title | week | subtitle | type | reading | tasks | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Your first script |
1 |
Write a script that reads in data, calculates a statistic, and makes a plot. |
Case Study |
|
|
- Datacamp's How to Make a Histogram with Basic R
- Datacamp's How to Make a Histogram with ggplot
You are working on a new project and your colleague has asked you to calculate the mean Petal Length in the dataset she collected in the field.
It looks like this:
Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species |
---|---|---|---|---|
5.1 | 3.5 | 1.4 | 0.2 | setosa |
4.9 | 3.0 | 1.4 | 0.2 | setosa |
4.7 | 3.2 | 1.3 | 0.2 | setosa |
4.6 | 3.1 | 1.5 | 0.2 | setosa |
5.0 | 3.6 | 1.4 | 0.2 | setosa |
5.4 | 3.9 | 1.7 | 0.4 | setosa |
4.6 | 3.4 | 1.4 | 0.3 | setosa |
5.0 | 3.4 | 1.5 | 0.2 | setosa |
4.4 | 2.9 | 1.4 | 0.2 | setosa |
4.9 | 3.1 | 1.5 | 0.1 | setosa |
5.4 | 3.7 | 1.5 | 0.2 | setosa |
4.8 | 3.4 | 1.6 | 0.2 | setosa |
4.8 | 3.0 | 1.4 | 0.1 | setosa |
4.3 | 3.0 | 1.1 | 0.1 | setosa |
5.8 | 4.0 | 1.2 | 0.2 | setosa |
5.7 | 4.4 | 1.5 | 0.4 | setosa |
5.4 | 3.9 | 1.3 | 0.4 | setosa |
5.1 | 3.5 | 1.4 | 0.3 | setosa |
5.7 | 3.8 | 1.7 | 0.3 | setosa |
5.1 | 3.8 | 1.5 | 0.3 | setosa |
5.4 | 3.4 | 1.7 | 0.2 | setosa |
5.1 | 3.7 | 1.5 | 0.4 | setosa |
4.6 | 3.6 | 1.0 | 0.2 | setosa |
5.1 | 3.3 | 1.7 | 0.5 | setosa |
4.8 | 3.4 | 1.9 | 0.2 | setosa |
5.0 | 3.0 | 1.6 | 0.2 | setosa |
5.0 | 3.4 | 1.6 | 0.4 | setosa |
5.2 | 3.5 | 1.5 | 0.2 | setosa |
5.2 | 3.4 | 1.4 | 0.2 | setosa |
4.7 | 3.2 | 1.6 | 0.2 | setosa |
4.8 | 3.1 | 1.6 | 0.2 | setosa |
5.4 | 3.4 | 1.5 | 0.4 | setosa |
5.2 | 4.1 | 1.5 | 0.1 | setosa |
5.5 | 4.2 | 1.4 | 0.2 | setosa |
4.9 | 3.1 | 1.5 | 0.2 | setosa |
5.0 | 3.2 | 1.2 | 0.2 | setosa |
5.5 | 3.5 | 1.3 | 0.2 | setosa |
4.9 | 3.6 | 1.4 | 0.1 | setosa |
4.4 | 3.0 | 1.3 | 0.2 | setosa |
5.1 | 3.4 | 1.5 | 0.2 | setosa |
5.0 | 3.5 | 1.3 | 0.3 | setosa |
4.5 | 2.3 | 1.3 | 0.3 | setosa |
4.4 | 3.2 | 1.3 | 0.2 | setosa |
5.0 | 3.5 | 1.6 | 0.6 | setosa |
5.1 | 3.8 | 1.9 | 0.4 | setosa |
4.8 | 3.0 | 1.4 | 0.3 | setosa |
5.1 | 3.8 | 1.6 | 0.2 | setosa |
4.6 | 3.2 | 1.4 | 0.2 | setosa |
5.3 | 3.7 | 1.5 | 0.2 | setosa |
5.0 | 3.3 | 1.4 | 0.2 | setosa |
7.0 | 3.2 | 4.7 | 1.4 | versicolor |
6.4 | 3.2 | 4.5 | 1.5 | versicolor |
6.9 | 3.1 | 4.9 | 1.5 | versicolor |
