iPlots is a package which provides interactive statistical graphics, written in Java. You can find many interesting plots such as histograms, barcharts, scatterplots, boxplots, fluctuation diagrams, parallel coordinates plots and spineplots. The amazing part is that all of these plots support querying, linked highlighting, color brushing, and interactive changing of parameters.

Before proceeding, please follow our short tutorial.

Look at the examples given and try to understand the logic behind them. Then try to solve the exercises below using R and without looking at the answers. Then check the solutions.

to check your answers.

**Exercise 1**

Install and call the packages `iplots`

and `MASS`

in your working environment and then attach the dataset “Cars93”.

**Exercise 2**

Create a mosaic plot of the variables “AirBags”, “Cylinders” and “Origin” of the “Cars93” dataset. **HINT**: Use `imosaic()`

.

**Exercise 3**

Create a barchart of the variable “Fuel.tank.capacity” of the “Cars93” dataset. **HINT**: Use `ibar()`

.

**Exercise 4**

Get a spineplot of the barchart you created in Exercise 3. **HINT**: Use `spineplot`

.

**Exercise 5**

See how the variable “Type” is ordered. **HINT**: Use `levels()`

.

**Exercise 6**

Reverse the order of the variable “Type”, name it “Type2” and check the order of “Type2”. **HINT**: Use `ordered()`

and `levels()`

.

**Exercise 7**

Plot the barcharts of “Type” and “Type2” and spot the difference. **HINT**: Use `ibar()`

.

**Exercise 8**

Make a Parallel Coordinate Plot for all the continuous variables of “Cars93”. **HINT**: Use `ipcp()`

.

**Exercise 9**

Make a parallel boxplot for all “price” variables. **HINT**: Use `ibox()`

.

**Exercise 10**

Split the boxplot for “Wheelbase” by number of “Cylinders”. **HINT**: Use `ibox()`

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