main.py

print('loading please wait')
import pandas as pd
import requests as rq
from bs4 import BeautifulSoup
import csv
import json


print('type the skanderbeg save code')
save = input()
print('do you want to compare this save with an older one?[y/n]')
resp1 = input()
save2 = ''
if resp1 == 'y':
    print('type the older skanderbeg Save code')
    save2 = input()

print('do you want to show only players?[y/n]')
ia = input()
try:
    with open('folder.txt') as f:
        folder = f.read()
        f.close()
except:
    f = open('folder.txt', 'x')
    folder = ''
if folder == '':
    print('please indicate the location of the folder where you want to store your graphs')
    folder = input()
    with open('folder.txt', 'wt') as z:
        z.write(str(folder))

if ia == 'y' or ia == 'yes':
    ia = '&playersOnly=yes'
else:
    ia = ''

url = 'https://skanderbeg.pm/api.php?key=963df40b3b93a81013da34dfdd815583&scope=getCountryData&save=' + save + '&tag=IRE&value=inc_no_subs;total_development;buildings_value;provinces;total_army;qualityScore;total_mana_spent_on_deving;total_mana_on_teching_up;spent_total;fdp;total_mana_spent_on_deving;battleCasualties;max_manpower;continents;dev_clicks;total_navy;total_army;hex;player;countryName&' + ia + '&format=json'
response = rq.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
with open('data.json', 'w', encoding='utf-8') as f_out:
    f_out.write(soup.prettify())

with open('data.json') as json_file:
    data = json.load(json_file)

df = pd.read_json('data.json')
corpus = df.iloc[0][1]
csv_columns = ['tag', 'fdp', 'battleCasualties', 'max_manpower', 'countryName', 'player', 'total_development',
               'spent_total', 'total_mana_on_teching_up', 'provinces', 'qualityScore', 'inc_no_subs', 'total_army',
               'total_mana_spent_on_deving', 'buildings_value', 'continents', 'total_navy', 'dev_clicks',
               'deving_stats','hex']

i = 0
dict = []
tags = []
for tag in data:
    tags.append(tag)
while i < len(df.columns):
    a = df.iloc[0][i]
    a.update({'tag': tags[i]})
    dict.append(a)
    i = i + 1


csv_file = "found.csv"
try:
    with open(csv_file, 'w', newline='') as csvfile:
        writer = csv.DictWriter(csvfile, fieldnames=csv_columns)
        writer.writeheader()
        for data in dict:
            for key, value in data.items():
                if key == 'provinces' and int(value) >= 1:
                    writer.writerow(data)
except IOError:
    print("I/O error")
if save2 != '':
    url = 'https://skanderbeg.pm/api.php?key=963df40b3b93a81013da34dfdd815583&scope=getCountryData&save=' + save2 + '&tag=IRE&value=inc_no_subs;total_development;buildings_value;provinces;total_army;qualityScore;total_mana_spent_on_deving;total_mana_on_teching_up;spent_total;fdp;total_mana_spent_on_deving;battleCasualties;max_manpower;continents;dev_clicks;total_navy;hex;total_army;player;countryName&' + ia + '&format=json'
    response = rq.get(url)
    soup = BeautifulSoup(response.text, 'html.parser')
    with open('data.json', 'w', encoding='utf-8') as f_out:
        f_out.write(soup.prettify())

    with open('data.json') as json_file:
        data = json.load(json_file)

    df = pd.read_json('data.json')
    corpus = df.iloc[0][1]
    csv_columns = ['tag', 'fdp', 'battleCasualties', 'max_manpower', 'countryName', 'player', 'total_development',
                   'spent_total', 'total_mana_on_teching_up', 'provinces', 'qualityScore', 'inc_no_subs', 'total_army',
                   'total_mana_spent_on_deving', 'buildings_value', 'continents', 'total_navy', 'dev_clicks',
                   'deving_stats','hex']

    i = 0
    dict = []
    tags = []
    for tag in data:
        tags.append(tag)
    while i < len(df.columns):
        a = df.iloc[0][i]
        a.update({'tag': tags[i]})
        dict.append(a)
        i = i + 1


    csv_file = "found2.csv"
    try:
        with open(csv_file, 'w', newline='') as csvfile:
            writer = csv.DictWriter(csvfile, fieldnames=csv_columns)
            writer.writeheader()
            for data in dict:
                for key, value in data.items():
                    if key == 'provinces' and int(value) >= 1:
                        writer.writerow(data)
    except IOError:
        print("I/O error")
with open('found.csv', 'r') as csvfile:
    lines = csvfile.readlines()
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