5.5 | 2.3 | 4.0 | 1.3 | versicolor |
6.5 | 2.8 | 4.6 | 1.5 | versicolor |
5.7 | 2.8 | 4.5 | 1.3 | versicolor |
6.3 | 3.3 | 4.7 | 1.6 | versicolor |
4.9 | 2.4 | 3.3 | 1.0 | versicolor |
6.6 | 2.9 | 4.6 | 1.3 | versicolor |
5.2 | 2.7 | 3.9 | 1.4 | versicolor |
5.0 | 2.0 | 3.5 | 1.0 | versicolor |
5.9 | 3.0 | 4.2 | 1.5 | versicolor |
6.0 | 2.2 | 4.0 | 1.0 | versicolor |
6.1 | 2.9 | 4.7 | 1.4 | versicolor |
5.6 | 2.9 | 3.6 | 1.3 | versicolor |
6.7 | 3.1 | 4.4 | 1.4 | versicolor |
5.6 | 3.0 | 4.5 | 1.5 | versicolor |
5.8 | 2.7 | 4.1 | 1.0 | versicolor |
6.2 | 2.2 | 4.5 | 1.5 | versicolor |
5.6 | 2.5 | 3.9 | 1.1 | versicolor |
5.9 | 3.2 | 4.8 | 1.8 | versicolor |
6.1 | 2.8 | 4.0 | 1.3 | versicolor |
6.3 | 2.5 | 4.9 | 1.5 | versicolor |
6.1 | 2.8 | 4.7 | 1.2 | versicolor |
6.4 | 2.9 | 4.3 | 1.3 | versicolor |
6.6 | 3.0 | 4.4 | 1.4 | versicolor |
6.8 | 2.8 | 4.8 | 1.4 | versicolor |
6.7 | 3.0 | 5.0 | 1.7 | versicolor |
6.0 | 2.9 | 4.5 | 1.5 | versicolor |
5.7 | 2.6 | 3.5 | 1.0 | versicolor |
5.5 | 2.4 | 3.8 | 1.1 | versicolor |
5.5 | 2.4 | 3.7 | 1.0 | versicolor |
5.8 | 2.7 | 3.9 | 1.2 | versicolor |
6.0 | 2.7 | 5.1 | 1.6 | versicolor |
5.4 | 3.0 | 4.5 | 1.5 | versicolor |
6.0 | 3.4 | 4.5 | 1.6 | versicolor |
6.7 | 3.1 | 4.7 | 1.5 | versicolor |
6.3 | 2.3 | 4.4 | 1.3 | versicolor |
5.6 | 3.0 | 4.1 | 1.3 | versicolor |
5.5 | 2.5 | 4.0 | 1.3 | versicolor |
5.5 | 2.6 | 4.4 | 1.2 | versicolor |
6.1 | 3.0 | 4.6 | 1.4 | versicolor |
5.8 | 2.6 | 4.0 | 1.2 | versicolor |
5.0 | 2.3 | 3.3 | 1.0 | versicolor |
5.6 | 2.7 | 4.2 | 1.3 | versicolor |
5.7 | 3.0 | 4.2 | 1.2 | versicolor |
5.7 | 2.9 | 4.2 | 1.3 | versicolor |
6.2 | 2.9 | 4.3 | 1.3 | versicolor |
5.1 | 2.5 | 3.0 | 1.1 | versicolor |
5.7 | 2.8 | 4.1 | 1.3 | versicolor |
6.3 | 3.3 | 6.0 | 2.5 | virginica |
5.8 | 2.7 | 5.1 | 1.9 | virginica |
7.1 | 3.0 | 5.9 | 2.1 | virginica |
6.3 | 2.9 | 5.6 | 1.8 | virginica |
6.5 | 3.0 | 5.8 | 2.2 | virginica |
7.6 | 3.0 | 6.6 | 2.1 | virginica |
4.9 | 2.5 | 4.5 | 1.7 | virginica |
7.3 | 2.9 | 6.3 | 1.8 | virginica |
6.7 | 2.5 | 5.8 | 1.8 | virginica |
7.2 | 3.6 | 6.1 | 2.5 | virginica |
6.5 | 3.2 | 5.1 | 2.0 | virginica |
6.4 | 2.7 | 5.3 | 1.9 | virginica |
6.8 | 3.0 | 5.5 | 2.1 | virginica |
5.7 | 2.5 | 5.0 | 2.0 | virginica |
5.8 | 2.8 | 5.1 | 2.4 | virginica |
6.4 | 3.2 | 5.3 | 2.3 | virginica |
6.5 | 3.0 | 5.5 | 1.8 | virginica |
