Standardize 'type' dataframe column

[jeff1evesque]

Since we've combined two datasets into one dataframe, the type column is inconsistent. Specifically, each dataset, introduces their own vernacular. This will need to be standardized within the run.R.

[jeff1evesque]

The following logic from load_dataframe_fin654.R properly prints the associated lists:

  ## replacement lists: index lenghts must match between 'old' and 'new'
  old = c(
    'hacked',
    'oops!',
    'unkn',
    'poor security',
    'lost device',
    'port',
    'disc',
    'phys',
    'insd',
    'stat'
  )

  new = c(
    'hack',
    'accidental-disclosed',
    'unknown',
    'hack',
    'lost-or-stolen',
    'lost-or-stolen',
    'accidental-disclosed',
    'accidental-disclosed',
    'insider',
    'accidental-disclosed'
  )

  if (length(old) == length(new)) {
    for (i in 1:length(new)) {
      print(paste(old[i], new[i]))
    }
  }

However, the following does not return the adjusted dataframe:

  ## replacement lists: index lenghts must match between 'old' and 'new'
  old = c(
    'hacked',
    'oops!',
    'unkn',
    'poor security',
    'lost device',
    'port',
    'disc',
    'phys',
    'insd',
    'stat'
  )

  new = c(
    'hack',
    'accidental-disclosed',
    'unknown',
    'hack',
    'lost-or-stolen',
    'lost-or-stolen',
    'accidental-disclosed',
    'accidental-disclosed',
    'insider',
    'accidental-disclosed'
  )

  if (length(old) == length(new)) {
    for (i in 1:length(new)) {
      data1$replace_val('type', old[i], new[i])
      data2$replace_val('type', old[i], new[i])
    }
  }

  ## return dataset
  return(rbind(data1$get_df(), data2$get_df()))

[jeff1evesque]

After running our app.R manually, we confirm that the type column, renamed as breach, has the expected adjusted column names:

> if (nzchar(Sys.getenv('RSTUDIO_USER_IDENTITY'))) {
+   cwd = dirname(rstudioapi::getSourceEditorContext()$path)
+   setwd(cwd)
+ }
> 
> ## utility functions
> devtools::install_local(paste0(cwd, '/packages/customUtility'))
√  checking for file 'C:\Users\jeff1\AppData\Local\Temp\RtmpAzu3aP\file16207d514df9\customUtility/DESCRIPTION' ... OK
-  preparing 'customUtility':
√  checking DESCRIPTION meta-information ... OK
-  checking for LF line-endings in source and make files and shell scripts
-  checking for empty or unneeded directories
-  building 'customUtility_0.1.0.tar.gz'

Installing package into ‘C:/Users/jeff1/Documents/R/win-library/3.5’
(as ‘lib’ is unspecified)
* installing *source* package 'customUtility' ...
** R
** byte-compile and prepare package for lazy loading
** help
No man pages found in package  'customUtility' 
*** installing help indices
** building package indices
** testing if installed package can be loaded
*** arch - i386
*** arch - x64
* DONE (customUtility)
In R CMD INSTALL
> devtools::install_local(paste0(cwd, '/packages/fin654'))
√  checking for file 'C:\Users\jeff1\AppData\Local\Temp\RtmpAzu3aP\file162044a87894\fin654/DESCRIPTION' (609ms)
-  preparing 'fin654':
√  checking DESCRIPTION meta-information ... OK
-  checking for LF line-endings in source and make files and shell scripts
-  checking for empty or unneeded directories
-  building 'fin654_0.1.0.tar.gz'

Installing package into ‘C:/Users/jeff1/Documents/R/win-library/3.5’
(as ‘lib’ is unspecified)
* installing *source* package 'fin654' ...
** R
** byte-compile and prepare package for lazy loading
** help
No man pages found in package  'fin654' 
*** installing help indices
** building package indices
** testing if installed package can be loaded
*** arch - i386
*** arch - x64
* DONE (fin654)
In R CMD INSTALL
> library('customUtility')
> 
> ## load packages
> load_package(c('reticulate', 'shiny', 'fin654'))
Loading required package: reticulate
Loading required package: shiny
Loading required package: fin654
reticulate      shiny     fin654 
      TRUE       TRUE       TRUE 
> py_install('pandas')
Solving environment: ...working... done

# All requested packages already installed.

Installation complete.

> df = load_data_fin654(
+     paste0(cwd, '/data/data-breaches.csv'),
+     paste0(cwd, '/data/Privacy_Rights_Clearinghouse-Data-Breaches-Export.csv'),
+     paste0('python/dataframe.py')
+   )
> unique(df$breach)
[1] "hack"                 "accidental-disclosed" "lost-or-stolen"      
[4] "inside job"           "insider"              "unknown"             
[7] "card"                
>