add table

app.r

@@ -52,6 +52,10 @@ get_menu <- function() {
         "Red/White Wine Comparison",
         href="/WineVision/Wine-Types",
         className="tab first"),
+      dccLink(
+        "Wine Table",
+        href="/WineVision/Wine-table",
+        className="tab"),
       dccLink(
         "Quality Factor Analysis",
         href="/WineVision/Quality-Factors",
@@ -88,6 +92,128 @@ app$layout(
     )
   )
 
+
+################################
+## Table page
+
+
+df <- wine_quality <- read_csv("data/processed/wine_quality.csv")
+gsub("(mg/dm^3)","",colnames(df),fixed = TRUE)->cn
+gsub("(g/dm^3)","",cn,fixed = TRUE)->cn
+gsub("(g/cm^3)","",cn,fixed = TRUE)->cn
+gsub("(%)","",cn,fixed = TRUE)->cn
+str_trim(cn, side = c("right"))->cn
+colnames(df)<-cn
+
+
+page_size <- 10
+
+
+table_layout<-htmlDiv(list(
+  Header,
+  dbcContainer(
+    dbcRow(list(
+      dbcCol(htmlDiv(
+        dbcCard(
+          dbcCardBody
+          (list(
+            htmlH5("WineVision dataset", className = "Card title"),
+            htmlP("", className = "card-text")
+          )
+          )))),
+      htmlBr(),
+      dbcCol(htmlDiv(
+        dashDataTable(
+          style_table = list(overflowX = 'scroll'),
+          id = 'table-sorting-filtering',
+          columns = lapply(sort(colnames(df)),
+                           function(colName){
+                             list(
+                               id = colName,
+                               name = colName
+                             )
+                           }),
+          page_current = 0,
+          page_size = page_size,
+          page_action = 'custom',
+
+          filter_action = 'custom',
+          filter_query = '',
+
+          sort_action = 'custom',
+          sort_mode = 'multi',
+          sort_by = list()
+        )
+
+      ), width=3)
+    )))))
+
+
+app$callback(
+  output = list(id = 'table-sorting-filtering', property = 'data'),
+  params = list(input(id = 'table-sorting-filtering', property = 'page_current'),
+                input(id = 'table-sorting-filtering', property = 'page_size'),
+                input(id = 'table-sorting-filtering', property = 'sort_by'),
+                input(id = 'table-sorting-filtering', property = 'filter_query')),
+  function(page_current, page_size, sort_by, filters) {
+
+    subdf <- df
+    # filter
+    if(filters != "") {
+
+      conditions <- strsplit(filters, split = "&&")[[1]]
+
+      not_show <- lapply(conditions,
+                         function(condition) {
+
+                           splited_condition <- strsplit(condition, split = " ")[[1]]
+                           # len should be 3
+                           len <- length(splited_condition)
+
+                           condition <- if('contains' %in% splited_condition) {
+
+                             splited_condition[which('contains' == splited_condition)] <- "=="
+
+                             if(!grepl("\"", splited_condition[len]) & !grepl("'", splited_condition[len])) {
+                               splited_condition[len] <- paste0("'", splited_condition[len], "'")
+                             }
+
+                             paste0(splited_condition, collapse = " ")
+                           } else if('=' %in% splited_condition) {
+                             gsub('=', '==', condition)
+                           } else if ('datestartswith' %in% splited_condition) {
+                             gsub('datestartswith', '>=', condition)
+                           } else condition
+
+                           subdf <<- subdf %>%
+                             dplyr::filter(eval(parse(text = condition)))
+                         })
+    }
+
+    # sort
+    if(length(sort_by) != 0) {
+
+      index <- lapply(sort_by,
+                      function(sort){
+                        if(sort[['direction']] == "asc") {
+                          subdf[, sort[['column_id']]]
+                        } else {
+                          -xtfrm(subdf[, sort[['column_id']]])
+                        }
+                      })
+
+      # sort by multi columns
+      subdf <- subdf[do.call(order, index), ]
+    }
+
+    start_id <- (page_current * page_size + 1)
+    end_id <- ((page_current + 1) * page_size)
+    subdf[start_id:end_id, ]
+  }
+)
+
+
+
 #################################
 ## Quality Factor Analysis Page
 
@@ -226,6 +352,9 @@ app$callback(output = list(id='page-content', property = 'children'),
                else if (pathname == "/WineVision/learn-more") {
                  return(learn_more_layout)
                }
+               else if (pathname == "/WineVision/Wine-table") {
+                 return(table_layout)
+               }
                else {
                  return(Wine_Types_layout)
                }

assets/styles.css

@@ -140,10 +140,6 @@ h6 {
   font-size: 1.825rem;
 }
 
-.risk-reward {
-  height: 120px;
-  width: auto;
-}
 
 li {
   color: #7a7a7a;

cluster.Rmd

@@ -10,4 +10,47 @@ output: html_document
 library(gclus)
 library(tidyverse)
 library(mclust)
-```
+```
+
+```{R}
+
+wine_quality <- read_csv("data/processed/wine_quality.csv")
+head(wine_quality)
+```
+
+
+```{R}
+wine_quality%>%select(-`Quality Factor Numeric`,-Wine,-`Quality Factor`)->data
+y<-wine_quality$Wine
+
+
+plot(data,col=y)
+```
+
+```{R}
+
+data%>%select(`Volatile Acidity (g/dm^3)`,pH)->d2
+test2 <- kmeans(scale(d2), 2)
+plot(d2, col=test2$cl)
+
+```
+
+
+
+```{R}
+mdat <- Mclust(data)
+plot(mdat, what="classification")
+
+```
+
+
+### logistic regression
+
+```{R}
+wine_quality%>%select(-Quality,-`Quality Factor Numeric`)->datarf
+library(randomForest)
+rfbod <- randomForest(factor(`Quality Factor`)~., data=datarf)
+rfbod
+```
+
+