diff --git a/README.md b/README.md
index c8a01de..12b320a 100644
--- a/README.md
+++ b/README.md
@@ -5,6 +5,7 @@ It's like dotfiles, but no, it's just Lua scripts I find useful.
 - `2webm.lua`: Converts everything in the working directory to .webm files.
 - `llm.lua`: (Windows only!) A very WIP script for working with LLMs through WSL using [ollama](https://github.com/jmorganca/ollama).
 - `print-arguments.lua`: For testing how a Lua script receives arguments, because this can be platform-specific.
+- `storage-statistics.lua`: Prints a variety of statistics about the files within the current directory. Requires LFS.
 - `test.lua`: (Dev Test) Used repeatedly while working on these scripts to verify minor details I'm forgetful about.
 - `utility-functions.lua`: (Library) Required for many of these scripts to run.
 - `video-dl.lua`: A few premade command lines for using `yt-dlp` to download what I want quicker.
diff --git a/storage-statistics.lua b/storage-statistics.lua
new file mode 100644
index 0000000..0be6711
--- /dev/null
+++ b/storage-statistics.lua
@@ -0,0 +1,233 @@
+#!/usr/bin/env luajit
+
+-- Primarily written by ChatGPT using GPT-3.5, with corrections and modifications by me.
+-- Do whatever the hell you want with it.
+
+local lfs = require "lfs"
+
+-- Function to get the filesize of a given file
+function get_filesize(filepath)
+    local file = io.open(filepath, "rb")
+    if file then
+        local size = file:seek("end")
+        file:close()
+        return size
+    else
+        return nil
+    end
+end
+
+-- Function to recursively traverse directories and get file sizes
+function traverse_directory(path)
+    local total_size = 0
+    local total_files = 0
+    local file_sizes = {}
+
+    for entry in lfs.dir(path) do
+        if entry ~= "." and entry ~= ".." then
+            local full_path = path..'\\'..entry
+            local attributes = lfs.attributes(full_path)
+
+            if attributes and attributes.mode == "file" then
+                local size = get_filesize(full_path)
+
+                if size then
+                    print(full_path, size, "bytes")
+                    table.insert(file_sizes, size)
+                    total_size = total_size + size
+                    total_files = total_files + 1
+                else
+                    print(full_path, "File not found or inaccessible")
+                end
+            elseif attributes and attributes.mode == "directory" then
+                local subdir_total_size, subdir_total_files, subdir_file_sizes = traverse_directory(full_path)
+                total_size = total_size + subdir_total_size
+                total_files = total_files + subdir_total_files
+                while #subdir_file_sizes > 0 do
+                    table.insert(file_sizes, table.remove(subdir_file_sizes))
+                end
+            end
+        end
+    end
+
+    return total_size, total_files, file_sizes
+end
+
+-- Function to calculate evenly spaced percentiles
+function calculate_percentiles(data, num_percentiles)
+    local result = {}
+    table.sort(data)
+
+    for i = 1, num_percentiles do
+        local p = (i - 1) / (num_percentiles - 1) * 100
+        local index = math.ceil(#data * p / 100)
+        if index == 0 then index = 1 end
+        result[i] = data[index]
+    end
+
+    return result
+end
+
+-- Function to print percentiles table returned from calculate_percentiles
+function print_percentiles(percentiles)
+    for i, value in pairs(percentiles) do
+        local p = (i - 1) / (#percentiles - 1) * 100
+        if p == 50 then
+            print(p .. "th percentile (median):", value, "bytes")
+        else
+            print(p .. "th percentile:", value, "bytes")
+        end
+    end
+end
+
+-- Function to calculate mode
+function calculate_mode(data)
+    local freq_map = {}
+    local max_freq = 0
+    local modes = {}
+
+    for _, value in ipairs(data) do
+        freq_map[value] = (freq_map[value] or 0) + 1
+        if freq_map[value] > max_freq then
+            max_freq = freq_map[value]
+        end
+    end
+
+    if max_freq == 1 then
+        return modes, max_freq -- no mode
+    end
+
+    for value, freq in pairs(freq_map) do
+        if freq == max_freq then
+            table.insert(modes, value)
+        end
+    end
+
+    table.sort(modes)
+    return modes, max_freq
+end
+
+-- Function to print mode results
+function print_mode_results(modes, max_freq)
+    if #modes == 0 then
+        print("No mode found.")
