The year 2024 in my habits

………………………….

Analysing my achievements for the year 2024 in my different habits.

# Loading the relevant packages
library(tidyverse)          # Data Wrangling
library(gt)                 # Displaying beautiful tables
library(ggiraph)            # Interactive Graphics
library(showtext)           # Display fancy text in ggplot2
library(fontawesome)        # Icons and Fonts 
 
# Setting font defaults
font_add_google("Monda", "body_font")
showtext_auto()

# Set the default theme with a custom font family
theme_set(theme_minimal(base_family = "body_font"))

# Setting default options for the interactive graphics
set_girafe_defaults(
  opts_hover = opts_hover(
    css = "fill:yellow;stroke:black;stroke-width:1px"
    ),
  opts_tooltip = opts_tooltip(
    css = "padding:3px;color:black;background-color:white;"
    )
)

Loading the data, studying and understanding it. Cleaning the names.

# Set the working directory (I didnt want to host raw data on GitHub)
list.files("loop_habits")

# Define the directory containing the CSV files
directory <- "loop_habits"

# List all CSV files in the directory
csv_files <- list.files(
  path = directory, 
  pattern = "\\.csv$", 
  full.names = TRUE
  )

# Extract base names (without file extension) to use as object names
file_names <- tools::file_path_sans_ext(basename(csv_files)) |>
  tolower()

# Read each CSV file and assign it to an object with the corresponding name
purrr::walk2(
  csv_files, 
  file_names, 
  ~ assign(.y, read_csv(.x), 
           envir = .GlobalEnv)
  )

library(janitor)
# Apply janitor::clean_names() to all created objects
purrr::walk(
  file_names, ~
    {
      cleaned_data <- get(.x) |>  clean_names() 
      # Retrieve object, clean names
      
      assign(.x, cleaned_data, envir = .GlobalEnv) 
      # Reassign cleaned data back to the same object
    }
  )

# Remove the temporary files
rm(csv_files, directory, file_names)

Exploring the raw data in the root folder - the overall habits - to make a beautiful table in {gt} tables

habits <- habits |> 
  select(
    position,
    name,
    question,
    num_repetitions,
    interval
  ) |> 
  mutate(
    position = as.numeric(position),
    interval = case_when(
      interval == 1 ~ "Daily",
      interval == 7 ~ "Weekly",
      .default = NA
    )
  ) |> 
  rename(description = question)


checkmarks <- checkmarks |> 
  mutate(
    day_of_week = fct_rev(wday(date, label = T, abbr = F)),
    day_number = yday(date),
    week_number = week(date),
    month_year = month(date, label = TRUE),
    walk_cycle = walk_cycle / 1000,
    date = format(date, "%d %B"),
    id = row_number()
  )

Table 1: The different habits that I tracked

habits |> 
  gt() |> 
  cols_label(
    position = "S. No.",
    name = "Name of the Habit",
    description = "Description / Question",
    num_repetitions = "Target number of repetitions",
    interval = "Frequency"
  ) |> 
  tab_header(
    title = "My Atomic Habits (2024)",
    subtitle = "The list of habits I tracked for myself in the year 2024",
  ) |> 
  gtExtras::gt_theme_espn()

Next, exploring the habits - walking/cycling habits

plot1 <- checkmarks |> 
  ggplot(
    mapping = aes(
      x = week_number,
      y = day_of_week, 
      fill = walk_cycle,
      data_id = id,
      tooltip = paste0(date, "\n", 
                       day_of_week, "\n",
                       round(walk_cycle, 2), 
                       " hours")
    )
  ) +
  geom_tile_interactive(
    colour = "white",
    linewidth = 1
  ) +
  scale_x_continuous(
    limits = c(0, 52),
    breaks = seq(from = 0, to = 52, length.out = 5),
    labels = c("Jan", "Mar", "Jun", "Sep", "Dec")
  ) +
  coord_fixed() +
  paletteer::scale_fill_paletteer_c(
    "grDevices::Blues 3", 
    direction = -1
  ) +
  labs(
    title = "Walking (number of hours per day)",
    y = NULL, x = NULL,
    fill = "Hours (per day)"
  ) +
  theme(
    legend.title = element_text(vjust = 0.5, hjust = 0.5),
    panel.grid = element_blank(),
    legend.position = "bottom",
    legend.title.position = "top"
  )

girafe(
  ggobj = plot1
)

facet_labels <- c("Number of days walked during the month", "Average duration walked per day")
names(facet_labels) <- c("walk_days", "walk_mean")
checkmarks |> 
  group_by(month_year) |> 
  summarize(
    walk_mean = round(mean(walk_cycle), 1),
    walk_days = sum(walk_cycle > 0)
  ) |> 
  pivot_longer(
    cols = -month_year,
    names_to = "facet_var",
    values_to = "value"
  ) |> 
  ggplot(
    mapping = aes(
      x = value,
      y = month_year
    )
  ) +
  geom_col(
    alpha = 0.5
  ) +
  geom_text(
    mapping = aes(
      label = value
    ),
    hjust = -0.1
  ) +
  facet_wrap(
    ~facet_var, 
    scales = "free_x",
    labeller = labeller(facet_var = facet_labels)
  ) +
  labs(
    x = NULL, y = NULL
  ) +
  theme(
    panel.grid = element_blank()
  )