# Loading the required libraries

import pandas as pd

import matplotlib.pyplot as plt

import numpy as np

import os

import powerlaw

# Function to create histograms

def histplot(data, binsize, ylab, xlab, color, title):

plt.title(title)

# Set the working directory

wd = os.getcwd() + '\\received\\'

# Reading in CSVs with the data for the histograms

russian_all = pd.read_csv(wd + "russian_users_received_all.csv", encoding = "ISO-8859-1", engine='python')

chinese_all = pd.read_csv(wd + "chinese_users_received_all.csv", encoding = "ISO-8859-1", engine='python')

american_all = pd.read_csv(wd + "unitedstates_users_received_all.csv", encoding = "ISO-8859-1", engine = 'python')

indian_all = pd.read_csv(wd + "indian_users_received_all.csv", encoding = "ISO-8859-1", engine = 'python')

russian_6_star = pd.read_csv(wd + "russian_stars_received_6_months.csv", encoding = "ISO-8859-1", engine='python')

chinese_6_star = pd.read_csv(wd + "chinese_stars_received_6_months.csv", encoding = "ISO-8859-1", engine='python')

american_6_star = pd.read_csv(wd + "unitedstates_stars_received_6_months.csv", encoding = "ISO-8859-1", engine = 'python')

indian_6_star = pd.read_csv(wd + "indian_stars_received_6_months.csv", encoding = "ISO-8859-1", engine = 'python')

russian_6_fork = pd.read_csv(wd + "russian_forks_received_6_months.csv", encoding = "ISO-8859-1", engine='python')

chinese_6_fork = pd.read_csv(wd + "chinese_forks_received_6_months.csv", encoding = "ISO-8859-1", engine='python')

american_6_fork = pd.read_csv(wd + "unitedstates_forks_received_6_months.csv", encoding = "ISO-8859-1", engine = 'python')

indian_6_fork = pd.read_csv(wd + "indian_forks_received_6_months.csv", encoding = "ISO-8859-1", engine = 'python')

# Putting the data into list form and popping the zeros off

russian_followers_all = russian_all['follower_count'].tolist()

chinese_followers_all = chinese_all['follower_count'].tolist()

american_followers_all = american_all['follower_count'].tolist()

indian_followers_all = indian_all['follower_count'].tolist()

russian_followers_all = [i for i in russian_followers_all if i != 0]

chinese_followers_all = [i for i in chinese_followers_all if i != 0]

american_followers_all = [i for i in american_followers_all if i != 0]

indian_followers_all = [i for i in indian_followers_all if i != 0]

russian_watchers_all = russian_all['watcher_count'].tolist()

chinese_watchers_all = chinese_all['watcher_count'].tolist()

american_watchers_all = american_all['watcher_count'].tolist()

indian_watchers_all = indian_all['watcher_count'].tolist()

russian_watchers_all = [i for i in russian_watchers_all if i != 0]

chinese_watchers_all = [i for i in chinese_watchers_all if i != 0]

american_watchers_all = [i for i in american_watchers_all if i != 0]

indian_watchers_all = [i for i in indian_watchers_all if i != 0]

russian_forkers_all = russian_all['fork_count'].tolist()

chinese_forkers_all = chinese_all['fork_count'].tolist()

american_forkers_all = american_all['fork_count'].tolist()

indian_forkers_all = indian_all['fork_count'].tolist()

russian_forkers_all = [i for i in russian_forkers_all if i != 0]

chinese_forkers_all = [i for i in chinese_forkers_all if i != 0]

american_forkers_all = [i for i in american_forkers_all if i != 0]

indian_forkers_all = [i for i in indian_forkers_all if i != 0]

chinese_6_star = chinese_6_star['star_count'].tolist()

american_6_star = american_6_star['star_count'].tolist()

indian_6_star = indian_6_star['star_count'].tolist()

russian_6_star = russian_6_star['star_count'].tolist()

chinese_6_fork = chinese_6_fork['fork_count'].tolist()

american_6_fork = american_6_fork['fork_count'].tolist()

indian_6_fork = indian_6_fork['fork_count'].tolist()

russian_6_fork = russian_6_fork['fork_count'].tolist()