+    elseif #modes == 1 then
+        print("Mode:", modes[1], "bytes")
+    else
+        print("Multiple modes:")
+        for i, mode in ipairs(modes) do
+            print("Mode " .. i .. ":", mode, "bytes")
+        end
+    end
+    print("Frequency:", max_freq)
+end
+
+-- Function to calculate standard deviation
+function calculate_standard_deviation(data)
+    local n = #data
+    local sum = 0
+    local sum_of_squared_deviations = 0
+
+    if n < 1 then
+        return 0 -- Standard deviation is undefined for small sample sizes
+    end
+
+    -- Calculate mean
+    for _, value in ipairs(data) do
+        sum = sum + value
+    end
+    local mean = sum / n
+
+    -- Calculate sum of squared deviations
+    for _, value in ipairs(data) do
+        local deviation = value - mean
+        sum_of_squared_deviations = sum_of_squared_deviations + deviation^2
+    end
+
+    -- Calculate standard deviation
+    local variance = sum_of_squared_deviations / (n - 1)
+    local standard_deviation = math.sqrt(variance)
+
+    return standard_deviation
+end
+
+-- Function to calculate a histogram
+function calculate_histogram(data, num_bins)
+    local histogram = {}
+    local min_value = math.min(unpack(data))
+    local max_value = math.max(unpack(data))
+    local bin_width = (max_value - min_value) / num_bins
+
+    for i = 1, num_bins do
+        local bin_start = min_value + (i - 1) * bin_width
+        local bin_end = bin_start + bin_width
+        histogram[i] = {bin_start, bin_end, 0}
+    end
+
+    for _, value in ipairs(data) do
+        local bin_index = math.floor((value - min_value) / bin_width) + 1
+        if bin_index <= num_bins then
+            histogram[bin_index][3] = histogram[bin_index][3] + 1
+        else
+            -- the largest file always calculates to an nth + 1 bin
+            histogram[num_bins][3] = histogram[num_bins][3] + 1
+        end
+    end
+
+    return histogram
+end
+
+-- Function to print histogram results
+function print_histogram(histogram)
+    for i, bin in ipairs(histogram) do
+        local bin_start, bin_end, count = unpack(bin)
+        print(string.format("%.2f - %.2f:", bin_start, bin_end), count, "files")
+    end
+end
+
+-- Function to print histogram results with logarithmic scaling and aligned graphical representation
+function print_histogram_graphical(histogram, graph_width)
+    local max_count = 0
+
+    -- Find the maximum count to determine the scale
+    for _, bin in ipairs(histogram) do
+        local count = bin[3]
+        if count > max_count then
+            max_count = count
+        end
+    end
+
+    local max_log_scaled = math.log(max_count + 1) -- Add 1 to avoid log(0)
+
+    -- Print the histogram with graphical representation and aligned text data
+    for _, bin in ipairs(histogram) do
+        local bin_start, bin_end, count = unpack(bin)
+        local log_scaled_count = math.log(count + 1) -- Add 1 to avoid log(0)
+        local scaled_width = math.floor((log_scaled_count / max_log_scaled) * graph_width) -- Adjust the width as needed
+
+        local bar = string.rep("#", scaled_width)
+        local empty_spaces = string.rep(" ", graph_width - scaled_width) -- Add empty spaces for alignment
+        print(string.format("[%s%s] %.2f - %.2f: %d files", bar, empty_spaces, bin_start, bin_end, count))
+    end
+end
+
+local root_directory = "." -- bodge to work in-place
+local total_size, total_files, total_file_sizes = traverse_directory(root_directory)
+
+if total_files > 0 then
+    print("")
+    print(total_files, "files found.")
+    local average_size = total_size / total_files
+    print("Average (mean) file size:", average_size, "bytes")
+    local standard_deviation = calculate_standard_deviation(total_file_sizes)
+    print("Standard deviation:", standard_deviation)
+    local mode_results, max_freq = calculate_mode(total_file_sizes)
+    print_mode_results(mode_results, max_freq)
+    local bin_size = math.ceil(math.sqrt(total_files)) -- Square Root Rule
+    local histogram_results = calculate_histogram(total_file_sizes, bin_size)
+    print_histogram_graphical(histogram_results, 40)
+    local percentiles = calculate_percentiles(total_file_sizes, 11)
+    print_percentiles(percentiles)
+else
+    print("No files found.")
+end