Merge pull request #34 from dtacled/tb

Update example creds and more inter_num updates
dtacled · Dec 18, 2024 · 3e52902 · 3e52902
2 parents e0fd6ce + dbdc8a3
commit 3e52902
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diff --git a/R/acled_transform_wider.R b/R/acled_transform_wider.R
@@ -39,6 +39,10 @@ acled_transform_wider <- function(data, type = "full_actors") {
     stop(paste0("Error: ", type, " is not a valid option. Please select a valid option:\"full_actors\", \"main_actors\", \"assoc_actors\", \"source\", \"api_monadic\""))
   }
 
+  if(type %in% c("full_actors", "main_actors")) {
+    inter_numeric <- any(1:8 %in% unique(data$inter))
+  }
+
   if (type == "full_actors") {
     columns_present <- function(df, cols) {
       all(sapply(cols, function(x) !is.na(match(x, names(df)))))
@@ -51,16 +55,18 @@ acled_transform_wider <- function(data, type = "full_actors") {
       stop("Some columns are missing. Please make sure your data frame includes: actor,type_of_actor,inter_type, and inter.")
     }
 
+
+
     reverse_data <- data %>%
       # Pivot actor firsts, flattening joint actors such as assoc actors
       pivot_wider(names_from = type_of_actor, values_from = actor, values_fn = function(x) str_flatten(x, collapse = "; "), values_fill = "") %>%
-      # Pivot inters next, adding a fill 9999 to those that do not apply, as a way of removing. inters from different types of actors
-      pivot_wider(names_from = inter_type, values_from = inter, values_fill = 9999) %>%
-      # Transform inter into character for collapsing
+
       mutate(
-        inter1 = as.character(inter1),
-        inter2 = as.character(inter2)
+        inter = as.character(inter)
       ) %>%
+
+      # Pivot inters next, adding a fill 9999 to those that do not apply, as a way of removing. inters from different types of actors
+      pivot_wider(names_from = inter_type, values_from = inter, values_fill = as.character(9999)) %>%
       mutate(inter1 = replace_na(inter1, "")) %>%
       mutate(inter2 = replace_na(inter2, "")) %>%
       group_by(across(c(-actor1, -actor2, -inter1, -inter2, -assoc_actor_1, -assoc_actor_2))) %>%
@@ -74,21 +80,34 @@ acled_transform_wider <- function(data, type = "full_actors") {
         assoc_actor_2 = str_c(assoc_actor_2, collapse = "")
       ) %>%
       ungroup() %>%
-      # Transform inter into numeric column
-      mutate(
-        inter1 = as.numeric(inter1),
-        inter2 = as.numeric(inter2)
-      ) %>%
       mutate(
         actor2 = na_if(actor2, ""),
         actor1 = na_if(actor1, ""),
         assoc_actor_1 = na_if(assoc_actor_1, ""),
-        assoc_actor_2 = na_if(assoc_actor_2, ""),
-        inter1 = replace_na(inter1, 0),
-        inter2 = replace_na(inter2, 0)
+        assoc_actor_2 = na_if(assoc_actor_2, "")
       ) %>%
       # Match column structure for an acled dataset
-      select(names(acledR::acled_old_dummy))
+      dplyr::select(names(acledR::acled_old_dummy))
+
+    # Coerce to numeric if inter were originally numeric
+    if(inter_numeric == TRUE) {
+      reverse_data <-
+        reverse_data %>%
+        mutate(
+          inter1 = as.numeric(inter1),
+          inter2 = as.numeric(inter2),
+          inter1 = replace_na(inter1, 0),
+          inter2 = replace_na(inter2, 0)
+        )
+    } else {
+      reverse_data <-
+        reverse_data %>%
+        mutate(
+          inter1 = case_when(inter1 == "" ~ NA_character_, TRUE ~ inter1),
+          inter2 = case_when(inter2 == "" ~ NA_character_, TRUE ~ inter2)
+        )
+    }
+
   } else if (type == "main_actors") {
     columns_present <- function(df, cols) {
       all(sapply(cols, function(x) !is.na(match(x, names(df)))))
@@ -104,13 +123,16 @@ acled_transform_wider <- function(data, type = "full_actors") {
     reverse_data <- data %>%
       # Pivot actor firsts, flattening joint actors such as assoc actors
       pivot_wider(names_from = type_of_actor, values_from = actor, values_fn = function(x) str_flatten(x, collapse = "; "), values_fill = "") %>%
-      # Pivot inters next, adding a fill 9999 to those that do not apply, as a way of removing. inters from different types of actors
-      pivot_wider(names_from = inter_type, values_from = inter, values_fill = 9999) %>%
