import pandas as pd
import psycopg2 as psy
import matplotlib.pyplot as plt


data = pd.read_csv(r'co2_emission.csv')
df = pd.DataFrame(data)
df2 = df.drop_duplicates()
co = None


try : 
    co = psy.connect(host='berlin',
        database = 'dbmalanone',
        user = 'malanone',
        password = 'azertyuiop')
    curs=co.cursor()

    #Delete all the lines which has no data
    curs.execute('''DELETE FROM CO_DEUX WHERE emission = 0''')
    curs.execute('''DELETE FROM CO_DEUX WHERE code LIKE 'NaN' ''')

	   #Chart that picture the evolution of the emission in France
    df3 = pd.read_sql('''SELECT * FROM CO_DEUX WHERE code LIKE 'FRA';''',con=co)

    #Chart that picture the evolution of the emission in France
    print(df3)
    fig = df3.plot(x='year', y='emission', legend=False, style='-')
    fig.set_title("Quantité d'émission (tonnes) en fonction des années")
    fig.set_xlabel("annee")
    fig.set_ylabel("emissions (en tonnes)")
 
    plt.show()


    df4 = pd.read_sql('''SELECT max(emission)emission, year, code FROM CO_DEUX WHERE code NOT LIKE 'OWID_WRL' GROUP BY year, code,emission HAVING emission = max(emission) ORDER BY year;''',con=co)
    print(df4)
    fig = df4.plot(x='code', y='year', legend=False, kind ='bar' ,style='-')
    fig.set_title("Plus gros pollueur de chaque annee")
    fig.set_xlabel("code du pays")
    fig.set_ylabel("annee")
    fig.set_xticks(df4.index)
    fig.set_xticklabels(df4['code'], rotation='45')
    plt.show()



    df5 = pd.read_sql('''SELECT emission,code FROM CO_DEUX WHERE code NOT LIKE 'OWID_WRL' AND year = 2017 GROUP BY emission,code HAVING emission >= (SELECT avg(emission) FROM CO_DEUX WHERE year = 2017);''',con=co)
    print(df5)
    fig = df5.plot(y='code', autopct='%1.1f%%', kind='pie', legend=False)
    fig.set_title("Pays dont l'émission de CO2 en 2017 dépasse la moyenne")
    fig.set_ylabel("emissions (en tonnes)")
    fig.set_ylim(0)
    plt.show()



    df6 = pd.read_sql('''SELECT avg(emission)moy, code FROM CO_DEUX GROUP BY code;''',con=co)
    print(df6)
    fig = df6.plot(x='code', y='moy', legend=False, style='-')
    fig.set_title("Quantité d'émission (tonnes) en fonction des années")
    fig.set_xlabel("code pays")
    fig.set_ylabel("emissions moyennes (en tonnes)")
    fig.set_xticks(df6.index)
    fig.set_xticklabels(df6['code'], rotation='45')

	# df6 = pd.read_sql('''SELECT * FROM CO_DEUX HAVING ;''',con=co)

	# fig = df6.plot(x='year', y='emission', legend=False, style='-')
   #  fig.set_title("Quantité d'émission (tonnes) en fonction des années")
   #  fig.set_xlabel("annee")
    # fig.set_ylabel("emissions (en tonnes)")
    
    plt.show()

    co.commit()




except (Exception, psy.DatabaseError) as error :
    print(error)

finally :
    if co is not None:
        co.close()