Merge pull request #3 from slu-openGIS/cran-release

Cran release

CRAN-RELEASE

@@ -0,0 +1,2 @@
+This package was submitted to CRAN on 2019-07-22.
+Once it is accepted, delete this file and tag the release (commit 2af548182c).

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: censusxy
 Title: Access the U.S. Census Bureau Geocoder
-Version: 0.1.0
+Version: 0.1.1
 Authors@R: c(
     person("Christopher", "Prener", ,"[email protected]", c("aut", "cre"),
     comment = c(ORCID = "0000-0002-4310-9888")),
@@ -9,11 +9,12 @@ Authors@R: c(
     )
 Description: Provides access to the U.S. Census Bureau's API for batch geocoding 
     American street addresses (<https://geocoding.geo.census.gov/geocoder>).
-    The package offers a vectorized solution for address geocoding. It was also 
-    developed specifically with large data sets in mind - only unique addresses 
-    are passed to the API for geocoding. If a data set exceeds 1,000 unique addresses, 
-    it will be automatically subset into appropriately sized API calls, geocoded, and 
-    then put back together so that a single object is returned.
+    The package offers a batch solution for address geocoding, as opposed to geocoding
+    a single address at a time. It has also been developed specifically with large 
+    data sets in mind - only unique addresses are passed to the API for geocoding. 
+    If a data set exceeds 1,000 unique addresses, it will be automatically subset 
+    into appropriately sized API calls, geocoded, and then put back together so that 
+    a single object is returned.
 Depends: R (>= 3.3)
 License: GPL-3
 URL: https://github.com/slu-openGIS/censusxy

NEWS.md

@@ -1,3 +1,9 @@
+# censusxy 0.1.1
+
+* CRAN release version of the software.
+* Corrected tense shifts in description paragraph in `DESCRIPTION`, `README.Rmd`, and `index.Rmd`
+* Other minor updates to `pkgdown` site and `README.Rmd`
+
 # censusxy 0.1.0
 
 * Added a `NEWS.md` file to track changes to the package.

R/cxy_geocode.R

@@ -24,10 +24,21 @@
 #' @importFrom rlang enquo quo_name
 #' @importFrom sf st_as_sf
 #'
+#' @examples
+#' # load sample data
+#' data <- stl_homicides_small
+#'
+#' # geocode data
+#' data <- cxy_geocode(data, address = "street_address", city = "city",
+#'     state = "state", zip = "postal_code")
+#'
+#' # preview data
+#' data
+#'
 #' @export
 cxy_geocode <- function(.data, address, city, state, zip, style = "minimal", output = "tibble", timeout = 30){
 
-  # global bindings
+   # global bindings
    lon = lat = NULL
 
    # check for missing parameters

README.Rmd

@@ -22,14 +22,20 @@ knitr::opts_chunk$set(
 [![DOI](https://zenodo.org/badge/165924122.svg)](https://zenodo.org/badge/latestdoi/165924122)
 [![CRAN_status_badge](http://www.r-pkg.org/badges/version/censusxy)](https://cran.r-project.org/package=censusxy)
 
-The `censusxy` package is designed to provide easy and efficient access to the [US Census Bureau Batch Geocoder](https://geocoding.geo.census.gov/geocoder/) in `R`. The package offers a vectorized solution for address geocoding (as opposed to packages like [`censusr`](https://CRAN.R-project.org/package=censusr), which provide functionality for a single address at a time). `censusxy` was also developed specifically with large data sets in mind - only unique addresses are passed to the API for geocoding. If a data set exceeds 1,000 unique addresses, it will be automatically subset into appropriately sized API calls, geocoded, and then put back together so that a single object is returned.
+The `censusxy` package is designed to provide easy and efficient access to the [U.S. Census Bureau Batch Geocoder](https://geocoding.geo.census.gov/geocoder/) in `R`. The package offers a batch solution for address geocoding (as opposed to packages like [`censusr`](https://CRAN.R-project.org/package=censusr), which provide functionality for a single address at a time). `censusxy` has also been developed specifically with large data sets in mind - only unique addresses are passed to the API for geocoding. If a data set exceeds 1,000 unique addresses, it will be automatically subset into appropriately sized API calls, geocoded, and then put back together so that a single object is returned.
 
