Merge pull request #553 from cmu-delphi/ds/vignettes4

doc: fix archive demo and make epipredict a link

README.Rmd

@@ -16,7 +16,7 @@ knitr::opts_chunk$set(
 The `{epiprocess}` package works with epidemiological time series data and
 provides tools to manage, analyze, and process the data in preparation for
 modeling. It is designed to work in tandem with
-`{epipredict}`, which provides
+[`{epipredict}`](https://cmu-delphi.github.io/epipredict/), which provides
 pre-built epiforecasting models and as well as tools to build custom models.
 Both packages are designed to lower the barrier to entry and implementation cost
 for epidemiological time series analysis and forecasting.

README.md

@@ -6,10 +6,11 @@
 The `{epiprocess}` package works with epidemiological time series data
 and provides tools to manage, analyze, and process the data in
 preparation for modeling. It is designed to work in tandem with
-`{epipredict}`, which provides pre-built epiforecasting models and as
-well as tools to build custom models. Both packages are designed to
-lower the barrier to entry and implementation cost for epidemiological
-time series analysis and forecasting.
+[`{epipredict}`](https://cmu-delphi.github.io/epipredict/), which
+provides pre-built epiforecasting models and as well as tools to build
+custom models. Both packages are designed to lower the barrier to entry
+and implementation cost for epidemiological time series analysis and
+forecasting.
 
 `{epiprocess}` contains:
 

vignettes/epiprocess.Rmd

@@ -167,7 +167,10 @@ dv <- pub_covidcast(
   geo_values = "ca,fl,ny,tx",
   time_values = epirange(20200601, 20211201),
   issues = epirange(20200601, 20211201)
-)
+) %>%
+  select(geo_value, time_value, issue, percent_cli = value) %>%
+  as_epi_archive(compactify = TRUE)
+dv
 ```
 
 ```{r, echo=FALSE, message=FALSE, warning=FALSE}
@@ -179,10 +182,13 @@ library(purrr)
 library(ggplot2)
 dv <- archive_cases_dv_subset$DT %>%
   select(-case_rate_7d_av) %>%
-  rename(issue = version, value = percent_cli) %>%
-  tibble()
+  tidyr::drop_na() %>%
+  as_epi_archive(compactify = TRUE)
+dv
 ```
 
+See `vignette("epi_arcive")` for a more in-depth guide to `epi_archive` objects.
+
 ## Data attribution
 
 This document contains a dataset that is a modified part of the [COVID-19 Data