x = 'found.csv'
y = 'found2.csv'
df1 = pd.read_csv(x, encoding='latin1')
try:
    df2 = pd.read_csv(y, encoding='latin1')

except:
    y = 'found.csv'
    df2 = pd.read_csv(y, encoding='latin1')

def replace(df):
    a = df.columns
    list(a)
    h = []
    j = []
    for x in a:
        h.append(x)
        if x == '|':
            x = 'tag'
        y = x.replace('|', '')
        z = y.replace('_', '')
        j.append(z)
    df.rename(columns={x: y for x, y in zip(h, j)}, inplace=True)


replace(df1)
replace(df2)

df1['totalarmy'] = df1['totalarmy'].fillna(0)
df1['totalnavy'] = df1['totalnavy'].fillna(0)
df2['totalarmy'] = df2['totalarmy'].fillna(0)
df2['totalnavy'] = df2['totalnavy'].fillna(0)
df1['buildingsvalue'] = df1['buildingsvalue'].fillna(0)
df2['buildingsvalue'] = df2['buildingsvalue'].fillna(0)
lista1 = [df1, df2]
lista = [df1]
date = [1444, 1469, 1481, 1]
tags = df1['tag'].tolist()
players = df1['countryName'].tolist()
i = 0
for player in players:
    if type(player) == type(0.54):
        players[i] = tags[i]
    i += 1


def a_su_b(dfa, dfb, nomicolonne):
    dfx = pd.DataFrame()
    i = 0
    length = len(nomicolonne)
    while i < length:
        z = nomicolonne[i]
        x = [a / b for a, b in zip(dfa[z], dfb[z])]
        dfx[z] = x
        i += 1
    return dfx


def calcolatorespaziatrura(ncolonne):
    a = ((4 * ncolonne) + 45) / 2000
    return a


def calcolosize(ncolonne):
    size = ((1 / 5) * -ncolonne) + 14
    return size


def humanvalue(dict, I, tags):
    j = I
    a = []
    for i in tags:
        x = dict[i]
        try:
            s = x[I]
            y = round(s, 2)
            a.append(y)
        except:
            pass
    return (a)


def sumof(data):
    a = 0
    for row in data:
        a = a + row
    return a


def testosucolonne(columns, ncifre):
    return columns


def devonnprovince(data):
    x = [round(i / k, 1) for i, k in zip(data['realdevelopment'], data['provinces'])]
    return x


def func(pct, allvals):
    absolute = int(pct / 100. * np.sum(allvals))
    return "{:.1f}%\n{:d}".format(pct, absolute)


def sostituisci(df):
    dft = df.T
    dict = dft.to_dict()
    for i in list(df.index.values):
        a = df['tag']
        y = a[i]
        dict[y] = dict.pop(i)
    return dict


def human(df):
    Humanplayers = df.loc[(df['tag'] == 'TUR') | (df['tag'] == 'FRA') | (df['tag'] == 'MOS') | (df['tag'] == 'CAS') | (
            df['tag'] == 'ENG') | (df['tag'] == 'HAB') | (df['tag'] == 'QOM') | (df['tag'] == 'PER') | (
                                  df['tag'] == 'SWE') | (df['tag'] == 'BRA') | (df['tag'] == 'HOL') | (
                                  df['tag'] == 'SWI') | (df['tag'] == 'PAL')]
    return Humanplayers


def prova(listadf):
    global tags
    i = 0
    for df in listadf:
        dict = sostituisci(df)
        humandict = {item: dict.get(item) for item in tags}
        playerdev = humanvalue(humandict, 'totaldevelopment', tags)
        playerincome = humanvalue(humandict, 'incnosubs', tags)
        playerbuildingsvalue = humanvalue(humandict, 'buildingsvalue', tags)
        playerprovinces = humanvalue(humandict, 'provinces', tags)
        playerbattlecasualites = humanvalue(humandict, 'battleCasualties', tags)
        playertotalarmy = humanvalue(humandict, 'totalarmy', tags)
        playerqualityscore = humanvalue(humandict, 'qualityScore', tags)
        playermanadev = humanvalue(humandict, 'totalmanaspentondeving', tags)
        playermanatech = humanvalue(humandict, 'totalmanaontechingup', tags)
        playermoneyspent = humanvalue(humandict, 'spenttotal', tags)
        playermaxmanpower = humanvalue(humandict, 'maxmanpower', tags)
        playertotalnavy = humanvalue(humandict, 'totalnavy', tags)
        playerfdp = humanvalue(humandict, 'fdp', tags)
        playerclick = humanvalue(humandict, 'devclicks', tags)
        if i == 0:
            a = [playerdev]
            b = [playerincome]
            c = [playerbuildingsvalue]
            d = [playerprovinces]
            e = [playerbattlecasualites]
            f = [playertotalarmy]
            g = [playerqualityscore]
            h = [playermanadev]
            ix = [playermanatech]
            l = [playermoneyspent]
            n = [playermaxmanpower]
            m = [playertotalnavy]
            o = [playerfdp]
            p = [playerclick]
            i += 1

