Merge pull request #184 from cmu-delphi/dsweber2-post-cran

post-cran updates

Author: dshemetov

README.Rmd

@@ -16,21 +16,20 @@ ggplot2::theme_set(ggplot2::theme_bw())
 
 # Delphi Epidata R client
 
-
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-
-
-The [Delphi Epidata API](https://cmu-delphi.github.io/delphi-epidata/) provides real-time access to epidemiological surveillance data for influenza, COVID-19, and other diseases for the USA at various geographical resolutions, both from official government sources such as the [Center for Disease Control (CDC)](https://www.cdc.gov/datastatistics/index.html) and [Google Trends](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/google-symptoms.html) and private partners such as [Facebook](https://delphi.cmu.edu/blog/2020/08/26/covid-19-symptom-surveys-through-facebook/) and [Change Healthcare](https://www.changehealthcare.com/). It is built and maintained by the Carnegie Mellon University [Delphi research group](https://delphi.cmu.edu/).
+The [Delphi Epidatr package](https://cmu-delphi.github.io/epidatr/) is an R front-end for the [Delphi Epidata API](https://cmu-delphi.github.io/delphi-epidata/), which provides real-time access to epidemiological surveillance data for influenza, COVID-19, and other diseases for the USA at various geographical resolutions, both from official government sources such as the [Center for Disease Control (CDC)](https://www.cdc.gov/datastatistics/index.html) and [Google Trends](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/google-symptoms.html) and private partners such as [Facebook](https://delphi.cmu.edu/blog/2020/08/26/covid-19-symptom-surveys-through-facebook/) and [Change Healthcare](https://www.changehealthcare.com/). It is built and maintained by the Carnegie Mellon University [Delphi research group](https://delphi.cmu.edu/).
 
 This package is designed to streamline the downloading and usage of data from the [Delphi Epidata
 API](https://cmu-delphi.github.io/delphi-epidata/). It provides a simple R interface to the API, including functions for downloading data, parsing the results, and converting the data into a tidy format. The API stores a historical record of all data, including corrections and updates, which is particularly useful for accurately backtesting forecasting models. We also provide packages for downstream data processing ([epiprocess](https://github.com/cmu-delphi/epiprocess)) and modeling ([epipredict](https://github.com/cmu-delphi/epipredict)).
 
 ## Usage
 
+You can find detailed docs here: 
+
 ```{r}
 library(epidatr)
 # Obtain the smoothed covid-like illness (CLI) signal from the
@@ -63,16 +62,23 @@ ggplot(epidata, aes(x = time_value, y = value)) +
 
 ## Installation
 
-Install from GitHub:
+You can install the stable version of this package from CRAN:
+
+```R
+install.packages("epidatr")
+pak::pkg_install("epidatr")
+renv::install("epidatr")
+```
+
+Or if you want the development version, install from GitHub:
 
 ```R
 # Install the dev version using `pak` or `remotes`
 pak::pkg_install("cmu-delphi/epidatr")
 remotes::install_github("cmu-delphi/epidatr")
+renv::install("cmu-delphi/epidatr")
 ```
 
-CRAN version coming soon.
-
 ### API Keys
 
 The Delphi API requires a (free) API key for full functionality. To generate

README.md

@@ -12,11 +12,13 @@ Actions](https://github.com/cmu-delphi/epidatr/workflows/ci/badge.svg)](https://
 [![codecov](https://codecov.io/gh/dsweber2/epidatr/branch/dev/graph/badge.svg?token=jVHL9eHZNZ)](https://app.codecov.io/gh/dsweber2/epidatr)
 <!-- badges: end -->
 
-The [Delphi Epidata API](https://cmu-delphi.github.io/delphi-epidata/)
-provides real-time access to epidemiological surveillance data for
-influenza, COVID-19, and other diseases for the USA at various
-geographical resolutions, both from official government sources such as
-the [Center for Disease Control
+The [Delphi Epidatr package](https://cmu-delphi.github.io/epidatr/) is
+an R front-end for the [Delphi Epidata
+API](https://cmu-delphi.github.io/delphi-epidata/), which provides
+real-time access to epidemiological surveillance data for influenza,
+COVID-19, and other diseases for the USA at various geographical
+resolutions, both from official government sources such as the [Center
+for Disease Control
 (CDC)](https://www.cdc.gov/datastatistics/index.html) and [Google
 Trends](https://cmu-delphi.github.io/delphi-epidata/api/covidcast-signals/google-symptoms.html)
 and private partners such as
@@ -38,6 +40,8 @@ modeling ([epipredict](https://github.com/cmu-delphi/epipredict)).
 
 ## Usage
 
+You can find detailed docs here:
+
 ``` r
 library(epidatr)
 # Obtain the smoothed covid-like illness (CLI) signal from the
@@ -87,16 +91,23 @@ ggplot(epidata, aes(x = time_value, y = value)) +
 
 ## Installation
 
-Install from GitHub:
+You can install the stable version of this package from CRAN:
+
+``` r
+install.packages("epidatr")
+pak::pkg_install("epidatr")
+renv::install("epidatr")
+```
+
+Or if you want the development version, install from GitHub:
 
 ``` r
 # Install the dev version using `pak` or `remotes`
 pak::pkg_install("cmu-delphi/epidatr")
 remotes::install_github("cmu-delphi/epidatr")
+renv::install("cmu-delphi/epidatr")
 ```
 
-CRAN version coming soon.
-
 ### API Keys
 
 The Delphi API requires a (free) API key for full functionality. To