#Nicole Clark #HW_7

#6.4.1

#library(tidyverse) word <- c(“one”, “two”, NA, “four”, “five”) number <- c(1, NA, 3, 4, 5) letter <- c(letters[1:5]) my_data <- data.frame(word, number, letter) my_data

library(tidyverse) Qual <- ahp %>% select(ends_with(c(“qual”,“area”))) %>% rename(a=oa_qual, b=kit_qual, c=bsmt_fin_qual)

#6.4.2 Qual %>% select(liv_area, heat_qual, everything())

#6.5.1 ahp %>% mutate(age = yr_sold - yr_built) %>% ggplot() + geom_point(mapping = aes(x = age, y = sale_price, color = kit_qual )) ahp %>% group_by(mo_sold) %>% summarize( prob = c(0.25, 0.75), q_price = quantile(sale_price, c(0.25, 0.75), na.rm = TRUE)) %>% ggplot(mapping = aes(x = mo_sold, y = q_price, color = factor(prob))) + geom_point()

#6.6.1 ahp %>% group_by(mo_sold) %>% summarize( prob = c(0.25, 0.75), q_price = quantile(sale_price, c(0.25, 0.75), na.rm = TRUE)) %>% ggplot(mapping = aes(x = mo_sold, y = q_price, color = factor(prob))) + geom_point()

#6.6.2 ahp %>% group_by(yr_built) %>% summarize(min_price=min(sale_price), max_price=max(sale_price), median_price=median(sale_price)) %>% ggplot() + geom_point(mapping=aes(x=yr_built, y=min_price, color = yr_built > 30))