Data driven DIY decisions using R

fixings.r

library(readr)
library(ggplot2)
library(dplyr)
library(ggrepel)

data <- read_delim(
  "Fixings.txt", "\t", escape_double = FALSE,
  trim_ws = TRUE)

knitr::kable(data)



p <- ggplot(data, aes(KG, Price)) +
  geom_point()+
  geom_point(aes(colour = Fixing, size = Size),stroke=2,alpha=0.8) +
  geom_text_repel(aes(label = Fixing, x = KG)) +
  theme_minimal() +
  expand_limits(x = c(0, 200), y = c(0, 3)) +
  ggtitle("Data Driven DIY - Hollow Wall Fixings",
          subtitle = "By drill diameter (mm)") +
  labs( x= "Plasterboard Fail Weight (KG)", y = "Price (£)")

p


p <- p + scale_size_continuous(range = range(data$Size)) +
  theme(legend.position = "none")
p

ggsave("2018-01-20-Hollow-Wall-Fixings.png", width = 6, height = 4)


# filter out the metal worm and hollow wall anchors - no use because of the tiled surface

data <- data %>% dplyr::filter(Price > .50)

p <- ggplot(data, aes(KG, Price)) +
  geom_point()+
  geom_point(aes(colour = Fixing, size = Size),stroke=2,alpha=0.8) +
  geom_text_repel(aes(label = Fixing, x = KG)) +
  theme_minimal() +
  expand_limits(x = c(0, 200), y = c(0, 3)) +
  ggtitle("Data Driven DIY - Hollow Wall Fixings",
          subtitle = "By drill diameter (mm)") +
  labs( x= "Plasterboard Fail Weight (KG)", y = "Price (£)")

p


p <- p + scale_size_continuous(range = range(data$Size)) +
  theme(legend.position = "none")
p


ggsave("2018-01-20-Hollow-Wall-Fixings-Revised.png", width = 6, height = 4)