In [1]:

%matplotlib inline
import matplotlib.pyplot as plt
plt.style.use("ggplot")

In [2]:

from pandas_datapackage_reader import read_datapackage
from shortcountrynames import to_name

In [3]:

df = read_datapackage("https://github.com/openclimatedata/edgar-co2-emissions")

In [4]:

unit = "kt"

In [5]:

df.head()

Out[5]:

				Emissions
Code	Name	Sector	Year
AFG	Afghanistan	Transport	1970	503.4713
		Other industrial combustion	1970	128.9440
		Buildings	1970	641.5890
		Non-combustion	1970	457.8263
		Power Industry	1970	10.4453

In [6]:

df = df.reset_index().drop("Name", axis=1).set_index(["Code", "Sector", "Year"]).sort_index()
df.head()

Out[6]:

			Emissions
Code	Sector	Year
ABW	Buildings	1970	0.090406
		1971	0.090664
		1972	0.098132
		1973	0.098482
		1974	0.094293

In [7]:

for code in ["WORLD", "USA", "CHN", "EU28"]:
    grouped = df.loc[code].reset_index().set_index("Year").groupby("Sector")["Emissions"]

    fig, axes = plt.subplots(nrows=1, ncols=5, figsize=(12,4), sharey=True)
    try:
        name = to_name(code)
    except KeyError:
        name = code
    fig.suptitle(name)
    sectors = ['Power Industry', 'Transport', 'Buildings', 'Other industrial combustion', 'Non-combustion']
    for (key, ax) in zip(sectors, axes):
        ax.set_title(key,  fontsize=10)
        grouped.get_group(key).plot(ax=ax, legend=False)
        ax.set_ylabel(unit)