+
       # Transform inter into character for collapsing
       mutate(
-        inter1 = as.character(inter1),
-        inter2 = as.character(inter2)
+        inter = as.character(inter)
       ) %>%
+
+      # Pivot inters next, adding a fill 9999 to those that do not apply, as a way of removing. inters from different types of actors
+      # Coerced to character to account for inters being text or numeric
+      pivot_wider(names_from = inter_type, values_from = inter, values_fill = as.character(9999)) %>%
+
       mutate(inter1 = replace_na(inter1, "")) %>%
       mutate(inter2 = replace_na(inter2, "")) %>%
       group_by(across(c(-actor1, -actor2, -inter1, -inter2))) %>%
@@ -122,21 +144,34 @@ acled_transform_wider <- function(data, type = "full_actors") {
         inter2 = str_trim(str_remove_all(str_c(inter2, collapse = " "), "9999"))
       ) %>%
       ungroup() %>%
-      # Transform inter into numeric column
-      mutate(
-        inter1 = as.numeric(inter1),
-        inter2 = as.numeric(inter2)
-      ) %>%
       mutate(
         actor2 = na_if(actor2, ""),
         actor1 = na_if(actor1, ""),
         assoc_actor_1 = na_if(assoc_actor_1, ""),
-        assoc_actor_2 = na_if(assoc_actor_2, ""),
-        inter1 = replace_na(inter1, 0),
-        inter2 = replace_na(inter2, 0)
+        assoc_actor_2 = na_if(assoc_actor_2, "")
       ) %>%
       # Match column structure for an acled dataset
-      select(names(acledR::acled_old_dummy))
+      dplyr::select(names(acledR::acled_old_dummy))
+
+    # Coerce to numeric if inter were originally numeric
+    if(inter_numeric == TRUE) {
+      reverse_data <-
+        reverse_data %>%
+        mutate(
+        inter1 = as.numeric(inter1),
+        inter2 = as.numeric(inter2),
+        inter1 = replace_na(inter1, 0),
+        inter2 = replace_na(inter2, 0)
+      )
+    } else {
+      reverse_data <-
+        reverse_data %>%
+        mutate(
+          inter1 = case_when(inter1 == "" ~ NA_character_, TRUE ~ inter1),
+          inter2 = case_when(inter2 == "" ~ NA_character_, TRUE ~ inter2)
+        )
+    }
+
   } else if (type == "assoc_actors") {
     columns_present <- function(df, cols) {
       all(sapply(cols, function(x) !is.na(match(x, names(df)))))
@@ -164,12 +199,30 @@ acled_transform_wider <- function(data, type = "full_actors") {
         actor2 = na_if(actor2, ""),
         actor1 = na_if(actor1, ""),
         assoc_actor_1 = na_if(assoc_actor_1, ""),
-        assoc_actor_2 = na_if(assoc_actor_2, ""),
-        inter1 = replace_na(inter1, 0),
-        inter2 = replace_na(inter2, 0)
+        assoc_actor_2 = na_if(assoc_actor_2, "")
       ) %>%
       # Match column structure for an acled dataset
-      select(names(acledR::acled_old_dummy))
+      dplyr::select(names(acledR::acled_old_dummy))
+
+    # Coerce to numeric if inter were originally numeric
+    # if(inter_numeric == TRUE) {
+    #   reverse_data <-
+    #     reverse_data %>%
+    #     mutate(
+    #       inter1 = as.numeric(inter1),
+    #       inter2 = as.numeric(inter2),
+    #       inter1 = replace_na(inter1, 0),
+    #       inter2 = replace_na(inter2, 0)
+    #     )
+    # } else {
+    #   reverse_data <-
+    #     reverse_data %>%
+    #     mutate(
+    #       inter1 = case_when(inter1 == "" ~ NA_character_, TRUE ~ inter1),
+    #       inter2 = case_when(inter2 == "" ~ NA_character_, TRUE ~ inter2)
+    #     )
+    # }
+
   } else if (type == "source") {
     columns_present <- function(df, cols) {
       all(sapply(cols, function(x) !is.na(match(x, names(df)))))
@@ -188,7 +241,7 @@ acled_transform_wider <- function(data, type = "full_actors") {
       summarise(source = str_c(source, collapse = "; ")) %>%
       ungroup() %>%
       # Match column structure for an acled dataset
-      select(names(acledR::acled_old_dummy))
+      dplyr::select(names(acledR::acled_old_dummy))
   } else if (type == "api_monadic") {
     df1 <- data %>%
       group_by(event_id_cnty) %>%

diff --git a/R/acled_update.R b/R/acled_update.R
@@ -77,7 +77,7 @@ acled_update <- function(df,
     warning("Warning: End date is earlier than the latest event date in your dataframe.")
   }
 
