diff --git a/mpg_plots.r b/mpg_plots.r
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index 0000000..9c879ed
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+++ b/mpg_plots.r
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+library(tidyverse)
+
+# take the mpg data set and pipe it to the mutate function
+# then add a new column to the data set and save to mpg_metric
+mpg_metric <- mpg %>%
+  mutate(city_metric = 0.425144 * cty)
+
+# View the metric data set
+View(mpg_metric)
+
+# group the mpg dataset by classes
+# then summarize the data by mean and median cty
+mpg %>%
+  group_by(class) %>%
+  summarise(mean(cty),
+            median(cty))
+
+# Data viz with ggplot2
+ggplot(mpg, aes(x = cty)) + 
+  geom_histogram() +
+  labs(x = "City mileage")
+
+# Scatter plot between city and highway mileage
+# this shows a linear relationship
+# then add a regression line on top
+ggplot(mpg, aes(x = cty,
+                y = hwy)) +
+  geom_point() +
+  geom_smooth(method = "lm")