Code to compare GDP to CO2 Levels since the year 0 AD

consumption_climate_change.py

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

gdp_ = 'http://www.ggdc.net/MADDISON/Historical_Statistics/vertical-file_02-2010.xls'
gdp = pd.read_excel(gdp_, sheet_name='PerCapita GDP', header =2, usecols=[0, 182], names=['year', 'GlobalGDPPerCapita']).dropna()
gdp.year = gdp.year.astype(int)

co2_ = 'ftp://data.iac.ethz.ch/CMIP6/input4MIPs/UoM/GHGConc/CMIP/yr/atmos/UoM-CMIP-1-1-0/GHGConc/gr3-GMNHSH/v20160701/mole_fraction_of_carbon_dioxide_in_air_input4MIPs_GHGConcentrations_CMIP_UoM-CMIP-1-1-0_gr3-GMNHSH_0000-2014.csv'
co2 = pd.read_csv(co2_)

df = gdp.merge(co2, on='year', how='inner').set_index('year')
df['LOG GDP Per Capita'] = np.log(df['GlobalGDPPerCapita'])
df = df/df.loc[1] * 100
df = df.reset_index()

fig, ax = plt.subplots(figsize=(10,5))
ax.plot(df['year'], df['LOG GDP Per Capita'], label='Log Global GDP Per Capita')
ax.plot(df['year'], df['data_mean_global'], label='Global C02 Levels')
plt.legend(frameon=False, ncol=2, loc='upper center')
plt.xlabel('Year')
plt.ylabel('Indexed to Year 1 AD = 100')
plt.title('Global Economic Output and CO2 Levels', y = 1.05, size=16, loc='left')
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.text(x=0, y=-0.2, s='Sources: IAC Switzerland and Angus Maddison', transform = ax.transAxes)
plt.show()