30 lines
732 B
R
30 lines
732 B
R
library(tidyverse)
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# take the mpg data set and pipe it to the mutate function
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# then add a new column to the data set and save to mpg_metric
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mpg_metric <- mpg %>%
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mutate(city_metric = 0.425144 * cty)
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# View the metric data set
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View(mpg_metric)
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# group the mpg dataset by classes
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# then summarize the data by mean and median cty
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mpg %>%
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group_by(class) %>%
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summarise(mean(cty),
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median(cty))
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# Data viz with ggplot2
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ggplot(mpg, aes(x = cty)) +
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geom_histogram() +
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labs(x = "City mileage")
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# Scatter plot between city and highway mileage
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# this shows a linear relationship
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# then add a regression line on top
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ggplot(mpg, aes(x = cty,
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y = hwy)) +
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geom_point() +
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geom_smooth(method = "lm")
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