-  if (inter_numeric == FALSE & length(df$inter1[[1]]) == 1) {
+  if (inter_numeric == FALSE & any(1:8 %in% unique(df$inter1))) {
     stop("The data frame provided appears to have numeric interaction values (inter1, inter2, and interaction variables). Set inter_numeric = TRUE in the acled_update() call to update data with numeric interaction values.")
   }
 

diff --git a/README.Rmd b/README.Rmd
@@ -20,17 +20,11 @@ knitr::opts_chunk$set(
 [![codecov](https://codecov.io/gh/ACLED/acledR/graph/badge.svg?token=TDJodXhEvx)](https://codecov.io/gh/ACLED/acledR)
 <!-- badges: end -->
 
-Welcome to ACLED's official R package! This package simplifies access to the data via ACLED's API. It also provides convenient functions for making common ACLED data transformations. See dtacled.github.io/acledR for more information and tutorials on how to use the package.
 
 
-# Overview
+Welcome to acledR! This package provides tools to extract and manipulate data from the [Armed Conflict Location and Event Data Project (ACLED)](https://acleddata.com/). It also provides convenient functions for making common ACLED data transformations. See [dtacled.github.io/acledR](https://dtacled.github.io/acledR) for more information and tutorials on how to use the package.
 
-This package provides tools to extract and manipulate data from the [Armed Conflict Location and Event Data Project (ACLED)](https://acleddata.com/). 
-
-To access ACLED data, please register an account at [developer.acleddata.com](developer.acleddata.com). 
-
-* You can visit our [guide](https://acleddata.com/acleddatanew//wp-content/uploads/2021/11/ACLED_Access-Guide_October-2020.pdf) on how to easily set up your ACLED account. 
-* We recommend you to save your ACLED API Key in an R object so you can easily re-use your key. 
+To access ACLED data, please register an account at [developer.acleddata.com](https://developer.acleddata.com). You can find detailed instructions for setting up your account and retreiving an API key [here](https://acleddata.com/acleddatanew//wp-content/uploads/2021/11/ACLED_Access-Guide_October-2020.pdf). 
 
 
 ## Installation

diff --git a/README.md b/README.md
@@ -7,74 +7,26 @@
 
 [![R-CMD-check](https://github.com/ACLED/acledR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/ACLED/acledR/actions/workflows/R-CMD-check.yaml)
 [![codecov](https://codecov.io/gh/ACLED/acledR/graph/badge.svg?token=TDJodXhEvx)](https://codecov.io/gh/ACLED/acledR)
-
 <!-- badges: end -->
 
-# Overview
-
-This package provides tools to extract and manipulate data from the
-[Armed Conflict Location and Event Data Project
-(ACLED)](https://acleddata.com/).
+Welcome to acledR! This package provides tools to extract and manipulate
+data from the [Armed Conflict Location and Event Data Project
+(ACLED)](https://acleddata.com/). It also provides convenient functions
+for making common ACLED data transformations. See
+[dtacled.github.io/acledR](https://dtacled.github.io/acledR) for more
+information and tutorials on how to use the package.
 
 To access ACLED data, please register an account at
-[developer.acleddata.com](developer.acleddata.com).
-
-- You can visit our
-  [guide](https://acleddata.com/acleddatanew//wp-content/uploads/2021/11/ACLED_Access-Guide_October-2020.pdf)
-  on how to easily set up your ACLED account.
-- We recommend you to save your ACLED API Key in an R object so you can
-  easily re-use your key.
-
-## Installation (for private repo)
-
-Since the package repo is currently private, you need to tell R and
-Github that you’re a collaborator. To do so, you first create a Github
-personal access token (PAT). You can set this to expire after a certain
-time (the default) or be permanent. We can initiate this process
-internally via:
-
-``` r
-# install.packages("usethis") if not installed already
-# create personal access token - this should redirect to your github page where you can copy the token
-usethis::create_github_token()
-```
-
-After you’ve copied the PAT from the browser, return to R and run this,
-which will store the PAT locally.
-
-``` r
-# paste the token where it says YourPAT
-credentials::set_github_pat("YourPAT")
-# if you run this, it should print your token; if not we've failed
-Sys.getenv("GITHUB_PAT")
-```
-
-I recommend also setting the PAT in your `.Rprofile` so it’s stored for
-all R sessions (i.e., you don’t have to save the PAT and paste it in
-each time you re-install).
+[developer.acleddata.com](https://developer.acleddata.com). You can find
+detailed instructions for setting up your account and retreiving an API
+key
+[here](https://acleddata.com/acleddatanew//wp-content/uploads/2021/11/ACLED_Access-Guide_October-2020.pdf).
 