        else:
            i += 1
            a.append(playerdev)
            b.append(playerincome)
            c.append(playerbuildingsvalue)
            d.append(playerprovinces)
            e.append(playerbattlecasualites)
            f.append(playertotalarmy)
            g.append(playerqualityscore)
            h.append(playermanadev)
            ix.append(playermanatech)
            l.append(playermoneyspent)
            n.append(playermaxmanpower)
            m.append(playertotalnavy)
            o.append(playerfdp)
            p.append(playerclick)
    dfplayerdev = pd.DataFrame(a, columns=players)
    dfplayerincome = pd.DataFrame(b, columns=players)
    dfplayerbuildingsvalue = pd.DataFrame(c, columns=players)
    dfplayerprovinces = pd.DataFrame(d, columns=players)
    dfplayerbattlecasualites = pd.DataFrame(e, columns=players)
    dfplayertotalarmy = pd.DataFrame(f, columns=players)
    dfplayerqualityscore = pd.DataFrame(g, columns=players)
    dfplayermanadev = pd.DataFrame(h, columns=players)
    dfplayermanatech = pd.DataFrame(ix, columns=players)
    dfplayermoneyspent = pd.DataFrame(l, columns=players)
    dfplayermaxmanpower = pd.DataFrame(n, columns=players)
    dfplayertotalnavy = pd.DataFrame(m, columns=players)
    playerfdp = pd.DataFrame(o, columns=players)
    playerclick = pd.DataFrame(p, columns=players)

    tutto = [dfplayerdev, dfplayerincome, dfplayerbuildingsvalue, dfplayerprovinces, dfplayerbattlecasualites,
             dfplayertotalarmy, dfplayerqualityscore, dfplayermanadev, dfplayermanatech, dfplayermoneyspent,
             dfplayermaxmanpower, dfplayertotalnavy, playerfdp, playerclick]
    return tutto


ogni = prova(lista)
k = 0
# colori grafico

colori = ['black', 'grey', 'rosybrown', 'brown', 'darkred', 'red', 'tomato', 'coral', 'orangered', 'sienna', 'peru',
          'orange', 'goldenrod', 'gold', 'khaki', 'olive', 'yellow', 'lawngreen', 'green', 'lime', 'teal', 'cyan',
          'steelblue', 'navy', 'blue', 'blueviolet', 'indigo', 'violet', 'magenta', 'deeppink']

listaz = ogni[0].columns
colornazioni = {}
count = 0
hex=df1['hex']
for nation in listaz:

    colornazioni[nation] = hex[count]
    count = count + 1

az = np.linspace(0, 1, len(players))
massimo = len(lines) - 1
if massimo > 20:
    resp = ' but the optimal maximum is around 20'
else:
    resp = ''
print('how many nation do you want ot print? the max is ' + str(massimo) + resp)
y = input()
y = int(y)
f = 100 / y
alpha1 = 0.8
alphagrid=0.4
sz = calcolatorespaziatrura(y)
sizes = calcolosize(y)
for s in ogni:
    if k == 0:  # dev
        plt.figure(figsize=[19.2, 10.8])
        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data