# Deriving the bin size from the largest value in the set

binsize = int(np.max(russian_followers_all))

# Plotting the first line

histplot(russian_followers_all, binsize, 'Users', 'Follower count', 'black', '')

# Repeating the process for the rest of the data

binsize = int(np.max(chinese_followers_all))

histplot(chinese_followers_all, binsize, 'Users', 'Follower count', 'red', '')

binsize = int(np.max(american_followers_all))

histplot(american_followers_all, binsize, 'Users', 'Follower count', 'blue', '')

binsize = int(np.max(indian_followers_all))

histplot(indian_followers_all, binsize, 'Users', 'Follower count', 'green', 'User All Follows Received by Count, LogLog Scale Plot')

plt.savefig('logscale_all_follow_received.png')

plt.close()

binsize = int(np.max(russian_watchers_all))

histplot(russian_watchers_all, binsize, 'Users', 'Star count', 'black', '')

binsize = int(np.max(chinese_watchers_all))

histplot(chinese_watchers_all, binsize, 'Users', 'Star count', 'red', '')

binsize = int(np.max(american_watchers_all))

histplot(american_watchers_all, binsize, 'Users', 'Star count', 'blue', '')

binsize = int(np.max(indian_watchers_all))

histplot(indian_watchers_all, binsize, 'Users', 'Star count', 'green', 'User All Stars Received by Count, LogLog Scale Plot')

plt.savefig('logscale_all_stars_received.png')

plt.close()

binsize = int(np.max(russian_forkers_all))

histplot(russian_forkers_all, binsize, 'Users', 'Fork count', 'black', '')

binsize = int(np.max(chinese_forkers_all))

histplot(chinese_forkers_all, binsize, 'Users', 'Fork count', 'red', '')

binsize = int(np.max(american_forkers_all))

histplot(american_forkers_all, binsize, 'Users', 'Fork count', 'blue', '')

binsize = int(np.max(indian_forkers_all))

histplot(indian_forkers_all, binsize, 'Users', 'Fork count', 'green', 'User All Forks Received by Count, LogLog Scale Plot')

plt.savefig('logscale_all_forks_received.png')

plt.close()

multiplier = 7

binsize = int(np.max(russian_6_star)/5)

histplot(russian_6_star, binsize, 'Users', 'Star count', 'black', '')

binsize = int(np.max(chinese_6_star)/multiplier)

histplot(chinese_6_star, binsize, 'Users', 'Star count', 'red', '')

binsize = int(np.max(american_6_star)/multiplier)

histplot(american_6_star, binsize, 'Users', 'Star count', 'blue', '')

binsize = int(np.max(indian_watchers_all)/multiplier)

histplot(indian_6_star, binsize, 'Users', 'Star count', 'green', 'User Jan-Jun 2019 Stars Received by Count, LogLog Scale Plot')

plt.savefig('logscale_jan-jun_stars_received.png')

plt.close()

multiplier = 6

binsize = int(np.max(russian_6_fork)/multiplier)

histplot(russian_6_fork, binsize, 'Users', 'Fork count', 'black', '')

binsize = int(np.max(chinese_6_fork)/multiplier)

histplot(chinese_6_fork, binsize, 'Users', 'Fork count', 'red', '')

binsize = int(np.max(american_forkers_all)/multiplier)

histplot(american_6_fork, binsize, 'Users', 'Fork count', 'blue', '')

binsize = int(np.max(indian_6_fork)/multiplier)

histplot(indian_6_fork, binsize, 'Users', 'Fork count', 'green', 'User Jan-Jun 2019 Forks Received by Count, LogLog Scale Plot')

plt.savefig('logscale_jan-jun_forks_received.png')

plt.close()

powerlaw.plot_pdf(russian_followers_all, color='black')

powerlaw.plot_pdf(chinese_followers_all, color='red')

powerlaw.plot_pdf(american_followers_all, color='blue')

powerlaw.plot_pdf(indian_followers_all, color='green')

plt.ylabel('Users')

plt.xlabel('Follow Count')

plt.title('All Follows Received by Count, PDF')

plt.savefig('pdf_all_follows_received.png')

plt.close()

powerlaw.plot_ccdf(russian_followers_all, color='black')

