacco expenditure
Description
The total household expenditure for cigarette and tobacco consumption (CTC) in Australia.
Format
Time series of class 'tsibble'
Details
aus_tobacco contains quarterly data with one measured variable:
Expenditure: | The total expenditure |
from 1985 Q3 to 2023 Q4 for the 6 states and 2 territories of Australia, indexed by:
Quarter: | Year-quarter. |
The prices are represented as a chain volume measure (a representation of constant prices) in billions of dollars.
Each series is uniquely identified using the key:
State: The state or territory. |
Source
Australian Bureau of Statistics. https://www.abs.gov.au/statistics/economy/national-accounts/australian-national-accounts-national-income-expenditure-and-product/mar-2024
Examples
aus_tobacco |> autoplot(Expenditure) + scale_y_log10()
Australian vehicle sales
Description
The number of new motor vehicles sold in Australia.
Format
Time series of class 'tsibble'
Details
aus_vehicle_sales contains monthly data with one measured variable:
Count: | The number of vehicles sold |
from January 1994 to December 2017 in Australia, indexed by:
Month: | Year-month. |
Each series is uniquely identified using the key:
Type: The type of the vehicle sold (Passenger, SUV, Other). |
Source
Australian Bureau of Statistics. https://www.abs.gov.au/statistics/industry/tourism-and-transport/sales-new-motor-vehicles/dec-2017. Cat No. 931401.
Examples
aus_vehicle_sales
Call volume for a large North American commercial bank
Description
Five-minute call volume handled on weekdays between 7:00am and 9:05pm, beginning 3 March and 24 October 2003 (164 days).
Format
Time series of class 'tsibble' at 5 minute intervals.
Source
Jonathan Weinberg
References
Weinberg, Brown & Stroud (2007) "Bayesian forecasting of an inhomogeneous Poisson process with applications to call center data" Journal of the American Statistical Associiation, 102:480, 1185-1198.
Examples
bank_calls
Boston marathon winning times since 1897
Description
Winning times for events at the Boston Marathon. 1897-2019.
Format
Annual time series of class 'tsibble'.
Source
Boston Athletic Association. https://www.baa.org/races/boston-marathon/results/champions
Examples
boston_marathon
Monthly Canadian gas production
Description
Monthly Canadian gas production, billions of cubic metres, January 1960 - February 2005
Format
Monthly time series of class 'tsibble'.
Source
Hyndman, R.J., Koehler, A.B., Ord, J.K., and Snyder, R.D., (2008) Forecasting with exponential smoothing: the state space approach, Springer.
References
http://www.exponentialsmoothing.net
Examples
canadian_gas
Conflicts between fpp3 packages and other packages
Description
This function lists all the conflicts between packages in the fpp3 collection and other packages that you have loaded.
Usage
fpp3_conflicts()
Details
Some conflicts are deliberately ignored: intersect, union,
setequal, and setdiff from dplyr; and intersect,
union, setdiff, and as.difftime from lubridate.
These functions make the base equivalents generic, so shouldn't negatively affect any
existing code.
Value
A list object of class fpp3_conflicts.
Examples
fpp3_conflicts()
List all packages loaded by fpp3
Description
List all packages loaded by fpp3
Usage
fpp3_packages(include_self = FALSE)
Arguments
include_self |
Include fpp3 in the list? |
Value
A character vector of package names.
Examples
fpp3_packages()
Rice production (Guinea)
Description
Total annual rice production (million metric tons) for Guinea. 1970-2011.
Format
Annual time series of class 'tsibble'.
Source
World Bank.
Examples
guinea_rice
Insurance quotations and advertising expenditure
Description
Monthly quotations and monthly television advertising expenditure for a US insurance company. January 2002 to April 2005
Format
Monthly time series of class 'tsibble'.
Source
Kindly provided by Dave Reilly, Automatic Forecasting Systems.
Examples
insurance |>
ggplot(aes(x=TVadverts, y=Quotes)) + geom_point()
Average daily total pedestrian count in Melbourne
Description
Daily average total pedestrian count (across different sensors) from 2019-01-01 to 2024-05-29.
Format
Time series of class 'tsibble'
Source
Melbourne Open Data Portal. https://data.melbourne.vic.gov.au
Examples
melb_walkers |> autoplot(Count)
Monthly offences in NSW
Description
nsw_offences contains monthly data with one measured variable:
| Count: | Number of offences reported |
Format
Time series of class 'tsibble'
Details
Each series is uniquely identified using one key:
| Type: | Offence type |
covering the period from Apr 1995–Dec 2023.
Source
NSW Bureau of Crime Statistics and Research. https://bocsar.nsw.gov.au/
Examples
nsw_offences
New York childcare data
Description
The number of employees (in thousands) in child day care services in New York City over the period the period from January 1990 to April 2024.
Format
Time series of class 'tsibble'
Details
ny_childcare contains monthly data with two columns:
Month: | Year-month |
Count: | Number of employees. |
Source
U.S. Bureau of Labor Statistics and Federal Reserve Bank of St. Louis, All Employees: Education and Health Services: Child Care Services in New York City, NY retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/SMU36935616562440001, 30 May 2024.
Examples
ny_childcare
OTexts page views
Description
Daily page views on the OTexts website https://OTexts.com/ as recorded by Google analytics.
Format
Time series of class 'tsibble'
Details
otexts_views contains daily data with two columns:
Date: | Date for which the page views are recorded |
Pageviews: | Page views on the OTexts website |
Examples
otexts_views
Price series for various commodities
Description
Annual prices for eggs, chicken, copper, nails, oil and wheat. Eggs, chicken, nails, oil and copper in $US; wheat in British pounds. All prices adjusted for inflation.
Format
Annual time series of class 'tsibble'.
Source
Makridakis, Wheelwright and Hyndman (1998) *Forecasting: methods and applications*, John Wiley & Sons: New York. Chapter 9.
Examples
prices |> autoplot(wheat)
Sales for a souvenir shop
Description
Monthly sales for a souvenir shop on the wharf at a beach resort town in Queensland, Australia.
Format
Monthly time series of class 'tsibble'.
Source
Makridakis, Wheelwright and Hyndman (1998) *Forecasting: methods and applications*, John Wiley & Sons: New York. Exercise 5.8.
Examples
souvenirs |> autoplot(Sales)
Percentage changes in economic variables in the USA.
Description
us_change contains percentage changes in
quarterly personal consumption expenditure, personal disposable income,
production, savings and the unemployment rate for the US, 1970 to 2016.
Original $ values were in chained 2012 US dollars.
Format
Time series of class 'tsibble'
Source
Federal Reserve Bank of St Louis.
Examples
us_change
US monthly employment data
Description
us_employment contains monthly US employment data from January 1939
to June 2019. Each 'Series_ID' represents different sectors of the economy.
Format
Time series of class 'tsibble'
Source
U.S. Bureau of Labor Statistics
Examples
us_employment
US finished motor gasoline product supplied.
Description
Weekly data beginning Week 6, 1991, and ending Week 3, 2017. Units are "million barrels per day".
Format
Time series object of class 'tsibble'.
Source
US Energy Information Administration.
Examples
us_gasoline