modifications in the plotted tables (i.e. conditional formatting) and one...

modifications in the plotted tables (i.e. conditional formatting) and one small improvement in another plot.

code.R

@@ -44,7 +44,7 @@ doId <- function(input) {
   #Wat als iets niet in kleurenset_afstanden valt?
   kleurenset_afstanden=c('25'='red', '50'='orange', '100'='yellow', '200'='green', '400'='blue', '800'='purple', '1500'='deeppink1','500'='black')
   kleurenset_strokes=c('Backstroke'='red', "Breaststroke"='orange', "Butterfly"="purple", "Freestyle"="green", "Medley"="blue")
-
+  kleurenset_pooltypes=c('25m'='orchid', '50m'='cornflowerblue', 'OW'='limegreen')
   bron=separate(bron, col = heatType, into = c("hoofdafstand", "heatType"), sep = ", ", fill='left')
   bron$heatType <- as.factor(bron$heatType)
 
@@ -77,8 +77,9 @@ doId <- function(input) {
   DateAndPool<-DateAndPool[order(DateAndPool$date),]
   freqtabel=as.data.frame(table(DateAndPool$city))
   freqtabel=freqtabel[order(freqtabel$Freq, decreasing=TRUE),]
-  freqtabel_plot<-plot_ly(type = 'table',
-                          cells = list(values =t(as.matrix(unname(freqtabel))))) %>%
+  kolombreedte=unname(sapply(freqtabel, function(x) max(nchar(as.character(x)))+5))
+  freqtabel_plot<-plot_ly(type = 'table', columnwidth=kolombreedte,
+                          cells = list(values =t(as.matrix(unname(freqtabel))), align='left')) %>%
         layout(title = 'Number of meets par city')
   appendPlotly(freqtabel_plot)
 
@@ -103,7 +104,7 @@ doId <- function(input) {
   tijdlijn_alles<-ggplot(zonder_split, aes(x=date, y=interaction(distance, stroke, sep='m '), shape=poolType))+
     geom_point()+
     geom_point(data = tabel_Prs, color="green", alpha=0.7, size=2, show.legend=FALSE)+
-    labs(y='distance & stroke')+
+    labs(y='distance & stroke')+ggtitle(" ")+
     guides(color='none')+ scale_x_date()+scale_y_discrete(limits=rev)
   tijdlijn_alles<-ggplotly(tijdlijn_alles, tooltip=c('x', 'shape'), dynamicTicks=TRUE)%>%
                            layout(title = list(text = paste0('Datum van alle gezwommen slagen per afstand',
@@ -126,10 +127,13 @@ doId <- function(input) {
     group_by(distance, stroke, poolType) %>%
     filter(date == max(date, na.rm=TRUE))
 
-  tabel_lastswam=tabel_LastEntrys%>%select(c('distance', 'stroke', 'poolType', 'date', 'city'))
-  plottabel_LastSwam=plot_ly(type='table',
+  tabel_lastswam=tabel_LastEntrys%>%select(c('distance', 'stroke', 'poolType', 'date'))
+  kolombreedte=unname(sapply(tabel_lastswam, function(x) max(nchar(as.character(x)))+5))
+  plottabel_LastSwam=plot_ly(type='table', columnwidth=kolombreedte,
                              header = list(values=colnames(tabel_lastswam)),
-                             cells=list(values=t(tabel_lastswam[order(tabel_lastswam$date),])))
+                             cells=list(values=t(tabel_lastswam[order(tabel_lastswam$date),]),
+                                        fill= list(color = list(kleurenset_pooltypes[tabel_lastswam$poolType])),
+                                        align='left'))
   plottabel_LastSwam<-plottabel_LastSwam %>% layout(title='Last swam par distance and pooltype')
   appendPlotly(plottabel_LastSwam)