How Much Memory Does A Data Scientist Need (step2)

datascience_memory_step2.R

data.slice.reg <- data.slice.cum_freq %>%
        filter(log10(sizeGB) >= -2) %>%
        filter(log10(sizeGB) <= 4)
ggplot(data.slice.reg, aes(x=log10(sizeGB), y=cum_freq, color=factor(year))) + 
        geom_line(aes(group = factor(year)))
attach(data.slice.reg)

model <- lm(log10(sizeGB) ~ cum_freq + year, na.action=na.exclude)
summary(model)