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In this video, we'll
create a basic line plot

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to visualize crime trends.

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Let's start by
reading in our data.

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We'll call it mvt for
motor vehicle thefts,

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and use the read.csv function
to read in the file mvt.csv.

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We'll add the argument
stringsAsFactors = FALSE,

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since we have a
text field, and we

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want to make sure
it's read in properly.

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Let's take a look at the
structure of our data

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using the str function.

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We have over
190,000 observations

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of three different variables--
the date of the crime,

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and the location of
the crime, in terms

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of latitude and longitude.

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We want to first convert the
Date variable to a format

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that R will recognize so that we
can extract the day of the week

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and the hour of the day.

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We can do this using
the strptime function.

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So we want to replace
our variable, Date,

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with the output of the
strptime function, which

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takes as a first argument
our variable, Date, and then

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as a second argument the
format that the date is in.

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Here, we can see in the
output from the str function

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that our format is the month
slash the day slash the year,

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and then the hour colon minutes.

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So our format equals, "%m/%d/%y
%H:%M", close the parentheses,

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and hit Enter.

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In this format, we can
extract the hour and the day

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of the week from
the Date variable,

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and we can add these as new
variables to our data frame.

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We can do this by first
defining our new variable,

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mvt$Weekday =
weekdays(mvt$Date).

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Then, to add the hour,
which we'll call mvt$Hour,

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we just take the hour
variable out of Date variable.

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This only exists because we
converted the Date variable.

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Let's take a look at the
structure of our data

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again to see what it looks like.

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Now, we have two more
variables-- Weekday,

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which gives the day
of the week, and Hour,

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which gives the hour of the day.

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Now, we're ready to
make some line plots.

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Let's start by
creating the line plot

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we saw in the previous video
with just one line and a value

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for every day of the week.

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We want to plot as that
value the total number

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of crimes on each
day of the week.

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We can get this
information by creating

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a table of the Weekday variable.

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This gives the total amount of
crime on each day of the week.

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Let's save this
table as a data frame

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so that we can pass it
to ggplot as our data.

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We'll call it WeekdayCounts, and
use the as.data.frame function

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to convert our table
to a data frame.

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Let's see what this looks
like with the str function.

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We can see that our data frame
has seven observations, one

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for each day of the week,
and two different variables.

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The first variable,
called Var1, gives

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the name of the day of the
week, and the second variable,

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called Freq, for frequency,
gives the total amount of crime

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on that day of the week.

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Now, we're ready
to make our plot.

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First, we need to load
the ggplot2 package.

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So we'll type library(ggplot2).

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Now, we'll create our plot
using the ggplot function.

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So type ggplot, and
then we need to give

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the name of our data,
which is WeekdayCounts.

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And then we need to
define our aesthetic.

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So our aesthetic
should have x = Var1,

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since we want the day of
the week on the x-axis,

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and y = Freq, since
we want the frequency,

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the number of crimes,
on the y-axis.

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Now, we just need to add
geom_line(aes(group=1)).

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This just groups all of
our data into one line,

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since we want one
line in our plot.

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Go ahead and hit Enter.

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We can see that this is very
close to the plot we want.

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We have the total
number of crime plotted

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by day of the week, but
our days of the week

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are a little bit out of order.

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We have Friday first, then
Monday, then Saturday,

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then Sunday, etc.

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What ggplot did was it
put the days of the week

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in alphabetical order.

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But we actually want the days of
the week in chronological order

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to make this plot a
bit easier to read.

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We can do this by making the
Var1 variable an ordered factor

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variable.

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This signals to ggplot that
the ordering is meaningful.

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We can do this by using
the factor function.

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So let's start by typing
WeekdayCounts$Var1,

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the variable we want to
convert, and set that equal

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to the output of
the factor function,

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where the first argument is our
variable, WeekdayCounts$Var1,

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the second argument
is ordered = TRUE.

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This says that we want
an ordered factor.

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And the third argument,
which is levels,

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should be equal to
a vector of the days

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of the week in the order
we want them to be in.

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We'll use the c
function to do this.

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So first, in quotes,
type "Sunday" --

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we want Sunday first-- and
then "Monday", "Tuesday",

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"Wednesday", "Thursday",
"Friday", "Saturday".

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Go ahead and close both
parentheses and hit Enter.

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Now, let's try our plot again by
just hitting the up arrow twice

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and hitting Enter.

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Now, this is the plot we want.

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We have the total crime
by day of the week

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with the days of the week
in chronological order.

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The last thing we'll
want to do to our plot

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is just change the
x- and y-axis labels,

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since they're not very
helpful as they are now.

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To do this, back
in the R console,

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just hit the up arrow to get
back to our plotting line,

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and then we'll add
xlab("Day of the Week").

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And then we'll add ylab("Total
Motor Vehicle Thefts").

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Now, this is the
plot we were trying

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to generate with descriptive
labels on the x- and y-axis.

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In the next video, we'll
add the hour of the day

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to our line plot, and
then create a heat map.