First thing first - install necessary packages if not already installed
rm(list = ls())
library(tidyverse)
library(dplyr)
library(ggplot2)
Now let us set the directory and get going
##Load the data
nihills <- read.csv(file = "nihills.csv")
str(nihills)
## 'data.frame': 23 obs. of 5 variables:
## $ X : chr "Binevenagh" "Slieve Gullion" "Glenariff Mountain" "Donard & Commedagh" ...
## $ dist : num 7.5 4.2 5.9 6.8 5 4.8 4.3 3 2.5 12 ...
## $ climb: int 1740 1110 1210 3300 1200 950 1600 1500 1500 5080 ...
## $ time : num 0.858 0.467 0.703 1.039 0.541 ...
## $ timef: num 1.064 0.623 0.887 1.214 0.637 ...
Check for missing values
sum(is.na(nihills))
## [1] 0
Wow!! no missing values`.
summary(nihills)
## X dist climb time
## Length:23 Min. : 2.500 Min. : 750 Min. :0.3247
## Class :character 1st Qu.: 4.000 1st Qu.:1205 1st Qu.:0.4692
## Mode :character Median : 4.500 Median :1500 Median :0.5506
## Mean : 5.778 Mean :2098 Mean :0.8358
## 3rd Qu.: 5.800 3rd Qu.:2245 3rd Qu.:0.7857
## Max. :18.900 Max. :8775 Max. :3.9028
## timef
## Min. :0.4092
## 1st Qu.:0.6158
## Median :0.7017
## Mean :1.1107
## 3rd Qu.:1.0014
## Max. :5.9856
According to the summary statistics - X is the name of the participant, Maximum distance covered is 18.9 units and minimum is 2.5 units. Climb starts from 750 units and the max altitude is 8775 units
As the climb increases, so is the time - believe me…
ggplot(nihills, aes(climb, timef)) + geom_line(color="Brown") +ggtitle("Time to climb")+ theme(panel.background = element_blank()) + theme(plot.title = element_text(hjust = 0.5))