        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
        plt.grid(axis='y',alpha=alphagrid)

        plt.xticks(rotation=-90)
        plt.ylabel('Development')
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        h = 0
        percentuali = []
        for ap in s.loc[len(s) - 1]:
            h += ((ap / somma) * 100)
            percentuali.append(h)
        balances = []
        q = f
        for l in percentuali:
            d = l - q
            balances.append(d)
            q += f
        j = max(balances)
        pvalue = (1 - ((j ** 2) / 2500)) * 100
        ax2 = ax1.twinx()
        ax2.spines['right'].set_position(('axes', 1.0))
        plt.ylim(0, 101)
        plt.plot(percentuali, marker='o', color='r')  # linea paretiana
        ax1.set_title('development' + '       Balancing%=' + str(round(pvalue)) + '%')
        plt.ylabel('% of dev on total')

        j = 0
        for i, v in enumerate(percentuali):  # testo su linea
            ax2.text(i - 0.10, v + 1, str(round(v)) + '%', color='black', fontweight='bold', size=sizes)
        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
            ax1.text(i - len(str(round(v, 1))) * sz, v + 0.5, str(round(v, 1)), color='black', fontweight='bold',
                     size=sizes)
        plt.savefig(folder + '/dev')
        plt.close()
    if k == 1:  # income
        plt.figure(figsize=[19.2, 10.8])
        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
        plt.xticks(rotation=-90)

        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
        plt.grid(axis='y',alpha=alphagrid)

        plt.xticks(rotation=-90)

        plt.ylabel('income')
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        h = 0
        percentuali = []
        for ap in s.loc[len(s) - 1]:
            h += ((ap / somma) * 100)
            percentuali.append(h)
        balances = []
        q = f
        for l in percentuali:
            d = l - q
            balances.append(d)
            q += f
        j = max(balances)
        pvalue = (1 - ((j ** 2) / 2500)) * 100
        ax2 = ax1.twinx()
        ax2.spines['right'].set_position(('axes', 1.0))
        plt.ylim(0, 101)
        plt.plot(percentuali, marker='o', color='r')  # linea paretiana
        ax1.set_title('income' + '       Balancing%=' + str(round(pvalue)) + '%')
        plt.ylabel('% of income on total')
        j = 0
        for i, v in enumerate(percentuali):  # testo su linea
            ax2.text(i - 0.10, v + 1, str(round(v)) + '%', color='black', fontweight='bold', size=sizes)
        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
            ax1.text(i - len(str(round(v))) * sz, v + 0.5, str(round(v)), color='black', fontweight='bold', size=sizes)
        plt.savefig(folder + '/income')
        plt.close()
    if k == 2:  # valore immobili
        plt.figure(figsize=[19.2, 10.8])
        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)
        hj =s.iloc[:,range(10,y)]
        s = s.iloc[:, range(0,10)]

        others=0
        counting=0
        coloriar=[]
        hh=hj.values.tolist()
        for value in hh[0]:
            others=others+value
            counting=counting+1
        s['Others']=others

        for nomej in s.columns:
            try:
               coloriar.append(colornazioni[nomej])
            except:
                coloriar.append('gray')



        ax2 = s.loc[len(s) - 1].plot.pie(autopct=lambda pct: func(pct, s.loc[len(s) - 1]), startangle=90, radius=1.3,colors=coloriar)
        plt.grid(axis='y',alpha=alphagrid)

        ax2.text(-0.3, 1.5, 'Buildings Value', color='black', fontweight='bold', size=sizes)
        plt.savefig(folder + '/Buildings Value')
        plt.close()
    if k == 3:  # province
        plt.figure(figsize=[19.2, 10.8])
        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
        plt.grid(axis='y',alpha=alphagrid)
        plt.xticks(rotation=-90)

        plt.ylabel('provinces')
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        h = 0
        percentuali = []
        for ap in s.loc[len(s) - 1]:
            h += ((ap / somma) * 100)
            percentuali.append(h)
        ax2 = ax1.twinx()
        ax2.spines['right'].set_position(('axes', 1.0))
        plt.ylim(0, 101)
        plt.plot(percentuali, marker='o', color='g')  # linea paretiana
        ax1.set_title('provinces')
        plt.ylabel('% of provinces on total')
        j = 0
        for i, v in enumerate(percentuali):  # testo su linea
            ax2.text(i - 0.10, v + 1, str(round(v)) + '%', color='black', fontweight='bold', size=sizes)
        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre.
            ax1.text(i - len(str(round(v, 1))) * sz, v + 0.5, str(round(v, 1)), color='black', fontweight='bold',
                     size=sizes)
        plt.savefig(folder + '/provinces')
        plt.close()
    if k == 4:
        plt.figure(figsize=[19.2, 10.8])
        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
        plt.grid(axis='y',alpha=alphagrid)

        plt.xticks(rotation=-90)

