R Learning Renault | 90% CERTIFIED |

renault_data$price <- as.numeric(gsub("[€,]", "", renault_data$price))

Renault twist: Compare the fuel economy of diesel vs. petrol Clio models after removing incomplete records.

Goal: Determine which Renault model offers the best balance of low price, high fuel efficiency, and good safety rating.

Steps in R:

Renault is a treasure trove of structured, interesting data:

These datasets allow you to practice core R skills: data cleaning, visualization, statistical testing, and even machine learning.

Use historical data to predict future prices or sales. r learning renault

library(tidymodels)
set.seed(123)
split <- initial_split(renault_data, prop = 0.75)
train <- training(split)
test <- testing(split)
model <- linear_reg() %>%
set_engine("lm") %>%
fit(price ~ hp + age + mileage, data = train)
predict(model, test)

Renault twist: Build a model to predict the resale value of a 5-year-old Renault Kadjar based on its original price, engine size, and accident history.