powerlaw.plot_ccdf(chinese_followers_all, color='red')

powerlaw.plot_ccdf(american_followers_all, color='blue')

powerlaw.plot_ccdf(indian_followers_all, color='green')

plt.ylabel('Users')

plt.xlabel('Follow Count')

plt.title('All Follows Received by Count, CCDF')

plt.savefig('ccdf_all_follows_received.png')

plt.close()

powerlaw.plot_pdf(russian_watchers_all, color='black')

powerlaw.plot_pdf(chinese_watchers_all, color='red')

powerlaw.plot_pdf(american_watchers_all, color='blue')

powerlaw.plot_pdf(indian_watchers_all, color='green')

plt.ylabel('Users')

plt.xlabel('Star Count')

plt.title('All Stars Received by Count, PDF')

plt.savefig('pdf_all_stars_received.png')

plt.close()

powerlaw.plot_ccdf(russian_watchers_all, color='black')

powerlaw.plot_ccdf(chinese_watchers_all, color='red')

powerlaw.plot_ccdf(american_watchers_all, color='blue')

powerlaw.plot_ccdf(indian_watchers_all, color='green')

plt.ylabel('Users')

plt.xlabel('Star Count')

plt.title('All Stars Received by Count, CCDF')

plt.savefig('ccdf_all_stars_received.png')

plt.close()

powerlaw.plot_pdf(russian_forkers_all, color='black')

powerlaw.plot_pdf(chinese_forkers_all, color='red')

powerlaw.plot_pdf(american_forkers_all, color='blue')

powerlaw.plot_pdf(indian_forkers_all, color='green')

plt.ylabel('Users')

plt.xlabel('Fork Count')

plt.title('All Forks Received by Count, PDF')

plt.savefig('pdf_all_forks_received.png')

plt.close()

powerlaw.plot_ccdf(russian_forkers_all, color='black')

powerlaw.plot_ccdf(chinese_forkers_all, color='red')

powerlaw.plot_ccdf(american_forkers_all, color='blue')

powerlaw.plot_ccdf(indian_forkers_all, color='green')

plt.ylabel('Users')

plt.xlabel('Fork Count')

plt.title('All Forks Received by Count, CCDF')

plt.savefig('ccdf_all_forks_received.png')

plt.close()

powerlaw.plot_pdf(russian_6_star, color='black')

powerlaw.plot_pdf(chinese_6_star, color='red')

powerlaw.plot_pdf(american_6_star, color='blue')

powerlaw.plot_pdf(indian_6_star, color='green')

plt.ylabel('Users')

plt.xlabel('Star Count')

plt.title('Jan-Jun 2019 Stars Received by Count, PDF')

plt.savefig('pdf_jan-jun_stars_received.png')

plt.close()

powerlaw.plot_ccdf(russian_6_star, color='black')

powerlaw.plot_ccdf(chinese_6_star, color='red')

powerlaw.plot_ccdf(american_6_star, color='blue')

powerlaw.plot_ccdf(indian_6_star, color='green')

plt.ylabel('Users')

plt.xlabel('Star Count')

plt.title('Jan-Jun 2019 Stars Received by Count, CCDF')

plt.savefig('ccdf_jan-jun_stars_received.png')

plt.close()

powerlaw.plot_pdf(russian_6_fork, color='black')

powerlaw.plot_pdf(chinese_6_fork, color='red')

powerlaw.plot_pdf(american_6_fork, color='blue')

powerlaw.plot_pdf(indian_6_fork, color='green')

plt.ylabel('Users')

plt.xlabel('Fork Count')

plt.title('Jan-Jun 2019 Forks Received by Count, PDF')

plt.savefig('pdf_Jan-Jun_forks_received.png')

plt.close()

powerlaw.plot_ccdf(russian_6_fork, color='black')

powerlaw.plot_ccdf(chinese_6_fork, color='red')

powerlaw.plot_ccdf(american_6_fork, color='blue')

powerlaw.plot_ccdf(indian_6_fork, color='green')

plt.ylabel('Users')

plt.xlabel('Fork Count')

plt.title('Jan-Jun 2019 Forks Received by Count, CCDF')

plt.savefig('ccdf_jan-jun_forks_received.png')

plt.close()