        plt.ylabel('Battle casualities')
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        h = 0
        percentuali = []

        for ap in s.loc[len(s) - 1]:
            try:
                h += ((ap / somma) * 100)
            except:
                pass
            percentuali.append(h)
        ax2 = ax1.twinx()
        ax2.spines['right'].set_position(('axes', 1.0))
        plt.ylim(0, 101)
        plt.plot(percentuali, marker='o', color='g')  # linea paretiana
        ax1.set_title('Battle casualities')
        plt.ylabel('% battle casualities on total')
        j = 0
        for i, v in enumerate(percentuali):  # testo su linea
            ax2.text(i - 0.10, v + 1, str(round(v)) + '%', color='black', fontweight='bold', size=sizes)
        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
            if v >= 100000:
                ax1.text(i - len(str(round(v / 1000000, 1)) + 'M') * sz, v + 0.5, str(round(v / 1000000, 1)) + 'M',
                         color='black', fontweight='bold', size=sizes)
            else:
                ax1.text(i - len(str(round(v / 1000, 1)) + 'k') * sz, v + 0.5, str(round(v / 1000, 1)) + 'k',
                         color='black', fontweight='bold', size=sizes)

        plt.savefig(folder + '/Battle casualities')
        plt.close()
    if k == 5:
        plt.figure(figsize=[19.2, 10.8])

        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
        plt.grid(axis='y',alpha=alphagrid)

        plt.xticks(rotation=-90)

        plt.ylabel('Total armies')
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        h = 0
        percentuali = []
        for ap in s.loc[len(s) - 1]:
            h += ((ap / somma) * 100)
            percentuali.append(h)
        balances = []
        q = f
        for l in percentuali:
            d = l - q
            balances.append(d)
            q += f
        j = max(balances)
        pvalue = (1 - ((j ** 2) / 2500)) * 100
        ax2 = ax1.twinx()
        ax2.spines['right'].set_position(('axes', 1.0))
        plt.ylim(0, 101)
        plt.plot(percentuali, marker='o', color='y')  # linea paretiana
        ax1.set_title('armies' + '       Balancing%=' + str(round(pvalue)) + '%')
        plt.ylabel('% Armies on total')
        j = 0
        for i, v in enumerate(percentuali):  # testo su linea
            ax2.text(i - 0.10, v + 1, str(round(v)) + '%', color='black', fontweight='bold', size=sizes)
        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
            ax1.text(i - len(str(int(v))) * sz, v + 0.5, str(int(v)), color='black', fontweight='bold', size=sizes)
        plt.savefig(folder + '/armies')
        plt.close()
    if k == 7:
        plt.figure(figsize=[19.2, 10.8])

        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
        plt.grid(axis='y',alpha=alphagrid)

        plt.xticks(rotation=-90)

        plt.ylabel('Mana spent on devving')
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        h = 0
        percentuali = []
        for ap in s.loc[len(s) - 1]:
            try:
                h += ((ap / somma) * 100)
            except:
                pass
            percentuali.append(h)
        ax1.set_title('Mana spent on devving')
        j = 0

        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
            ax1.text(i - len(str(round(v / 1000, 1)) + 'k') * sz, v + 0.5, str(round(v / 1000, 1)) + 'k', color='black',
                     fontweight='bold', size=sizes)
        plt.savefig(folder + '/Mana spent on devving')
        plt.close()
    if k == 8:
        plt.figure(figsize=[19.2, 10.8])

        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt # bar plt
        plt.grid(axis='y',alpha=alphagrid)

        plt.xticks(rotation=-90)

        plt.ylabel('Mana spent on teching up')
        a = s.loc[len(s) - 1]
        plt.ylim(a[-1] - 500, a[0] + 500)
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        h = 0
        percentuali = []
        for ap in s.loc[len(s) - 1]:
            try:
                h += ((ap / somma) * 100)
            except:
                pass

            percentuali.append(h)
        ax1.set_title('Mana spent on teching up')
        j = 0

        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
            ax1.text(i - len(str(round(v / 1000, 1)) + 'k') * sz, v + 0.5, str(round(v / 1000, 1)) + 'k', color='black',
                     fontweight='bold', size=sizes)
        plt.savefig(folder + '/Mana spent on teching up')
        plt.close()
    if k == 9:
        plt.figure(figsize=[19.2, 10.8])

