Data Manipulation with dplyr

# Load the Tidyverse
library(tidyverse)

# Load the course datasets
babynames <- read_rds("datasets/babynames.rds")
counties <- read_rds("datasets/counties.rds")

babynames %>%
  # Filter for the year 1990
  filter(year==1990) %>%
  # Sort the number column in descending order 
  arrange(desc(number))

babynames %>%
  # Find the most common name in each year
  group_by(year) %>%
  slice_max(number,n=1)

selected_names <- babynames %>%
  # Filter for the names Steven, Thomas, and Matthew 
  filter(name %in% c("Steven", "Thomas", "Matthew"))

# Plot the names using a different color for each name
ggplot(selected_names, aes(x =year, y = number, color = name)) +
  geom_line()

# Calculate the fraction of people born each year with the same name
babynames %>%
  group_by(year) %>%
  mutate(year_total = sum(number)) %>%
  ungroup() %>%
  mutate(fraction = number / year_total) %>%
  # Find the year each name is most common
  group_by(name) %>%
  slice_max(fraction, n = 1)

names_normalized <- babynames %>%
  # Add columns name_total and name_max for each name
  group_by(name) %>%
  mutate(name_total = sum(number),
         name_max = max(number)) %>%
  # Ungroup the table 
  ungroup() %>%
  # Add the fraction_max column containing the number by the name maximum 
  mutate(fraction_max=number/name_max)

names_filtered <- names_normalized %>%
  # Filter for the names Steven, Thomas, and Matthew
  filter(name %in% c("Steven","Thomas","Matthew"))

# Visualize the names in names_filtered over time
ggplot(names_filtered,aes(x=year,y=fraction_max,color=name))+
geom_line()

babynames_fraction <- babynames %>%
  group_by(year) %>%
  mutate(year_total = sum(number)) %>%
  ungroup() %>%
  mutate(fraction = number / year_total)
babynames_fraction %>%
  # Arrange the data in order of name, then year 
  arrange(name,year) %>%
  # Group the data by name
  group_by(name) %>%
  # Add a ratio column that contains the ratio of fraction between each year 
  mutate(ratio=fraction/lag(fraction))

babynames_fraction <- babynames %>%
  group_by(year) %>%
  mutate(year_total = sum(number)) %>%
  ungroup() %>%
  mutate(fraction = number / year_total)
babynames_ratios_filtered <- babynames_fraction %>%
                     arrange(name, year) %>%
                     group_by(name) %>%
                     mutate(ratio = fraction / lag(fraction)) %>%
                     filter(fraction >= 0.00001)
babynames_ratios_filtered %>%
  # Extract the largest ratio from each name 
  slice_max(ratio,n=1) %>%
  # Sort the ratio column in descending order 
  arrange(desc(ratio)) %>%
  # Filter for fractions greater than or equal to 0.001
  filter(fraction >= 0.001)