import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

#%matplotlib inline

import requests 
from bs4 import BeautifulSoup
wikiurl='https://en.wikipedia.org/wiki/List_of_countries_by_carbon_dioxide_emissions'
table_class='wikitable sortable jquery-tablesorter'

response=requests.get(wikiurl)
#status 200: The server successfully answered the http request 
print(response.status_code)

soup = BeautifulSoup(response.text, 'html.parser')
table = soup.find('table',{'class':"wikitable"})

df2018 = pd.read_html(str(table))[0]
df2018


#get lists of data
emi_ = df2018[('2018 CO2 emissions[21]', 'Total excluding LUCF[23]')]
country_ = list(df2018[('Country[20]', 'Country[20]')])
country_mod = [i.replace('\xa0',' ') for i in country_]

#create a DataFrame
df = pd.DataFrame(zip(country_mod,emi_), columns = ['countries', 'emission_2018'])

#remove the row of country that cannot be converted
df = df[df['countries']!='Serbia & Montenegro']  
df.iloc[:,1] = df.iloc[:,1].astype('float')
df = df[(df['emission_2018']>200) & (df['emission_2018']<1000)]
df['percentage'] = [i*100/sum(df['emission_2018']) for i in df['emission_2018']]
df.head(9)


df_s = df.sort_values(by='emission_2018', ascending=False)
df_s.head(9)

plt.figure(figsize=(15,6.5))
sns.set_style('darkgrid')
g = sns.barplot(data=df, x='countries', y='emission_2018',
                ci=False, palette='viridis_r')
g.set_xticklabels(df['countries'], rotation=55, fontdict={'fontsize':10})
plt.show()


def get_color(name, number):
    pal = list(sns.color_palette(palette=name, n_colors=number).as_hex())
    return pal

pal_vi = get_color('viridis_r', len(df))
pal_plas = get_color('plasma_r', len(df))
pal_spec = get_color('Spectral', len(df))
pal_hsv = get_color('hsv', len(df))



import math
plt.gcf().set_size_inches(12, 12)
sns.set_style('darkgrid')

#set max value
max_val = max(df['emission_2018'])*1.01
ax = plt.subplot(projection='polar')

#set the subplot 
ax.set_theta_zero_location('N')
ax.set_theta_direction(1)
ax.set_rlabel_position(0)
ax.set_thetagrids([], labels=[])
ax.set_rgrids(range(len(df)), labels= df['countries'])

#set the projection
ax = plt.subplot(projection='polar')

for i in range(len(df)):
    ax.barh(i, list(df['emission_2018'])[i]*2*np.pi/max_val,
            label=list(df['countries'])[i], color=pal_vi[i])

plt.legend(bbox_to_anchor=(1, 1), loc=2)
plt.show()


import math
plt.gcf().set_size_inches(12, 12)
sns.set_style('darkgrid')

#set max value
max_val = max(df_s['emission_2018'])*1.01
ax = plt.subplot(projection='polar')

for i in range(len(df)):
    ax.barh(i, list(df_s['emission_2018'])[i]*2*np.pi/max_val,
            label=list(df_s['countries'])[i], color=pal_plas[i])

#set the subplot 
ax.set_theta_zero_location('N')
ax.set_theta_direction(1)
ax.set_rlabel_position(0)
ax.set_thetagrids([], labels=[])
ax.set_rgrids(range(len(df)), labels= df_s['countries'])

#set the projection
ax = plt.subplot(projection='polar')
plt.legend(bbox_to_anchor=(1, 1), loc=2)
plt.show()


plt.figure(figsize=(12,12))
ax = plt.subplot(111, polar=True)
plt.axis()

#set min and max value
lowerLimit = 0
max_v = df['emission_2018'].max()

#set heights and width
heights = df['emission_2018']
width = 2*np.pi / len(df.index)

#set index and angle
indexes = list(range(1, len(df.index)+1))
angles = [element * width for element in indexes]

bars = ax.bar(x=angles, height=heights, width=width, bottom=lowerLimit,
              linewidth=1, edgecolor="white", color=pal_vi)
labelPadding = 15

for bar, angle, height, label in zip(bars,angles, heights, df['countries']):
    rotation = np.rad2deg(angle)
    alignment = ""
    #deal with alignment
    if angle >= np.pi/2 and angle < 3*np.pi/2:
        alignment = "right"
        rotation = rotation + 180
    else: 
        alignment = "left"
    ax.text(x=angle, y=lowerLimit + bar.get_height() + labelPadding,
            s=label, ha=alignment, va='center', rotation=rotation, 
            rotation_mode="anchor")
    ax.set_thetagrids([], labels=[])


plt.show()



plt.figure(figsize=(12,12))
ax = plt.subplot(111, polar=True)
plt.axis()

#set min and max value
lowerLimit = 0
max_v = df_s['emission_2018'].max()

#set heights and width
heights = df_s['emission_2018']
width = 2*np.pi / len(df_s.index)

#set index and angle
indexes = list(range(1, len(df_s.index)+1))
angles = [element * width for element in indexes]

bars = ax.bar(x=angles, height=heights, width=width, bottom=lowerLimit,
              linewidth=1, edgecolor="white", color=pal_plas)
labelPadding = 15

for bar, angle, height, label in zip(bars,angles, heights, df_s['countries']):
    rotation = np.rad2deg(angle)
    alignment = ""
    #deal with alignment
    if angle >= np.pi/2 and angle < 3*np.pi/2:
        alignment = "right"
        rotation = rotation + 180
    else: 
        alignment = "left"
    ax.text(x=angle, y=lowerLimit + bar.get_height() + labelPadding,
            s=label, ha=alignment, va='center', rotation=rotation, 
            rotation_mode="anchor")
    ax.set_thetagrids([], labels=[])


plt.show()