        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
        plt.grid(axis='y',alpha=alphagrid)

        plt.xticks(rotation=-90)

        plt.ylabel('money spent')
        plt.title('money spent')
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
            if v >= 100000:
                ax1.text(i - len(str(round(v / 1000000, 1)) + 'M') * sz, v + 0.5, str(round(v / 1000000, 1)) + 'M',
                         color='black', fontweight='bold', size=sizes)
            else:
                ax1.text(i - len(str(round(v / 1000, 1)) + 'k') * sz, v + 0.5, str(round(v / 1000, 1)) + 'k',
                         color='black', fontweight='bold', size=sizes)
        plt.savefig(folder + '/moneyspent')
        plt.close()
    if k == 10:
        plt.figure(figsize=[19.2, 10.8])

        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
        plt.grid(axis='y',alpha=alphagrid)

        plt.xticks(rotation=-90)

        plt.ylabel('max mp')
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        h = 0
        percentuali = []
        for ap in s.loc[len(s) - 1]:
            h += ((ap / somma) * 100)
            percentuali.append(h)

        balances = []
        q = f
        for l in percentuali:
            d = l - q
            balances.append(d)
            q += f
        j = max(balances)
        pvalue = (1 - ((j ** 2) / 2500)) * 100
        ax2 = ax1.twinx()
        ax2.spines['right'].set_position(('axes', 1.0))
        plt.ylim(0, 101)
        plt.plot(percentuali, marker='o', color='g')  # linea paretiana
        ax1.set_title('max manpower' + '       Balancing%=' + str(round(pvalue)) + '%')
        plt.ylabel('% max mp on total')
        j = 0
        for i, v in enumerate(percentuali):  # testo su linea
            ax2.text(i - 0.10, v + 1, str(round(v)) + '%', color='black', fontweight='bold', size=12)
        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
            if v >= 100000:
                ax1.text(i - len(str(round(v / 1000000, 1)) + 'M') * sz, v + 0.5, str(round(v / 1000000, 1)) + 'M',
                         color='black', fontweight='bold', size=sizes)
            else:
                ax1.text(i - len(str(round(v / 1000, 1)) + 'k') * sz, v + 0.5, str(round(v / 1000, 1)) + 'k',
                         color='black', fontweight='bold', size=sizes)
        plt.savefig(folder + '/max manpower')
        plt.close()
    if k == 11:
        plt.figure(figsize=[19.2, 10.8])

        s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
        s = s.iloc[:, range(0, y)]
        coloriar = []
        for nomej in s.columns:
            coloriar.append(colornazioni[nomej])

        ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
        plt.grid(axis='y',alpha=alphagrid)

        plt.xticks(rotation=-90)

        plt.ylabel('total navy')
        somma = 0
        for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
            somma = somma + a
        h = 0
        percentuali = []
        for ap in s.loc[len(s) - 1]:
            h += ((ap / somma) * 100)
            percentuali.append(h)
        ax2 = ax1.twinx()
        ax2.spines['right'].set_position(('axes', 1.0))
        plt.ylim(0, 101)
        plt.plot(percentuali, marker='o', color='g')  # linea paretiana
        ax1.set_title('total navy')
        plt.ylabel('% total navy on total')
        j = 0
        for i, v in enumerate(percentuali):  # testo su linea
            ax2.text(i - 0.10, v + 1, str(round(v)) + '%', color='black', fontweight='bold', size=sizes)
        for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
            ax1.text(i - len(str(int(v))) * sz, v + 0.5, str(int(v)), color='black', fontweight='bold', size=sizes)
        plt.savefig(folder + '/total navy')
        plt.close()
    if k == 13:
        try:
            plt.figure(figsize=[19.2, 10.8])

            s = s.sort_values(by=(len(s) - 1), axis=1, ascending=False)  # sort data
            s = s.iloc[:, range(0, y)]
            coloriar = []
            for nomej in s.columns:
                coloriar.append(colornazioni[nomej])

            ax1 = s.loc[len(s) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
            plt.grid(axis='y', alpha=alphagrid)

            plt.xticks(rotation=-90)

