In kimjam/srms: Package to automate tasks and reporting for OCD SRMS Team.

knitr::opts_chunk$set(fig.width = 8)

country_filter <- . %>%
  dplyr::filter(Country_Code %in% countries$Country_Code)

counter <- . %>% {
  if ('Country_Code' %in% names(.)) {
    dplyr::group_by(., Type, Country_Code) %>%
      dplyr::summarise(., complaints = n())
  } else {
    as.null(.)
  }}

mytheme <- gridExtra::ttheme_default(
  core = list(fg_params=list(cex = .5)),
  colhead = list(fg_params=list(cex = .5)),
  rowhead = list(fg_params=list(cex = .5))
)

grob_binder <- function(ggrob, tgrob) {
  tgrob$heights <- unit.pmax(tgrob$heights)
  tgrob$widths <- unit(rep(1/ncol(tgrob), ncol(tgrob)), 'npc')

  ggrob %<>% gtable_add_rows(., sum(tgrob$heights))
  ggrob %<>% gtable_add_grob(., grobs = tgrob, t = nrow(ggrob),
                             l = 4, b = nrow(ggrob), r = 4)

  grid.draw(ggrob)
  invisible(ggrob)
}

make_basic_table <- function(df) {
  DT::datatable(data = df,
            options = list(dom = 'ft',
                           scrollY = '300px',
                           paging = FALSE),
            rownames = FALSE,
            colnames = gsub('\\.|_' ,' ', names(df)),
            escape = TRUE)
}

extract_summary <- function(string) {
  desc <- stringr::str_split(string, '\\\r\\\n', simplify = TRUE) %>% 
    as.character() %>% 
    trimws() %>%
    paste(collapse = ' ')

  summary <- stringr::str_match(desc, 'PROBLEM STATEMENT.(.*?)CUSTOMER IS COMPLAINING ABOUT') %>% 
    as.character() %>% tail(1) %>% trimws()

  if (summary == '' || is.na(summary)) {
    summary <- stringr::str_match(desc, 'CUSTOMER IS COMPLAINING ABOUT.(.*?)COMPLAINANT') %>% 
      as.character() %>% tail(1) %>% trimws()
  }

  if (is.na(summary)) {
    return(stringr::str_split(string, pattern = '\\\r\\\n', simplify = TRUE) %>%
             as.character() %>%
             trimws() %>%
             .[1])
  }

  return(summary)
}

complaints_summary <- function(country) {
  country_name <- countries$Country[countries$Country_Code == country]
  types <- c('CLEQ', 'CLRE', 'TMEQ', 'TMRE')
  clre_df <- clre[[country]] %>% 
  {if (is.null(.)) {.} else {dplyr::mutate(., Type = 'CLRE')}}
  cleq_df <- cleq[[country]] %>% 
  {if (is.null(.)) {.} else {dplyr::mutate(., Type = 'CLEQ')}}
  tmre_df <- tmre[[country]] %>% 
  {
    if (is.null(.)) {
      .
    } else {
      dplyr::mutate(., Type = 'TMRE') %>% 
        dplyr::rename(dummy = Call_Subject,
                      Call_Subject = Category)
    }
  }
  tmeq_df <- tmeq[[country]] %>% 
  {if (is.null(.)) {.} else {dplyr::mutate(., Type = 'TMEQ')}}

  if (is.null(c(clre_df, cleq_df, tmre_df, tmeq_df))) {
    text_list <- vector('list', 4) %>% setNames(types)

    for (type in types) {
      text_list[[type]] <- textGrob(paste('No', type, 'complaints in', 
                                          stringr::str_to_title(country_name), 
                                          'during this time period.'))
    }
    return(text_list)
  }

  if (!is.null(c(clre_df, cleq_df))) {
    cl_df <- rbind(clre_df, cleq_df) %>%
      dplyr::select(
        Type,
        J_Number,
        Complaint_Nbr___CH,
        Create_Audit_DT,
        Call_Subject,
        Call_Area,
        Problem_Description
      ) %>%
      dplyr::rename(Complaint_Number = Complaint_Nbr___CH,
                    J_No = J_Number,
                    Complaint_Date = Create_Audit_DT) %>%
      dplyr::mutate(
        Complaint_Date = purrr::map_chr(Complaint_Date,
                                        ~ strftime(.x, 
                                                   format = '%Y-%m-%d %H:%M:%S'))
      )
  } else {
    cl_df <- NULL
  }

  tm_parser <- . %>%
    dplyr::select(
        Type,
        J_Number,
        Complaint_Nbr,
        Create_Audit_DT,
        Call_Subject,
        Call_Area,
        Problem_Desc
      ) %>%
      dplyr::rename(Complaint_Number = Complaint_Nbr,
                    J_No = J_Number,
                    Complaint_Date = Create_Audit_DT,
                    Problem_Description = Problem_Desc) %>%
      dplyr::mutate(
        Complaint_Date = purrr::map_chr(Complaint_Date,
                                        ~ strftime(.x, 
                                                   format = '%Y-%m-%d %H:%M:%S'))
      )

  if (!is.null(c(tmre_df, tmeq_df))) {
    tm_df <- rbind(tmre_df %>% {if (is.null(.)) {.} else {tm_parser(.)}},
                   tmeq_df %>% {if (is.null(.)) {.} else {tm_parser(.)}})
  } else {
    tm_df <- NULL
  }  

  df_list <- rbind(cl_df, tm_df) %>%
    dplyr::mutate(Complaint_Summary = purrr::map(Problem_Description, 
                                                 ~ extract_summary(.x))) %>%
    dplyr::select(-Problem_Description) %>%
    split(.$Type)

  for (type in types[-match(names(df_list), types)]) {
    df_list[[type]] <- textGrob(paste('No', type, 'complaints in', 
                                      stringr::str_to_title(country_name), 
                                      'during this time period.'))
  }