-``` r
-# to set your PAT for all R sessions, run
-file.edit(file.path("~", ".Rprofile"))
-# and then paste credentials::set_github_pat("YourPAT") into the .Rprofile script
-# save the file
-```
+## Installation
 
-Now you can install the package and it will automatically locate your
-PAT.
+The package will be reviewed and available on CRAN shortly. In the
+meantime, you can install the package from Github:
 
 ``` r
-# install from github
 devtools::install_github("ACLED/acledR")
 ```
-
-## Installation (for public use)
-
-Until the acledR package gets added into the Comprehensive R Archive
-Network (CRAN), users can utilize devtools to install the package from
-Github. Thankfully, the installation is rather simple. You can install
-it through the following code:
-
-``` r
-devtools::install_github("ACLED/acledR") ## if you are interested in a particular branch, please add a 'ref' argument. 
-```
diff --git a/tests/testthat/setup-acled_access.R b/tests/testthat/setup-acled_access.R
@@ -1,5 +1,5 @@
 
 # Setup for test acled_access
 
-# Run the function to set up the enviornment credentials
+# Run the function to set up the environment credentials
 acled_access(email = Sys.getenv("EMAIL_ADDRESS_EXAMPLES"), key = Sys.getenv("EXAMPLES_KEY"))
diff --git a/tests/testthat/test-acled_access.R b/tests/testthat/test-acled_access.R
@@ -2,8 +2,7 @@
 # Does it save the credentials in the enviornment? - Missing
 
 test_that("acled_access properly stores the credentials", {
-  # expect_equal(Sys.getenv("acled_email"),"[email protected]")
-  expect_equal(Sys.getenv("acled_email"),"[email protected]")
+  expect_equal(Sys.getenv("acled_email"),"[email protected]")
   expect_equal(nchar(Sys.getenv("acled_key")), 20)
 })
 

diff --git a/tests/testthat/test-acled_api.R b/tests/testthat/test-acled_api.R
@@ -178,7 +178,7 @@ test_that("Error when one of two countries are wrong",{
 
 ## Test what happens when someone inputs acled_access as TRUE but it includes email and key. ----
 test_that("Acled_access is ignored",{
-  expect_true(grepl("t.billing", log_received_data_check_credential$email[1]))
+  expect_true(grepl("acledrexamples", log_received_data_check_credential$email[1]))
 })
 
 # Test errors from incorrectly input arguments. ----
@@ -305,7 +305,7 @@ test_that("A warning appears that acled_access is being ignored, and the proper
   expect_message(acled_api(email = Sys.getenv("EMAIL_ADDRESS_EXAMPLES"), key = Sys.getenv("EXAMPLES_KEY"),
                            acled_access = T, log = T, inter_numeric = TRUE), regexp = "acled_access is TRUE, but email and key are included in the function. Ignoring acled_access.")
 
-  expect_true(grepl("t.billing", alog$email[1]))
+  expect_true(grepl("acledrexamples", alog$email[1]))
 })
 
 

diff --git a/tests/testthat/test-acled_deletions_api.R b/tests/testthat/test-acled_deletions_api.R
@@ -22,7 +22,7 @@ test_that("names of columns are correct - unix", {
 ## Test that email and key are handled appropiately ----
 
 test_that("Email and key are handled as expected without acled_access",{
-          expect_true(grepl("t.billing", received_deleted_log$email[1]))}
+          expect_true(grepl("acledrexamples", received_deleted_log$email[1]))}
 )
 
 ## Test that acled_access is handled appropiately. ----
@@ -32,7 +32,7 @@ test_that("Email and Key are handled appropiately",{
 
   some_log <- acled_deletions_api(date_deleted = "1658707200", acled_access = T, log = T)
 
-  expect_true(grepl("t.billing", some_log$email[1]))}
+  expect_true(grepl("acledrexamples", some_log$email[1]))}
 )
 
 ## Date and unix return the same output ----
@@ -90,7 +90,7 @@ test_that("A warning appears that acled_access is being ignored, and the proper
   expect_message(acled_deletions_api(email = Sys.getenv("EMAIL_ADDRESS_EXAMPLES"), key = Sys.getenv("EXAMPLES_KEY"),
                                      date_deleted = "1658707200",acled_access = T, log = T), regexp = "acled_access is TRUE, but email and key are included in the function. Ignoring acled_access.")
 
-  expect_true(grepl("t.billing@acleddata.com", alog$email[1]))
+  expect_true(grepl("acledrexamples@gmail.com", alog$email[1]))
  })