            plt.ylabel('dev clicks')
            somma = 0
            for a in s.loc[len(s) - 1]:  # somma ultima riga matrice
                somma = somma + a
            h = 0
            percentuali = []
            for ap in s.loc[len(s) - 1]:
                h += ((ap / somma) * 100)
                percentuali.append(h)
            ax2 = ax1.twinx()
            ax2.spines['right'].set_position(('axes', 1.0))
            plt.ylim(0, 101)
            plt.plot(percentuali, marker='o', color='g')  # linea paretiana
            ax1.set_title('total dev clicks')
            plt.ylabel('% dev clicks on the total')
            j = 0
            for i, v in enumerate(percentuali):  # testo su linea
                ax2.text(i - 0.10, v + 1, str(round(v)) + '%', color='black', fontweight='bold', size=sizes)
            for i, v in enumerate(s.loc[len(s) - 1]):  # testo su barre
                ax1.text(i - len(str(int(v))) * sz, v + 0.5, str(int(v)), color='black', fontweight='bold', size=sizes)
            plt.savefig(folder + '/dev clicks')
            plt.close()
        except:
            pass
    k += 1


def boh(lista):
    a1 = []
    b1 = []
    c1 = []
    d1 = []
    for df in lista:
        i = 0
        tags1 = df['tag'].tolist()
        players1 = df['countryName'].tolist()
        for player in players1:
            if type(player) == type(0.54):
                players1[i] = tags1[i]
            i += 1
        a = pd.DataFrame([df['incnosubs'].tolist()], columns=players1)
        b = pd.DataFrame([df['provinces'].tolist()], columns=players1)
        c = pd.DataFrame([df['totaldevelopment'].tolist()], columns=players1)
        d = pd.DataFrame([df['maxmanpower'].tolist()], columns=players1)
        a1.append(a)
        b1.append(b)
        c1.append(c)
        d1.append(d)
    a2 = pd.concat(a1)
    b2 = pd.concat(b1)
    c2 = pd.concat(c1)
    d2 = pd.concat(d1)
    total = [a2, b2, c2, d2]
    return total


h = boh(lista1)

dev = ogni[0]
pro = ogni[3]
manpower = ogni[10]
income = ogni[1]
fdp = ogni[12]
plt.figure(figsize=[19.2, 10.8])
fdpdev = [a * b for a, b in zip(dev.loc[0], fdp.loc[0])]
dffdpdev = pd.DataFrame(np.array([fdpdev]), columns=players)
dffdpdev = dffdpdev.append(fdp, ignore_index=True)
dffdpdev = dffdpdev.sort_values(by=0, axis=1, ascending=False)
dffdpdev = dffdpdev.iloc[:, range(0, y)]

plt.figure(figsize=[19.2, 10.8])

avgdev = [a / b for a, b in zip(dev.loc[0], pro.loc[0])]
dfavgdev = pd.DataFrame(np.array([avgdev]), columns=players)
dfavgdev = dfavgdev.sort_values(by=(len(dfavgdev) - 1), axis=1, ascending=False)
dfavgdev = dfavgdev.iloc[:, range(0, y)]
coloriar = []
for nomej in dfavgdev.columns:
    coloriar.append(colornazioni[nomej])
ax1 = dfavgdev.loc[len(dfavgdev) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')  # bar plt
plt.grid(axis='y', alpha=alphagrid)

plt.xticks(rotation=-90)

for i, v in enumerate(dfavgdev.loc[len(dfavgdev) - 1]):  # testo su barre
    ax1.text(i - len(str(round(v, 1))) * sz, v + 0.005, str(round(v, 1)), color='black', fontweight='bold', size=sizes)
plt.title('avg dev')
plt.savefig(folder + '/avg dev')
plt.close()
plt.figure(figsize=[19.2, 10.8])

avgmanpower = [(a - 10000) / b for a, b in zip(manpower.loc[0], pro.loc[0])]
dfavgmanpower = pd.DataFrame(np.array([avgmanpower]), columns=players)
dfavgmanpower = dfavgmanpower.sort_values(by=(len(dfavgmanpower) - 1), axis=1, ascending=False)  #
dfavgmanpower = dfavgmanpower.iloc[:, range(0, y)]
coloriar = []
for nomej in dfavgmanpower.columns:
    coloriar.append(colornazioni[nomej])
ax1 = dfavgmanpower.loc[len(dfavgmanpower) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')
plt.grid(axis='y', alpha=alphagrid)

plt.xticks(rotation=-90)

