consolidate ggplot examples in single dir

ggplot_examples/crickets.r

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+library(tidyverse)
+library(modeldata)
+
+# the dataset
+View(crickets)
+
+# basic scatter plot
+ggplot(crickets, aes(x = temp,
+                     y = rate,
+                     color = species)) +
+  geom_point() + 
+  labs(x = "Termperature",
+       y = "Chirp Rate",
+       color = "Species",
+       title = "Cricket Chripts",
+       caption = "Source: McDonal (2009)") +
+  scale_color_brewer(palette = "Dark2")
+
+# modifying basic properties of the plot 
+ggplot(crickets, aes(x = temp,
+                     y = rate)) +
+  geom_point(color = "red",
+             size = 2,
+             shape = "square") + 
+  labs(x = "Termperature",
+       y = "Chirp Rate",
+       title = "Cricket Chripts",
+       caption = "Source: McDonal (2009)") +
+  scale_color_brewer(palette = "Dark2")
+
+# learn more about the options for the geom
+# with ?geom_point
+
+# adding another layer like a regression line
+ggplot(crickets, aes(x = temp,
+                     y = rate)) +
+  geom_point() + 
+  geom_smooth(method = "lm",
+              se = FALSE) +
+  labs(x = "Termperature",
+       y = "Chirp Rate",
+       title = "Cricket Chripts",
+       caption = "Source: McDonal (2009)") +
+  scale_color_brewer(palette = "Dark2")
+
+# adding another regression line per species
+ggplot(crickets, aes(x = temp,
+                     y = rate,
+                     color = species)) +
+  geom_point() + 
+  geom_smooth(method = "lm",
+              se = FALSE) +
+  labs(x = "Termperature",
+       y = "Chirp Rate",
+       title = "Cricket Chripts",
+       caption = "Source: McDonal (2009)") +
+  scale_color_brewer(palette = "Dark2") +
+  theme_light()
+
+# other plots like histograms and frequency poly
+ggplot(crickets, aes(x = rate)) +
+  geom_histogram(bins = 15) # one quantitative variable
+
+# frequency polynome
+ggplot(crickets, aes(x = rate)) +
+  geom_freqpoly(bins = 15) 
+
+# bar plot with fill color according to species, no legend
+ggplot(crickets, aes(x = species,
+                     fill = species)) + 
+  geom_bar(show.legend = FALSE) +
+  scale_fill_brewer(palette = "Dark2")
+
+# boxplot with color equal to species
+ggplot(crickets, aes(x = species,
+                     y = rate,
+                     color = species)) +
+  geom_boxplot(show.legend = FALSE) +
+  scale_color_brewer(palette = "Dark2") +
+  theme_minimal()
+
+# facetign (side by side)
+# show the differnce between species
+
+# not great:
+ggplot(crickets, aes(x = rate,
+                     fill = species)) +
+  geom_histogram(bins = 15) +
+  scale_fill_brewer(palette = "Dark2")
+
+# better style
+ggplot(crickets, aes(x = rate,
+                     fill = species)) +
+  geom_histogram(bins = 15,
+                 show.legend = FALSE) +
+  facet_wrap(~species,
+             ncol = 1) +
+  scale_fill_brewer(palette = "Dark2")

ggplot_examples/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")