Re-export editing pass + don't re-export cumulative death data

Cumulative death data is in tibble format and isn't really the type of data we
expect in many functions. Probably not good to make it too accessible.

NAMESPACE

@@ -87,7 +87,6 @@ export(growth_rate)
 export(guess_period)
 export(is_epi_df)
 export(is_grouped_epi_archive)
-export(jhu_confirmed_cumulative_num)
 export(key_colnames)
 export(max_version_with_row_in)
 export(mutate)

R/reexports.R

@@ -139,26 +139,6 @@ delayedAssign("covid_incidence_county_subset", epidatasets::covid_incidence_coun
 #' @export
 delayedAssign("covid_incidence_outliers", epidatasets::covid_incidence_outliers)
 
-#' @inherit epidatasets::jhu_confirmed_cumulative_num description source references title
-#' @inheritSection epidatasets::jhu_confirmed_cumulative_num Data dictionary
-#' @examples
-#' # Since this is a re-exported dataset, it cannot be loaded using
-#' # the `data()` function. `data()` looks for a file of the same name
-#' # in the `data/` directory, which doesn't exist in this package.
-#' # works
-#' epiprocess::jhu_confirmed_cumulative_num
-#'
-#' # works
-#' library(epiprocess)
-#' jhu_confirmed_cumulative_num
-#'
-#' # fails
-#' \dontrun{
-#' data(jhu_confirmed_cumulative_num, package = "epiprocess")
-#' }
-#' @export
-delayedAssign("jhu_confirmed_cumulative_num", epidatasets::jhu_confirmed_cumulative_num)
-
 #' @inherit epidatasets::archive_cases_dv_subset description source references title
 #' @inheritSection epidatasets::archive_cases_dv_subset Data dictionary
 #' @examples

vignettes/aggregation.Rmd

@@ -22,7 +22,7 @@ library(covidcast)
 x <- covid_incidence_county_subset
 ```
 
-The data can also be fetched from the Delphi API with the following query:
+The data can also be fetched from the Delphi Epidata API with the following query:
 ```{r, message = FALSE, eval = FALSE, warning = FALSE}
 library(epidatr)
 

vignettes/archive.Rmd

@@ -36,10 +36,10 @@ library(ggplot2)
 
 # This fetches the raw data backing the archive_cases_dv_subset object.
 dv <- archive_cases_dv_subset$DT %>%
-  tibble()
+  as_tibble()
 ```
 
-The data can also be fetched from the Delphi API with the following query:
+The data can also be fetched from the Delphi Epidata API with the following query:
 ```{r, message = FALSE, warning = FALSE, eval = FALSE}
 library(epidatr)
 
@@ -84,8 +84,8 @@ print(x)
 ```
 
 An `epi_archive` is consists of a primary field `DT`, which is a data table
-(from the `data.table` package) that has the columns `geo_value`, `time_value`,
-`version` (and possibly additional ones), and other metadata fields, such as
+(from the `data.table` package) that has at least the required columns
+`geo_value`, `time_value`, and `version`; and other metadata fields, such as
 `geo_type`.
 
 The variables `geo_value`, `time_value`, `version` serve as **key variables**

vignettes/correlation.Rmd

@@ -23,11 +23,12 @@ library(dplyr)
 The data is included in this package (via the [`epidatasets` package](https://cmu-delphi.github.io/epidatasets/)) and can be loaded with:
 ```{r}
 x <- cases_deaths_subset %>%
-  select(geo_value, time_value, case_rate = case_rate_7d_av, death_rate = death_rate_7d_av) %>%
+  select(geo_value, time_value,
+         case_rate = case_rate_7d_av, death_rate = death_rate_7d_av) %>%
   arrange(geo_value, time_value)
 ```
 
-The data can also be fetched from the Delphi API with the following query:
+The data can also be fetched from the Delphi Epidata API with the following query:
 ```{r, eval = FALSE}
 library(epidatr)
 
@@ -36,21 +37,21 @@ d <- as.Date("2024-03-20")
 x <- pub_covidcast(
   source = "jhu-csse",
   signals = "confirmed_7dav_incidence_prop",
-  time_type = "day",
   geo_type = "state",
-  time_values = epirange(20200301, 20211231),
+  time_type = "day",
   geo_values = "*",
+  time_values = epirange(20200301, 20211231),
   as_of = d
 ) %>%
   select(geo_value, time_value, case_rate = value)
 
 y <- pub_covidcast(
   source = "jhu-csse",
   signals = "deaths_7dav_incidence_prop",
-  time_type = "day",
   geo_type = "state",
-  time_values = epirange(20200301, 20211231),
+  time_type = "day",
   geo_values = "*",
+  time_values = epirange(20200301, 20211231),
   as_of = d
 ) %>%
   select(geo_value, time_value, death_rate = value)

vignettes/epiprocess.Rmd

@@ -98,19 +98,20 @@ which we also broadly refer to as signal variables. The documentation for
 A data frame or tibble that has `geo_value` and `time_value` columns can be
 converted into an `epi_df` object, using the function `as_epi_df()`. As an
 example, we'll work with daily cumulative COVID-19 cases from four U.S. states:
-CA, FL, NY, and TX, over time span from mid 2020 to early 2022, and we'll use
-the [`epidatr`](https://github.com/cmu-delphi/epidatr) package
-to fetch this data from the [COVIDcast
-API](https://cmu-delphi.github.io/delphi-epidata/api/covidcast.html).
+CA, FL, NY, and TX, over time span from mid 2020 to early 2022. We have included
+this example data in the `epidatasets::jhu_confirmed_cumulative_num` object,
+which we prepared by downloading the data using `epidatr::pub_covidcast()`.
 
 ```{r, message = FALSE}
+library(epidatasets)
 library(epiprocess)
 library(dplyr)
 library(tidyr)
 library(withr)
 
 cases <- jhu_confirmed_cumulative_num
 
+class(cases)
 colnames(cases)
 ```
 

vignettes/growth_rate.Rmd

@@ -29,7 +29,7 @@ x <- cases_deaths_subset %>%
   arrange(geo_value, time_value)
 ```
 
-The data can also be fetched from the Delphi API with the following query:
+The data can also be fetched from the Delphi Epidata API with the following query:
 ```{r, message = FALSE, eval = FALSE}
 library(epidatr)
 

vignettes/outliers.Rmd

@@ -16,7 +16,7 @@ reported COVID-19 case counts from FL and NJ.
 
 The dataset has 730 rows and 3 columns.
 
-```{r, echo=FALSE, warning=FALSE, message=FALSE}
+```{r, echo=TRUE, warning=FALSE, message=FALSE}
 library(epiprocess)
 library(dplyr)
 library(tidyr)

vignettes/slide.Rmd

@@ -38,7 +38,7 @@ edf <- cases_deaths_subset %>%
   arrange(geo_value, time_value)
 ```
 
-The data can also be fetched from the Delphi API with the following query:
+The data can also be fetched from the Delphi Epidata API with the following query:
 ```{r, message = FALSE, eval = FALSE}
 library(epidatr)