Sorry it’s in german because I used it for a private project!

library(plotly)

Ind$Gentrification[which(Ind$Gentrification == 1)]    <- 'Nicht eindeutig zuzuordnen'
Ind$Gentrification[which(Ind$Gentrification == 2)]    <- 'Pionierphase (?)'
Ind$Gentrification[which(Ind$Gentrification == 3)]    <- 'Pionierphase'
Ind$Gentrification[which(Ind$Gentrification == 4)]    <- 'Pionier- bis Gentrifierphase'
Ind$Gentrification[which(Ind$Gentrification == 5)]    <- 'Gentrifierphase bis Super Gentrification'
Ind$Gentrification[which(Ind$Gentrification == "NA")]     <- 'Keine Gentrifizierung'
Ind$Gentrification[which(Ind$Gentrification == "Mitte")]  <- 'Hamburger Durchschnitt'
Ind$Gentrification <- as.factor(Ind$Gentrification)

colors <- c('royalblue4','firebrick3','gainsboro','khaki1','lightskyblue2','steelblue3','mediumaquamarine')

p <- plot_ly(Ind, x = ~SI, y = ~MI, z = ~WI, color = ~Gentrification, colors = colors, marker = list(symbol = 'circle', sizemode = 'diameter'), sizes = c(5, 150), text = ~paste("Stadtteil:",id )) %>%
  
   layout(title = "Indexwerte und Gentrifizierungsphasen",
       paper_bgcolor = "rgb(243, 243, 243)"
       ) %>%
   
   add_markers() %>%
   layout(scene = list(xaxis  = list(title = 'SozialIndex'),
                       yaxis  = list(title = 'MobilitätsIndex'),
                       zaxis  = list(title = 'WohnungsmarktIndex')))
p
## Warning: package 'bindrcpp' was built under R version 3.4.4

library(ggplot2)

p=ggplot(Ind, aes(x= SI, y= WI, color=Gentrification, size=MI)) + geom_point() + theme(legend.position=“none”) p