Challenge 7: Incorporating Multiple Inputs
Functions + Fish
Condition Index
A frequently used measurement for fish health is a condition index (Wikipedia article). The following simple equation can be used to calculate the approximate condition index of a fish:
\[\text{condition index} = \frac{weight}{length^3} \times 100\]
1. There are specific units required for the calculation of a condition index – length must be in centimeters and weight must be in grams. The weight data for the Blackfoot River fish were collected in grams; the length data were collected in millimeters. Transform the length data to the correct units.
2. Collecting data of this sort can be very messy! Write a function that will replace unlikely length and weight measurements with NA. Your function should accept at least three inputs:
- a vector of measurements,
- the minimum reasonable value,
- the maximum reasonable value.
If a value falls outside these bounds, you should replace it with an NA.
If you are struggling with the structure of your function, I would suggest reading the Mutating Function from R4DS.
3. After consulting the Montana Record Table for the four species of trout included in these data, I have conjectured that it is unlikely to have measurements for fish below 5 cm and above 80 cm in length or below 10 g and above 4,000 g in weight. Use your function to modify the length and weight columns of the fish dataset based on my cutoffs.
4. Write a function to calculate the condition index of a fish, given inputs of weight and length.
Consider whether you will write a function that works with vectors (accepting vectors as inputs) or a function that works with data frames (accepting a dataset and variable names as inputs)!
5. Make a thoughtful visualization of how fish conditions have varied over the duration of this study.
… you need to use at least a third variable!