Merge pull request #51 from rsquaredacademy/develop

Release prep

.travis.yml

@@ -7,13 +7,12 @@ sudo: false
 
 matrix:
   include:
+  - r: devel 
   - r: release
-  - r: release
-    os: osx
-    osx_image: xcode8.3
-    before_install:
-      - sudo tlmgr install framed titling
-  - r: devel
+  - r: 3.6
+  - r: 3.5
+  - r: 3.4
+  - r: 3.3
 
 r_packages:
   - covr

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: rbin
 Type: Package
 Title: Tools for Binning Data
-Version: 0.1.2.9000
+Version: 0.2.0
 Authors@R: person("Aravind", "Hebbali", email = "hebbali.aravind@gmail.com", role = c("aut", "cre"))
 Description: Manually bin data using weight of evidence and information value. Includes other binning 
     methods such as equal length, quantile and winsorized. Options for combining levels of categorical
@@ -11,29 +11,24 @@ License: MIT + file LICENSE
 URL: https://github.com/rsquaredacademy/rbin, https://rbin.rsquaredacademy.com
 BugReports: https://github.com/rsquaredacademy/rbin/issues
 Depends: 
-    R (>= 3.6)
-Encoding: UTF-8
-LazyData: true
-RoxygenNote: 6.1.1
+    R (>= 3.3)
 Imports: 
-    DescTools,
-    dplyr,
-    forcats,
+    data.table,
     ggplot2,
+    stats,
+    utils
+Suggests:
+    covr,
     graphics,
-    magrittr,
+    knitr,
     miniUI,
-    recipes,
     rlang,
+    rmarkdown,
     rstudioapi,
     shiny,
-    stats,
-    tibble,
-    utils
-Suggests:
-    covr,
     testthat,
-    vdiffr,
-    knitr,
-    rmarkdown
+    vdiffr
 VignetteBuilder: knitr
+Encoding: UTF-8
+LazyData: true
+RoxygenNote: 7.1.0

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(plot,rbin_equal_freq)
 S3method(plot,rbin_equal_length)
 S3method(plot,rbin_factor)
 S3method(plot,rbin_manual)
@@ -12,7 +13,9 @@ S3method(print,rbin_manual)
 S3method(print,rbin_quantiles)
 S3method(print,rbin_winsorize)
 S3method(rbin_equal_freq,default)
+S3method(rbin_equal_length,default)
 S3method(rbin_factor,default)
+S3method(rbin_manual,default)
 S3method(rbin_winsorize,default)
 export(rbinAddin)
 export(rbinFactorAddin)
@@ -25,8 +28,16 @@ export(rbin_factor_create)
 export(rbin_manual)
 export(rbin_quantiles)
 export(rbin_winsorize)
-importFrom(magrittr,"%<>%")
-importFrom(magrittr,"%>%")
-importFrom(rlang,"!!")
-importFrom(rlang,":=")
+importFrom(data.table,":=")
+importFrom(data.table,.N)
+importFrom(data.table,data.table)
+importFrom(data.table,setDF)
+importFrom(data.table,setorder)
+importFrom(stats,na.omit)
+importFrom(stats,quantile)
 importFrom(utils,globalVariables)
+importFrom(utils,head)
+importFrom(utils,install.packages)
+importFrom(utils,menu)
+importFrom(utils,packageVersion)
+importFrom(utils,tail)

NEWS.md

@@ -1,3 +1,7 @@
+# rbin 0.2.0
+
+This is a minor release for bug fixes and internal changes.
+
 # rbin 0.1.2
 
 * This is a patch release to fix CRAN note.

R/rbin-addins.R

@@ -13,14 +13,18 @@
 #'
 rbinAddin <- function(data = NULL) {
 
+  check_suggests('shiny')
+  check_suggests('miniUI')
+  check_suggests('rstudioapi')
+
 	context <- rstudioapi::getActiveDocumentContext()
   text <- context$selection[[1]]$text
   default_data <- text
 
     if (is.null(data)) {
          if (nzchar(default_data)) {
               data <- default_data
-         } 
+         }
     }
 
