Project 6 - Data generation and artwork

Author

Affiliation

Andrew Moles

Learning Developer, Digital Skills Lab

On this page

• Learning objectives:
• Outcomes
  • Outcome 1 - Generate a dataset
  • Outcome 2 - Make artwork from that dataset
• Steps to help you get to the outcome
  • Part 1 - the setup
  • Part 2 - making a colour palette
  • Part 3 - random sampling
  • Part 4 - generating a sequence of numbers
  • Part 5 - making a factor
  • Part 6 - generating a data frame
  • Part 7 - generate a randomised normal distribution
  • Part 8 - stream plot
  • Part 9 - aesthetic adjustments
  • Part 10 - setting a seed
  • Final task - fill out the survey!

Learning objectives:

• Create your own data using sampling, distribution, and sequence generation
• Visualise the data to make artwork

Outcomes

We will write a program that will randomly generate a dataset which we will then make some artwork from. As we are generating data and using random sampling your result will look a bit different from the outcomes. You will likely end up with different colours and different distributions.

We will be aiming for two outcomes in this project.

Outcome 1 - Generate a dataset

Outcome 2 - Make artwork from that dataset

Steps to help you get to the outcome

Part 1 - the setup

Open an R script file and save it.

Part 2 - making a colour palette

Make a vector, using the below colours, to make a colour palette.

'#ffc09f','#ffd799','#ffee93','#fef2ad','#fcf5c7','#cee2d0','#a0ced9','#a7e3c8','#adf7b6','#264653','#287271','#2a9d8f','#e9c46a','#f4a261','#e76f51','#e97c61'

Part 3 - random sampling

Take a sample of the colour vector you just created, selecting four elements. Assign the result to a new vector.

When sampling the colour vector you created, how do you know if you have sampled with or without replacement?

Part 4 - generating a sequence of numbers

Generate a sequence, starting from 0 through to 100. Make the length of the sequence 30. Assign the result so we can use it later.

Part 5 - making a factor

Make a factor that contains the numbers 1 through to the length of the sample you took from the colour palette. Assign the result so we can use it later.

Below is what your output should look like given we have sampled 4 colours from our colour palette.

[1] 1 2 3 4
Levels: 1 2 3 4

Part 6 - generating a data frame

Using the sequence of numbers and the factor you made, create a data frame from all combinations of the supplied vectors. Make sure to assign the result.

You should end up with a data frame with 2 columns which have all combinations of the vectors you supplied.

Part 7 - generate a randomised normal distribution

Generate a randomised normal distribution, whereby you use the mean and standard deviation of the sequence you generated.

Add the result as a column to the data frame you just created.

After completing this step you should have a dataset similar to what is shown in Section 2.1.

Part 8 - stream plot

Using a combination of the ggplot2 and ggstream packages make the artwork, which is known as a stream plot.

Part 9 - aesthetic adjustments

There are a few more minor adjustments to make to finish up our visualisation so it looks like what we see in Section 2.2.

• Add colours, which has two steps:
  • Make the fill and colour aesthetic to be your factor
  • Manually change the fill and colour scale so they use the sampled colour palette
• Add a complete theme to the visual which removes everything
• set the guides for fill and colour to none
• Adjust the type of the stream to proportional. You can test out the other types which are mirror and ridge

Part 10 - setting a seed

To guarantee that the same random values are produced each time you run the code we can set a seed. This makes our code reproducible.

Set a seed so that when you re-run the code you get the same result.

This needs to happen before you use any of the random generation functions, so add this to the top of the code you have written.

Final task - fill out the survey!

We are always looking to improve and iterate our workshops. Follow the link to give your feedback.