7.7 | 3.8 | 6.7 | 2.2 | virginica |
7.7 | 2.6 | 6.9 | 2.3 | virginica |
6.0 | 2.2 | 5.0 | 1.5 | virginica |
6.9 | 3.2 | 5.7 | 2.3 | virginica |
5.6 | 2.8 | 4.9 | 2.0 | virginica |
7.7 | 2.8 | 6.7 | 2.0 | virginica |
6.3 | 2.7 | 4.9 | 1.8 | virginica |
6.7 | 3.3 | 5.7 | 2.1 | virginica |
7.2 | 3.2 | 6.0 | 1.8 | virginica |
6.2 | 2.8 | 4.8 | 1.8 | virginica |
6.1 | 3.0 | 4.9 | 1.8 | virginica |
6.4 | 2.8 | 5.6 | 2.1 | virginica |
7.2 | 3.0 | 5.8 | 1.6 | virginica |
7.4 | 2.8 | 6.1 | 1.9 | virginica |
7.9 | 3.8 | 6.4 | 2.0 | virginica |
6.4 | 2.8 | 5.6 | 2.2 | virginica |
6.3 | 2.8 | 5.1 | 1.5 | virginica |
6.1 | 2.6 | 5.6 | 1.4 | virginica |
7.7 | 3.0 | 6.1 | 2.3 | virginica |
6.3 | 3.4 | 5.6 | 2.4 | virginica |
6.4 | 3.1 | 5.5 | 1.8 | virginica |
6.0 | 3.0 | 4.8 | 1.8 | virginica |
6.9 | 3.1 | 5.4 | 2.1 | virginica |
6.7 | 3.1 | 5.6 | 2.4 | virginica |
6.9 | 3.1 | 5.1 | 2.3 | virginica |
5.8 | 2.7 | 5.1 | 1.9 | virginica |
6.8 | 3.2 | 5.9 | 2.3 | virginica |
6.7 | 3.3 | 5.7 | 2.5 | virginica |
6.7 | 3.0 | 5.2 | 2.3 | virginica |
6.3 | 2.5 | 5.0 | 1.9 | virginica |
6.5 | 3.0 | 5.2 | 2.0 | virginica |
6.2 | 3.4 | 5.4 | 2.3 | virginica |
5.9 | 3.0 | 5.1 | 1.8 | virginica |
To work with only one column in the iris
dataset, try typing iris$Sepal.Length
. What does the $
do?
For the histogram, you can either use the basic hist()
function (easier but less powerful) or try to use the geom_hist()
function in ggplot (more complicated but much more powerful). See the reading list for hints on these two functions.
When you complete this task, you will have done some 'reproducible research' resulting in a script that calculates a statistic and makes a graph. In future lessons we'll cover how to save the graphic to your hardrive (if you are curious, check out the examples in ?png
)
- Create a new R script in RStudio (File->New File->R Script)
- Save this file somewhere you will find it later
- In your new script, load the iris dataset with
data(iris)
- Read the help file for the function that calculates the mean (you can run
?mean
or use the GUI). - Calculate the mean of the
Petal.Length
field and save it as an object namedpetal_length_mean
- Plot the distribution of the
Petal.Length
column as a histogram (?hist
) - Save the script
- Click 'Source' in RStudio to run your script from beginning to end