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This is the third part of our data visualization series and at this part we will explore the features of two more of the charts that googleVis provides.
Read the examples below to understand the logic of what we are going to do and then test yous skills with the exercise set we prepared for you. Lets begin!
Answers to the exercises are available here.
Package Installation
As you already know, the first thing you have to do is install and load the googleVis package with:
install.packages("googleVis")
library(googleVis)
NOTE: The charts are created locally by your browser. In case they are not displayed at once press F5 to reload the page.
Scatter chart
It is quite simple to create a scatter chart with googleVis. We will use the cars
dataset. Look at the example below:
ScatterC <- gvisScatterChart(cars)
plot(ScatterC)
Exercise 1
Create a list named “ScatterC” and pass to it the cars
dataset as a scatter chart. HINT: Use gvisScatterChart()
.
Exercise 2
Plot the the scatter chart. HINT: Use plot()
.
Titles
It is time to learn how to enhance the appearance of our googleVis charts. We shall give a title to the chart and also name hAxis and vAxis. Look at the example:
options=list(title="Cars", vAxis="{title:'speed'}",
hAxis="{title:'dist'}" )
Exercise 3
Name your chart “Cars”, your chart’s vAxis “speed”, your chart’s hAxis “dist” and plot the chart. HINT: Use list()
.
Size
You can adjust the size with width
and height
.
Exercise 4
Set your chart’s width
to 600 and height
to 300.
Legend
You can deactivate your chart’s legend
if you set it to “none”.
Exercise 5
Deactivate your chart’s legend
.
- Work extensively with the GoogleVis package and its functionality
- Learn what visualizations exist for your specific use case
- And much more
Point size & Line width
You can determine the size of the chart’s points with pointsize
and also choose to unite them with line with linewidth
. For example:
pointSize=4,linewidth=3
Exercise 6
Set point size to 3 and line width to 2.
Bubble Chart
Another amazing type of chart that googleVis provides is the bubble chart. You can create a simple Bubble Chart of the Fruits
dataset like this:
BubbleC <- gvisBubbleChart(Fruits)
plot(BubbleC)
Exercise 7
Create a list named “BubbleC” and pass to it the Fruits
dataset as a bubble chart. HINT: Use gvisBubbleChart()
.
Exercise 8
Plot the chart. HINT: Use plot()
.
Bubble Chart’s Features
As you can see, you created a bubble chart but it seems to be useless. In order to make it useful you should pass to it some of your dataset’s variables as features. It depends on what you want to be displayed and how. If you type head(Fruits)
you can easily recognize the numeric variables of your dataset. Then you can use them like this:
BubbleC <- gvisBubbleChart(Fruits,idvar="VAR1",
xvar="VAR2", yvar="VAR3",
colorvar="VAR4", sizevar="VAR5")
Exercise 9
Find the numeric variables of Fruits
, then set “Fruit” as idvar
, “Sales” as xvar
, “Expenses” as yvar
, “Year” as colorvar
and “Profit” as sizevar
and plot your chart. HINT: Use head()
.
Data range
You can also adjust the minimum and maximum number of hAxis and vAxis that you want to be displayed. Look at the example below:
options=list(
hAxis='{minValue:50, maxValue:150}')
Exercise 10
Set your hAxis range from 70 to 130 and your vAxis range from 50 to 100.
Related exercise sets:
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