Calculation between groups in one column in tidy data - r

Question

I have data like that:
df <- (
tibble(
ID = rep(1:2, 4),
Group = c("A", "B", "A", "B","A", "B", "A", "B"),
Parameter = c("Blood", "Blood", "Height", "Height", "Waist", "Waist", "Hip", "Hip"),
Value = c(6.3, 6.0, 180, 170, 90, 102, 60, 65))
)
I want to calculate the ratio between "Height" and "Waist" and between "Waist" and "Hip".
I have the following solution. But my solution requires using spread() and delivers only the calculation for "Waist-to-hip".
df <- rbind(df,
spread(df, Parameter, Value)
%>% transmute(ID = ID,
Group = Group,
Parameter = "Ratio.Height-to-Hip",
Value = Height / Hip,
Parameter = "Ratio.Waist-to-Hip",
Value = Waist / Hip))
Is it possible to stay in tidy data format and avoid switching to the long-format? Why is the calculation for "Height-to-hip" missing?

Answer 1

Here is one the possible solution:
# Calculate ratios "Height" vs "Waist" and "Waist" vs "Hip"
# 1. Load packages
library(tidyr)
library(dplyr)
# 2. Data set
df <- tibble(
id = rep(1:2, 4),
group = c("A", "B", "A", "B","A", "B", "A", "B"),
parameter = c("Blood", "Blood", "Height", "Height", "Waist", "Waist", "Hip", "Hip"),
value = c(6.3, 6.0, 180, 170, 90, 102, 60, 65))
# 3. Filter and transform data set
df <- df %>%
filter(parameter %in% c("Height", "Waist", "Hip")) %>%
spread(parameter, value)
# 4. Convert column names to lower case
colnames(df) <- tolower(colnames(df))
# 5. Calcutate ratios
df <- df %>%
mutate(
ratio_height_vs_waist = round(height / waist, 2),
ratio_waist_vs_hip = round(waist / hip, 2))

Answer 2

The main problem is that the data are not in a tidy format.
Two key features of the tidy format are (Wickham, 2013):
Each variable forms a column;
Each observation forms a row.
In its original format, your data violates these two rules. For example, the Parameter column contains four variables (Blood, Height, Waist, and Hip). The knock-on effect of grouping several variables within Parameter is that each observation has to be repeated across several rows. In general, repeated rows of an identifier (ID in this case) in the absence of repeated measures is a sign that two or more variables have been grouped under a single column.
Anyway, here's my attempt to clean the data (I have used mutate and and not transmute for illustrative purposes).
# Load packages
library(dplyr)
library(tidyr)
library(magrittr) # For the %<>% function, which I love
# Make data frame, df
df <- tibble(
ID = rep(1:2, 4),
Group = c("A", "B", "A", "B","A", "B", "A", "B"),
Parameter = c("Blood", "Blood", "Height", "Height", "Waist", "Waist", "Hip", "Hip"),
Value = c(6.3, 6.0, 180, 170, 90, 102, 60, 65))
# Wrangle df
df %<>%
# ID and Group appear to be repeated, so use them to group_by
group_by(ID, Group) %>%
# Spread the Value column by the Parameter column
spread(key = Parameter,
value = Value) %>%
# Ungroup, just because its a good habit
ungroup() %>%
# Generate new columns.
mutate(Ratio_height_to_hip = Height / Hip,
Ratio_waist_to_hip = Waist / Hip)
# Print df
df
#> # A tibble: 2 x 8
#> ID Group Blood Height Hip Waist Ratio_height_to_hip
#> <int> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 A 6.3 180 60 90 3.000000
#> 2 2 B 6.0 170 65 102 2.615385
#> # ... with 1 more variables: Ratio_waist_to_hip <dbl>

Answer 3

df <- df %>%
spread(Parameter, Value) %>%
mutate("Ratio.Height-to-Hip" = Height / Hip) %>%
mutate("Ratio.Waist-to-Hip" = Hip / Waist) %>%
gather("Parameter", "Value", -c("ID", "Group"))
Your data is not in tidy format ;) If you want your data in tidy format remove the last step.