ggplot2 Exercises

Recreate the following plots shown below. Don't worry if your plots don't match exactly what is shown below, as long as you have a general understanding of ggplot2 and the grammar of graphics

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Important Note!

Some of the images may be distorted from the conversion to a web format

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For the first few plots, use the mpg dataset

library(ggplot2)
library(ggthemes)
head(mpg)

	manufacturer	model	displ	year	cyl	trans	drv	cty	hwy	fl	class
1	audi	a4	1.8	1999	4	auto(l5)	f	18	29	p	compact
2	audi	a4	1.8	1999	4	manual(m5)	f	21	29	p	compact
3	audi	a4	2	2008	4	manual(m6)	f	20	31	p	compact
4	audi	a4	2	2008	4	auto(av)	f	21	30	p	compact
5	audi	a4	2.8	1999	6	auto(l5)	f	16	26	p	compact
6	audi	a4	2.8	1999	6	manual(m5)	f	18	26	p	compact

Histogram of hwy mpg values:

Barplot of car counts per manufacturer with color fill defined by cyl count

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Switch now to use the txhousing dataset that comes with ggplot2

head(txhousing)

	city	year	month	sales	volume	median	listings	inventory	date
1	Abilene	2000	1	72	5380000	71400	701	6.3	2000
2	Abilene	2000	2	98	6505000	58700	746	6.6	2000.083
3	Abilene	2000	3	130	9285000	58100	784	6.8	2000.167
4	Abilene	2000	4	98	9730000	68600	785	6.9	2000.25
5	Abilene	2000	5	141	10590000	67300	794	6.8	2000.333
6	Abilene	2000	6	156	13910000	66900	780	6.6	2000.417

Create a scatterplot of volume versus sales. Afterwards play around with alpha and color arguments to clarify information.

Warning message:
: Removed 568 rows containing missing values (geom_point).

Add a smooth fit line to the scatterplot from above. Hint: You may need to look up geom_smooth()

Warning message:
: Removed 568 rows containing non-finite values (stat_smooth).Warning message:
: Removed 568 rows containing missing values (geom_point).

Great Job!

Up next you'll have a data visualization project in which you will build up a real data visualization used in The Economist.