#!/usr/bin/env python
# coding: utf-8

# # Explore UNFCCC emissions data

# In[1]:


import os
from pathlib import Path

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


# In[2]:


# data directory
data_dir  = Path(os.path.abspath("../data/processed/"))
data_file = data_dir / "unfccc-ghg-without-lulucf-1990-2021.csv"

# load data
df = pd.read_csv(data_file)


# # 1. Who are the top 10 emitters for 2021

# In[3]:


df.loc[df['year'] == 2021].sort_values(by='emissions_gt',ascending=False)[0:10]


# In[4]:


top10 = list(df.loc[df['year'] == 2021].sort_values(by='emissions_gt',ascending=False)[0:10]['party'])


# In[5]:


for party in top10:
    data = df.loc[df['party'] == party]
    plt.plot(data['year'], data['emissions_gt'], label=party)

plt.xlabel('Year')
plt.ylabel('Emissions (gigatonne)')

plt.legend(title='Country', bbox_to_anchor=(1.05, 1), loc='upper left')


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