Use here::here when reading data-raw files

data-raw/AUS_CigTob_Exp/AUS_CigTob_Exp.R

@@ -7,7 +7,7 @@ library(fpp3)
 # for Victoria), and merged the respective cigarettes and tobacco expenditure
 # data into a single data set.
 
-aus_tobacco <- readxl::read_xlsx(path ="data-raw/AUS_CigTob_Exp/CigTob_Updated.xlsx") |>
+aus_tobacco <- readxl::read_xlsx(path = here::here("data-raw/AUS_CigTob_Exp/CigTob_Updated.xlsx")) |>
   mutate(Quarter = yearquarter(Quarter)) |>
   pivot_longer(VIC:ACT, names_to = "State", values_to = "Expenditure") |>
   mutate(Expenditure = Expenditure / 1e3) |>

data-raw/AUS_Fertility/aus_fertility.R

@@ -3,7 +3,7 @@ library(fpp3)
 # Data downloaded from https://www.abs.gov.au/statistics/people/population/births-australia/2022
 # Fertility, by age, by state of usual residence
 # on 30 May 2024
-aus_fertility <- readr::read_csv("data-raw/AUS_Fertility/ABS_FERTILITY_AGE_STATE_1.0.0_...A.csv")
+aus_fertility <- readr::read_csv(here::here("data-raw/AUS_Fertility/ABS_FERTILITY_AGE_STATE_1.0.0_...A.csv"))
 aus_fertility <- aus_fertility |>
   filter(`MEASURE: Measure` == "11: Fertility rate") |>
   select(-c(DATAFLOW, `MEASURE: Measure`, `FREQ: Frequency`, `UNIT_MEASURE: Unit of Measure`,

data-raw/AUS_accommodation/aus_accommodation.R

@@ -1,8 +1,7 @@
-library(tsibble)
-library(tidyverse)
+library(fpp3)
 library(readabs)
 
-aus_accommodation <- read_abs_local(filenames="8635010.xlsx", path="data-raw/AUS_accommodation/") |>
+aus_accommodation <- read_abs_local(filenames="8635010.xlsx", path=here::here("data-raw/AUS_accommodation/")) |>
   filter(series_type == "Original") |>
   mutate(
     Date = yearquarter(date),
@@ -20,7 +19,7 @@ aus_accommodation <- read_abs_local(filenames="8635010.xlsx", path="data-raw/AUS
   filter(State != "Total (Area)") |>
   as_tsibble(index=Date, key=State)
 
-cpi <- read_abs_local(filenames="640101.xlsx", path="data-raw/AUS_accommodation/") |>
+cpi <- read_abs_local(filenames="640101.xlsx", path=here::here("data-raw/AUS_accommodation/")) |>
   filter(str_detect(series,"Australia"), data_type=="INDEX") |>
   mutate(Date = yearquarter(date)) |>
   select(Date, value) |>

data-raw/US_change/uschange.R

@@ -5,7 +5,7 @@ library(tsibble)
 # Downloaded from https://research.stlouisfed.org/pdl/1216/
 
 # Read monthly unemployment data
-unrate <- read_tsv("data-raw/US_change/uschange_fpp3_Monthly.txt") |>
+unrate <- read_tsv(here::here("data-raw/US_change/uschange_fpp3_Monthly.txt")) |>
   mutate(Month = yearmonth(observation_date)) |>
   select(Month, everything(), -observation_date) |>
   rename(Unemployment = UNRATE_20191004) |>
@@ -19,7 +19,7 @@ unrate <- unrate |>
   filter_index("1969 Q4" ~ .)
 
 # Read remaining quarterly data
-other <- read_tsv("data-raw/US_change/uschange_fpp3_Quarterly.txt", na=c("",".")) |>
+other <- read_tsv(here::here("data-raw/US_change/uschange_fpp3_Quarterly.txt"), na=c("",".")) |>
   mutate(Quarter = yearquarter(observation_date)) |>
   select(Quarter, everything(), -observation_date) |>
   rename(

data-raw/US_employment/US_employment.R

@@ -5,7 +5,7 @@ library(tsibble)
 # Data download from https://research.stlouisfed.org/pdl/1215
 
 us_employment <- read_tsv(
-  "data-raw/US_employment/US_employment_fpp3_Monthly.txt",
+  here::here("data-raw/US_employment/US_employment_fpp3_Monthly.txt"),
   col_types = cols(
     .default = col_double(),
     observation_date = col_date(format = "")
@@ -16,7 +16,7 @@ us_employment <- read_tsv(
   separate(Series_ID, "Series_ID", extra = "drop") |>
   as_tsibble(key = Series_ID, index=Month)
 
-readme <- read_lines("data-raw/US_employment/US_employment_fpp3_README.txt") |>
+readme <- read_lines(here::here("data-raw/US_employment/US_employment_fpp3_README.txt")) |>
   {split(., cumsum(str_detect(., "Series ID")))[-1]} |>
   map_dfr(function(desc){
     desc <- desc[seq_len(str_which(desc, "The source code is") - 1)]