marckohlbrugge · September 3, 2024 10:44
diff --git a/x_analysis.rb b/x_analysis.rb
 require 'http'
 require 'json'
 require 'terminal-table'


 users = [
  { username: "marckohlbrugge" }
 ]

 # Fetch data for each user
 users.each do |user|
  username = user[:username]
  data = HTTP.get("https://api.fxtwitter.com/#{username}").parse
  
  followers = data.dig('user', 'followers')
  tweets = data.dig('user', 'tweets')
  
  followers_per_tweet = (followers.to_f / tweets).round(2)
  
  user.merge!(
    followers:,
    tweets:,
    followers_per_tweet:
  )
 end

 # Sort by follower count (highest first)
 sorted_users = users.sort_by { |user| -user[:followers] }

 table = Terminal::Table.new do |t|
  t.headings = ['Username', 'Followers', 'Tweets', 'Followers per tweet']
  sorted_users.each do |user|
    t << [
      user[:username],
      user[:followers],
      user[:tweets],
      user[:followers_per_tweet]
    ]
  end
 end

 puts table

 # Calculate correlation between tweets and followers
 tweets = sorted_users.map { |user| user[:tweets] }
 followers = sorted_users.map { |user| user[:followers] }

 sum_tweets = tweets.sum
 sum_followers = followers.sum
 sum_tweets_squared = tweets.map { |t| t**2 }.sum
 sum_followers_squared = followers.map { |f| f**2 }.sum
 sum_tweets_followers = tweets.zip(followers).map { |t, f| t * f }.sum
 n = tweets.length

 numerator = (n * sum_tweets_followers) - (sum_tweets * sum_followers)
 denominator = Math.sqrt((n * sum_tweets_squared - sum_tweets**2) * (n * sum_followers_squared - sum_followers**2))

 correlation = numerator / denominator

 puts "\nCorrelation between tweets and followers: #{correlation.round(4)}"
	require 'http'
	require 'json'
	require 'terminal-table'


	users = [
	{ username: "marckohlbrugge" }
	]

	# Fetch data for each user
	users.each do \|user\|
	username = user[:username]
	data = HTTP.get("https://api.fxtwitter.com/#{username}").parse

	followers = data.dig('user', 'followers')
	tweets = data.dig('user', 'tweets')

	followers_per_tweet = (followers.to_f / tweets).round(2)

	user.merge!(
	followers:,
	tweets:,
	followers_per_tweet:
	)
	end

	# Sort by follower count (highest first)
	sorted_users = users.sort_by { \|user\| -user[:followers] }

	table = Terminal::Table.new do \|t\|
	t.headings = ['Username', 'Followers', 'Tweets', 'Followers per tweet']
	sorted_users.each do \|user\|
	t << [
	user[:username],
	user[:followers],
	user[:tweets],
	user[:followers_per_tweet]
	]
	end
	end

	puts table

	# Calculate correlation between tweets and followers
	tweets = sorted_users.map { \|user\| user[:tweets] }
	followers = sorted_users.map { \|user\| user[:followers] }

	sum_tweets = tweets.sum
	sum_followers = followers.sum
	sum_tweets_squared = tweets.map { \|t\| t**2 }.sum
	sum_followers_squared = followers.map { \|f\| f**2 }.sum
	sum_tweets_followers = tweets.zip(followers).map { \|t, f\| t * f }.sum
	n = tweets.length

	numerator = (n * sum_tweets_followers) - (sum_tweets * sum_followers)
	denominator = Math.sqrt((n * sum_tweets_squared - sum_tweets*2) (n * sum_followers_squared - sum_followers**2))

	correlation = numerator / denominator

	puts "\nCorrelation between tweets and followers: #{correlation.round(4)}"