WorkingWithData.R

# Working with Data

#Set Working directory
setwd("/Users/daviddryburgh/Documents/R_Programming")

# Read a CSV data file
cars <- read.csv("Cars.csv")

# Peek at the data
head(cars)

# Load the dplyr library
library(dplyr)

# Select a subset of columns
temp <- select(
  .data = cars,
  Transmission,
  Cylinders,
  Fuel.Economy
)

# Inspect the results
head(temp)

# Filter a subset of rows
temp <- filter(
  .data = temp,
  Transmission == "Automatic"
)

# Inspect the results
head(temp)

# Compute a new column 
temp <- mutate(
  .data = temp,
  Consumption = Fuel.Economy * 0.425
)

# Inspect the results
head(temp)

# Group by a column
temp <- group_by(
  .data = temp,
  Cylinders
)

# Inspect the results
head(temp)

# Aggregate based on groups, this showing the average consumption of cars
# based on the number of cyliders
temp <- summarize(
  .data = temp,
  Avg.Consumption = mean(Consumption)
)

# Inspect the results
head(temp)

# Arrange the rows in descending order
temp <- arrange(
  .data = temp,
  desc(Avg.Consumption)
)

# Inspect the results
head(temp)

# Convert to data frame
efficiency <- as.data.frame(temp)

# Inspect the results
print(efficiency)

# Chain methods together. %>% is a piping sequence to join methods together
# and write cleaner R code
efficiency <- cars %>%
  select(Fuel.Economy, Cylinders, Transmission) %>%
  filter(Transmission == "Automatic") %>%
  mutate(Consumption = Fuel.Economy * 0.425) %>%
  group_by(Cylinders) %>%
  summarize(Avg.Consumption = mean(Consumption)) %>%
  arrange(desc(Avg.Consumption)) %>%
  as.data.frame()

# Inspect the results
print(efficiency)

# Save the results to a CSV file
write.csv(
  x = efficiency,
  file = "Fuel Efficiency.csv",
  row.names = FALSE
)