  return(df_list)
}

renderer <- function(item) {
  if (any(class(item) == 'grob')) {
    grid.draw(item)
  } else {
    make_basic_table(df = item)
  }
}

daterange <- strftime(c(srms::last_month(), lubridate::floor_date(Sys.time(), 'month')), 
                      format = '%Y-%m-%d')

countries <- srms::srms_table('country_codes') %>%
  dplyr::filter(Region == 'LAR')

clre <- srms::roc_re_v26b(add = 'audit', daterange = daterange) %>% 
  country_filter() %>%
  split(.$Country_Code)
cleq <- srms::roc_eq_v26b(add = 'audit', daterange = daterange) %>% 
  country_filter() %>% 
  split(.$Country_Code)
tm <- srms::tm_general_template(daterange = daterange) %>% 
  country_filter() %>%
  dplyr::filter(Call_Subject != 'NONPROD') %>%
  dplyr::mutate(Type = ifelse(Call_Type %in% c('CE', 'PHSE', 'CERE', 'CSW'),
                              'Instrument',
                              'Reagent')) %>% 
  dplyr::left_join(
    y = tmrecat %>%
      dplyr::select(
        Dataset,
        Call.subject,
        Category
      ),
    by = c('Call_Subject' = 'Call.subject')
  ) %>%
  split(.$Type)

if ('Reagent' %in% names(tm)) {
  tmre <- tm$Reagent %>% split(.$Country_Code)
} else {
  tmre <- NULL
}

tmeq <- tm$Instrument %>% split(.$Country_Code)

groups <- c('AR', 'BR', 'CL', 'CO', 'MX', 'PA', 'PR', 'UY', 'VE')
types <- c('CLRE', 'CLEQ', 'TMRE', 'TMEQ')

LATAM Summary

df <- tibble::tibble(Country_Code = rep(groups, each = 4),
                     Type = rep(types, length(groups))) %>%
  dplyr::left_join(
    y = rbind(
      clre %>% dplyr::bind_rows() %>% dplyr::mutate(Type = 'CLRE') %>% counter(),
      cleq %>% dplyr::bind_rows() %>% dplyr::mutate(Type = 'CLEQ') %>% counter(),
      tmre %>% dplyr::bind_rows() %>% dplyr::mutate(Type = 'TMRE') %>% counter(),
      tmeq %>% dplyr::bind_rows() %>% dplyr::mutate(Type = 'TMEQ') %>% counter()
    ),
    by = c('Type', 'Country_Code')
  ) %>%
  dplyr::left_join(
    y = countries %>% dplyr::select(Country, Country_Code),
    by = 'Country_Code'
  ) %>%
  dplyr::select(-Country_Code) 

tgrob <- df %>%
  tidyr::spread(Country, complaints, fill = 0) %>%
  add_margins() %>%
  tableGrob(row = NULL, theme = mytheme)

ggrob <- ggplotGrob(
  ggplot(df, aes(x = Country, y = complaints, fill = Type)) + 
    geom_col(color = 'black', position = 'dodge') + 
    scale_fill_tableau() + 
    theme(legend.position = 'top',
          axis.title.x = element_blank()) +
    ggtitle(paste0('LATAM Complaints: ', strftime(daterange[1], format = '%B %Y')))
)

grob_binder(ggrob = ggrob, tgrob = tgrob)

out <- NULL
for (group in groups) {
  out <- c(
    out,
    knitr::knit_expand(
      text = paste0(
        '\n{{country_name}} {data-navmenu=\'Country\'}',
        '\n=====================================\n',
        '\nColumn {.tabset .tabset-fade}',
        '\n-------------------------------------',
        '\n\n### CLEQ Summary',
        '\n```r}-cleq}',
        '\nitems <- complaints_summary(\'{{group}}\')',
        '\nrenderer(items$CLEQ)',
        '\n```',
        '\n\n### CLRE Summary',
        '\n```r}-clre}',
        '\nrenderer(items$CLRE)',
        '\n```',
        '\n\n### TMEQ Summary',
        '\n```r}-tmeq}',
        '\nrenderer(items$TMEQ)',
        '\n```',
        '\n\n### TMRE Summary',
        '\n```r}-tmre}',
        '\nrenderer(items$TMRE)',
        '\n```'
      ),
      country_name = countries$Country[countries$Country_Code == group],
      group = group
    )
  )
}

r knitr::knit(text = out)

Complaint Viewer

df <- rbind(dplyr::bind_rows(clre) %>% 
              dplyr::select(Complaint_Nbr___CH, Problem_Description) %>%
              dplyr::rename(Complaint_Nbr = Complaint_Nbr___CH),
            dplyr::bind_rows(cleq) %>% 
              dplyr::select(Complaint_Nbr___CH, Problem_Description) %>%
              dplyr::rename(Complaint_Nbr = Complaint_Nbr___CH),
            dplyr::bind_rows(tmre) %>% {
              if (nrow(.) != 0) {
                dplyr::select(., Complaint_Nbr, Problem_Desc) %>%
                  dplyr::rename(., Problem_Description = Problem_Desc)
              } else {
                .
              }},
            dplyr::bind_rows(tmeq) %>% 
              dplyr::select(Complaint_Nbr, Problem_Desc) %>%
              dplyr::rename(Problem_Description = Problem_Desc)) %>%
  dplyr::mutate(Problem_Description = gsub('\\\r\\\n', '<br/>', 
                                           Problem_Description))

DT::datatable(
  data = df,
  options = list(dom = 'ft',
                 scrollY = '300px',
                 paging = FALSE),
  rownames = FALSE,
  colnames = gsub('\\.|_' ,' ', names(df)),
  escape = FALSE
)