hi in this video we'll go over different
methods that data can be visualized
and how the data can be interpreted so
what is data visualization
it's when you use graphs charts images
that help you visualize complex
data here's an example
on the top is the raw data collected
about temperature
rainfall and sunlight in great britain
it's kind of hard to pull any useful
information from these numbers right
on the bottom the information has been
presented in a way that makes it much
less difficult to make sense of the data
you can easily see the location since a
map is used
and the colors represent the amount of
the rain or sunshine
so why do we want to visualize data well
it makes it easier to understand the
data and then we're able to
use information from the data when we
see it in a visual form
it's much faster than reading through
pages and pages of numbers
and this isn't just about maps and
rainfall data visualization assists
everywhere it's in science government
sports
everywhere you can see this data used
and data visualization is incredibly
useful because it helps us recognize
problems here's a visualization that
displays the amount of
endangered species across the united
states your eyes are almost instantly
drawn to the two locations with the
highest amount of endangered species
do you see them you can see that florida
and then the bottom left of the u.s
contain the most endangered species
this is helpful because now we know that
programs to save these species
should probably focus in those area and
data visualization has been around for
centuries
you can even count maps and map creation
as one of the first data visualizations
this is an example of a very early data
visualization
this was created to track napoleon's
losses along his route
now think back to this time period see
if you can actually
picture charles joseph menard creating
this visualization
he probably had a table of values drawn
out and he had to look at the value
and then very carefully plot the points
and make sure the distance between the
points were uniform
he had to probably have a little bit of
artistic talent
it had to take quite some time there
were no computers or database programs
back then it was all done by hand
in today's data visualization we have
come
so far we can process large amounts of
data
very quickly we can even keep it updated
so that it is
current and always accurate and then we
can add interactivity
as well this helps us blend science and
art
it makes our visualizations very nice to
look at
there are so many different kinds it's
not just graphs and pie charts anymore
and more being created every day now a
lot of these visualizations
seen here are a bit advanced so we're
going to start by looking at some of the
basic
most commonly used types
pie charts are a good choice when a
percentage can be useful in interpreting
the data
we don't have the exact value here but
that might not be what we're trying to
display
this pie chart shows how often twitter
users check their feed
if i were to ask you how many check once
a day
you could use the chart to figure that
out do you see it
it looks like about twelve percent looks
like twelve percent of twitter users
check their twitter once a day
so it doesn't actually matter how many
users we're talking about here
either way twelve percent of that group
of the twitter group
will probably check their twitter feed
once a day a line chart is great for
showing trends
over time so you can quickly compare the
broadband
rates for different countries looks like
denmark and the netherlands have the
best rate
also you can see the increase in the
rates for each individual country
so let's see has access to high speed
internet gotten better or worse for
these countries
well you can definitely see it's
increasing now bar charts are great for
comparing different categories
and this is actually a stacked bar chart
which offers even more information
in each individual bar now at first
glance you might notice that the first
bar
is the highest so ethan and joel cohen
have the greatest number of award wins
now there are three colors in the bar
and if you use the key on the right you
can see that they've won awards for
thrillers
dramas and crime films now what's
interesting as well is the third bar
from the left take a look
at steven spielberg's bar he may not
have won as many awards but look at all
the different colors
all the different genres of film that
he's one for that's very impressive as
well
so there's a lot of useful data from
this visualization
now having creativity in your
visualization can be very helpful when
interpreting the data
if you look at just the top two rows of
data it's hard to pull out
anything useful about lebron james
shooting statistics
but if we place these values on an
actual basketball court it becomes very
useful
if we were lebron james we could see
where we might want to practice a bit
more
and if we were the team playing against
him we now know
that we probably should keep him out of
the key where it shows him shooting at
66.7 percent
and he definitely shoots more from the
left side of the hoop so we might want
to cover him tighter when he's over
there
so how are these visualizations used
well there are a lot of public data sets
and these tools allow widespread access
so
anyone can go to the google public data
explorer or gap minder
and anyone can use the data to try to
find patterns find trends
and recognize problems and that is a
quick overview on the different types of
data visualizations
that we can use