for i, v in enumerate(dfavgmanpower.loc[len(dfavgmanpower) - 1]):  # testo su barre
    ax1.text(i - len(str(round(v / 1000, 1)) + 'k') * sz, v + 0.05, str(round(v / 1000, 1)) + 'k', color='black',
             fontweight='bold', size=sizes)
plt.title('manpower per province')
plt.savefig(folder + '/manpower per province')
plt.close()
plt.figure(figsize=[19.2, 10.8])
avgincome = [(a - 2) / b for a, b in zip(income.loc[0], dev.loc[0])]
dfavgincome = pd.DataFrame(np.array([avgincome]), columns=players)
dfavgincome = dfavgincome.sort_values(by=(len(dfavgincome) - 1), axis=1, ascending=False)  #
dfavgincome = dfavgincome.iloc[:, range(0, y)]
coloriar = []
for nomej in dfavgincome.columns:
    coloriar.append(colornazioni[nomej])
ax1 = dfavgincome.loc[len(dfavgincome) - 1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')
plt.grid(axis='y', alpha=alphagrid)

plt.xticks(rotation=-90)

for i, v in enumerate(dfavgincome.loc[len(dfavgincome) - 1]):  # testo su barre
    ax1.text(i - len(str(round(v, 2))) * sz, v, str(round(v, 2)), color='black', fontweight='bold', size=sizes)
plt.title('income per dev(nation efficency)')
plt.savefig(folder + '/income per dev(nation efficency)')
plt.close()


# diff income %
def differenza(playerincome, cosa):
    global y
    global alpha1
    global alphagrid

    plt.figure(figsize=[19.2, 10.8])
    diffincome = []
    diffincomeper = []
    diff = lambda x: round(x.iloc[0] - x.iloc[1], 2)
    diffper = lambda x: round(((x.iloc[0] / x.iloc[1]) * 100) - 100, 1)
    playerincome.loc[2] = playerincome.apply(diff)
    playerincome.loc[3] = playerincome.apply(diffper)
    playerincome.dropna(axis=1, inplace=True)
    dfdiffincome = pd.DataFrame(np.array([playerincome.iloc[-1].tolist(), playerincome.iloc[-2].tolist()]),
                                columns=playerincome.columns)
    dfdiffincome = dfdiffincome.sort_values(by=1, axis=1, ascending=False)
    if len(dfdiffincome.columns)<=y:
        y=len(dfdiffincome.columns)
    sz = calcolatorespaziatrura(y)
    sizes = calcolosize(y)
    dfdiffincomeper = pd.DataFrame(np.array([playerincome.iloc[-1].tolist()]), columns=playerincome.columns)
    dfdiffincome = dfdiffincome.iloc[:, range(0, y)]
    coloriar = []
    for nomej in dfdiffincome.columns:
        coloriar.append(colornazioni[nomej])
    dfdiffincomeper = dfdiffincomeper.iloc[:, range(0, y)]
    ax1 = dfdiffincome.iloc[-1].plot.bar(color=coloriar, alpha=alpha1, edgecolor='black')
    plt.grid(axis='y', alpha=alphagrid)
    plt.xticks(rotation=-90)
    plt.title(cosa + ' gained in this session')
    ax2 = ax1.twinx()
    ax2.spines['right'].set_position(('axes', 1.0))

    plt.ylim(-5, 321)
    for i, v in enumerate(dfdiffincome.iloc[0]):  # testo su linea
        if v > 0:
            ax2.text(i - len(str(round(v)) + '+%') * sz, 0.5, '+' + str(round(v)) + '%', color='black',
                     fontweight='bold', size=sizes)
        else:
            try:
                ax2.text(i - len(str(round(v)) + '%') * sz, 0.5,   str(round(v)) + '%', color='black',
                         fontweight='bold', size=sizes)
            except:
                pass
    for i, v in enumerate(dfdiffincome.iloc[1]):  # testo su barre
        if v > 1000:
            ax1.text(i - len(str(round(v / 1000,2))+'k') * sz, v + 0.1, str(round(v / 1000)) + 'k', color='black', fontweight='bold',
                     size=sizes)
        elif v<-1000:
            ax1.text(i - len(str(round(v / 1000,2))+'k') * sz, v + 0.1, str(round(v / 1000)) + 'k', color='black', fontweight='bold',size=sizes)
        else:
            ax1.text(i - len(str(int(v))) * sz, v + 0.1, str(round(v)), color='black', fontweight='bold', size=sizes)


    plt.savefig(folder + '/#' + cosa + ' gained in this session')
    plt.close()


if save2 != '':
    differenza(h[0], 'income')
    differenza(h[1], 'provinces')
    differenza(h[2], 'development')
    differenza(h[3], 'max manpower')
print('check your graphs folder(Press ENTER to close)')