 ## Installation
 ### Installing Dependencies
 You should check the [`sf` package website](https://r-spatial.github.io/sf/) and the [`censusxy` package website](https://slu-openGIS.github.io/censusxy/) for the latest details on installing dependencies for that package. Instructions vary significantly by operating system. For best results, have `sf` installed before you install `censusxy`. Other dependencies, like `dplyr`, will be installed automatically with `censusxy` if they are not already present.
 
 ### Installing censusxy
-The package is soon to be on CRAN, but meanwhile, the development version of `censusxy` can be accessed from GitHub with `remotes`:
+Once `sf` is installed, the easiest way to get `censusxy` is to install it from CRAN:
+
+```r
+install.packages("censusxy")
+```
+
+Alternatively, the development version of `censusxy` can be accessed from GitHub with `remotes`:
 
 ```r
 # install.packages("remotes")
@@ -59,7 +65,7 @@ If you request an `sf` object, you easily preview the results with the [`mapview
 ```r
 > mapview::mapview(homicide_sf)
 ```
-```{r exampleMap1, echo=FALSE, out.width = '60%'}
+```{r exampleMap1, echo=FALSE, out.width = '100%'}
 knitr::include_graphics("man/figures/homicide_example.png")
 ```
 

README.md

@@ -14,15 +14,14 @@ status](https://codecov.io/gh/slu-openGIS/censusxy/branch/master/graph/badge.svg
 [![CRAN\_status\_badge](http://www.r-pkg.org/badges/version/censusxy)](https://cran.r-project.org/package=censusxy)
 
 The `censusxy` package is designed to provide easy and efficient access
-to the [US Census Bureau Batch
+to the [U.S. Census Bureau Batch
 Geocoder](https://geocoding.geo.census.gov/geocoder/) in `R`. The
-package offers a vectorized solution for address geocoding (as opposed
-to packages like
-[`censusr`](https://CRAN.R-project.org/package=censusr), which provide
-functionality for a single address at a time). `censusxy` was also
-developed specifically with large data sets in mind - only unique
-addresses are passed to the API for geocoding. If a data set exceeds
-1,000 unique addresses, it will be automatically subset into
+package offers a batch solution for address geocoding (as opposed to
+packages like [`censusr`](https://CRAN.R-project.org/package=censusr),
+which provide functionality for a single address at a time). `censusxy`
+has also been developed specifically with large data sets in mind - only
+unique addresses are passed to the API for geocoding. If a data set
+exceeds 1,000 unique addresses, it will be automatically subset into
 appropriately sized API calls, geocoded, and then put back together so
 that a single object is returned.
 
@@ -40,8 +39,15 @@ installed automatically with `censusxy` if they are not already present.
 
 ### Installing censusxy
 
-The package is soon to be on CRAN, but meanwhile, the development
-version of `censusxy` can be accessed from GitHub with `remotes`:
+Once `sf` is installed, the easiest way to get `censusxy` is to install
+it from CRAN:
+
+``` r
+install.packages("censusxy")
+```
+
+Alternatively, the development version of `censusxy` can be accessed
+from GitHub with `remotes`:
 
 ``` r
 # install.packages("remotes")
@@ -81,7 +87,7 @@ If you request an `sf` object, you easily preview the results with the
 > mapview::mapview(homicide_sf)
 ```
 
-<img src="man/figures/homicide_example.png" width="60%" />
+<img src="man/figures/homicide_example.png" width="100%" />
 
 ## Contributor Code of Conduct
 

cran-comments.md

@@ -1,5 +1,11 @@
 ## Release summary
-This is the initial version of the `censusxy` package.
+This is the initial version of the `censusxy` package. It was previously submitted (on July 5) and then rejected (on July 9):
+
+> Please ensure that your functions do not write by default or in your examples/vignettes/tests in the user's home filespace (including the  package directory and getwd()). 
+
+We have reviewed the package to be sure - `censusxy` only interacts with the file system in `cxy_geocoder.R`, where a `.csv` is written to the temp directory (lines 14-16), which is subsequently cleaned up (line 57). We thought that this would be permissable according to CRAN policy since we're only working with the temp directory here. 
+
+We are not at all opposed to making changes to ensure we comply with CRAN policy - but are unsure what to change in this instance. Uwe kindly suggested that we could resubmit the package as is and that he would be willing to take a look at the function. Thanks, Uwe, for your offer and help!
 
 ## Test environments
 * local OS X install: R 3.6.0