     if (any(class(data) %in% c("data.frame","tibble","tbl_df"))) {
@@ -48,7 +52,7 @@ rbinAddin <- function(data = NULL) {
 			  					shiny::textInput("mydata", "Data Name", value = mydata)
 			  				)
 			  			)
-        
+
 						)
 		  		)
         )
@@ -71,10 +75,10 @@ rbinAddin <- function(data = NULL) {
       	  	shiny::fluidRow(
       	  	  shiny::column(4,
       	  	  	shiny::h4('Cut Points'),
-			    			shiny::p('For manual binning, you need to specify the cut points for the bins. `rbin` 
-			    								follows the left closed and right open interval for creating bins. The 
-                          number of cut points you specify is one less than the number of bins you 
-                          want to create i.e. if you want to create 10 bins, you need to specify only 
+			    			shiny::p('For manual binning, you need to specify the cut points for the bins. `rbin`
+			    								follows the left closed and right open interval for creating bins. The
+                          number of cut points you specify is one less than the number of bins you
+                          want to create i.e. if you want to create 10 bins, you need to specify only
                           9 cut points. View the vignette or documentation for more information.')
       	  	  	),
       	  	  shiny::column(8, align = 'center',
@@ -86,7 +90,7 @@ rbinAddin <- function(data = NULL) {
 				      	shiny::actionButton("create_bins", "Create Bins")
 		      		)
 		    		)
-		  		)   
+		  		)
       	)
       ),
       miniUI::miniTabPanel("Bins", icon = shiny::icon("table"),
@@ -112,7 +116,7 @@ rbinAddin <- function(data = NULL) {
       	)
       )
     )
-  
+
 
   server <- function(input, output, session) {
 
@@ -171,13 +175,11 @@ rbinAddin <- function(data = NULL) {
 	})
 
 	down_bins <- shiny::reactive({
-		compute_bins() %>%
-		  magrittr::use_series(bins) %>%
-		  dplyr::select(cut_point, bin_count, good, bad, woe, iv)
+    compute_bins()$bins[c('cut_point', 'bin_count', 'good', 'bad', 'woe', 'iv')]
 	})
 
 	output$woe_manual <- shiny::renderPrint({
-	  compute_bins() 
+	  compute_bins()
 	})
 
 	output$woe <- shiny::renderPlot({
@@ -220,7 +222,7 @@ rbinFactorAddin <- function(data = NULL) {
     if (is.null(data)) {
          if(nzchar(default_data)) {
               data <- default_data
-         } 
+         }
     }
 
     if (any(class(data) %in% c("data.frame","tibble","tbl_df"))) {
@@ -350,8 +352,8 @@ rbinFactorAddin <- function(data = NULL) {
 		shiny::updateSelectInput(
 	  	session,
 	    inputId = "sel_cat",
-	    choices = levels(as.factor(dplyr::pull(data1(), input$pred_var))),
-	    selected = levels(as.factor(dplyr::pull(data1(), input$pred_var)))
+	    choices = levels(as.factor(data1()[[input$pred_var]])),
+	    selected = levels(as.factor(data1()[[input$pred_var]]))
 	  )
 
 	})
@@ -370,9 +372,7 @@ rbinFactorAddin <- function(data = NULL) {
 	})
 
 	down_bins <- shiny::reactive({
-		woe_man() %>%
-		  magrittr::use_series(bins) %>%
-		  dplyr::select(level, bin_count, good, bad, woe, iv)
+    woe_man()$bins[c('level', 'bin_count', 'good', 'bad', 'woe', 'iv')]
 	})
 
 	woe_plot <- shiny::eventReactive(input$create_bins, {

R/rbin-create-bins.R

@@ -16,22 +16,15 @@
 #'
 rbin_create <- function(data, predictor, bins) {
 
-  pred <- rlang::enquo(predictor)
-
-  pred_name <-
-    data %>%
-    dplyr::select(!! pred) %>%
-    names()
-
-  data2 <-
-    data %>%
-    dplyr::select(predictor = !! pred)
+  pred <- deparse(substitute(predictor))
+  data2 <- data[pred]
+  colnames(data2) <- c("predictor")
 
   l_freq <- bins$lower_cut
   u_freq <- bins$upper_cut
   bin_na <- sum(is.na(bins$bins$bin))
   lbins  <- length(bins$bins$bin) - bin_na
-  
+
   data2$binned <- NA
   dummy_names <- bins$bins$cut_point
 
@@ -40,23 +33,13 @@ rbin_create <- function(data, predictor, bins) {
       dummy_names[i]
   }
 
-  bm_rec <- recipes::recipe( ~ ., data = data2)
-
-  binned_data <-
-    bm_rec %>%
-    recipes::step_dummy(binned) %>%
-    recipes::prep(training = data2, retain = TRUE) %>%
-    recipes::bake(new_data = data2)
-
-  bin_names <- f_bin(u_freq)[-1]
-  sym_sign  <- c(rep("_<_", (lbins - 2)), "_>=_")
-
-  final_data <-
-    binned_data %>%
-    dplyr::select(-predictor) %>%
-    magrittr::set_colnames(paste0(rep(pred_name, (lbins - 2)), sym_sign, bin_names))
-
-  dplyr::bind_cols(data, final_data)
+  data2$binned <- as.factor(data2$binned)
+  result <- rbin_factor_create(data2, binned)
+  result[c('predictor', 'binned')] <- NULL
+  bin_names <- f_bin(u_freq)
+  sym_sign  <- c(rep("_<_", (lbins - 1)), "_>=_")
+  colnames(result) <- paste0(rep(pred, (lbins - 1)), sym_sign, bin_names)
+  cbind(data, result)
 
 }