When trying to understand historical drainage and climate information, it's important to understand the context of individual data points when examining historical data.
Kevin Bailey
When trying to understand historical drainage and climate information, it's important to understand the context of individual data points when examining historical data.
The lake depth slider tool uses the Lake Huron dataset that comes with the R datasets library to create a histogram of historical lake depths, and project a ranking line and return a percentile rank for a specific lake depth measurement via a sliderbar.
library(datasets)
data("LakeHuron")
It is written in R and using Shiny for the UI and Server components.
This is using the hist function for creating the histogram
hist(LakeHuron)
the ecdf function is used to generate the percentile rank for the input value based on the dataset
for example:
pct_rank <- round(ecdf(LakeHuron)(579), 2)
returns 0.44 for an input depth of 579
Check out the app at: https://kevinabailey.shinyapps.io/course_project