1. notebooks
  2. Global Carbon Budget | Territorial and Consumption Emissions.ipynb
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]:
emissions = read_datapackage("https://github.com/openclimatedata/global-carbon-budget", "territorial-emissions")
In [4]:
emissions.head()
Out[4]:
Emissions Source
Code Year
ABW 1959 0.196 CDIAC
1960 0.169 CDIAC
1961 0.176 CDIAC
1962 0.193 CDIAC
1963 0.185 CDIAC
In [5]:
emissions = emissions.drop("Source", axis=1)
In [6]:
unit = "MtC"
In [7]:
ax = emissions.loc["CHN"].plot()
emissions.loc["USA"].plot(ax=ax)
plt.legend([to_name("CHN"), to_name("USA")])
plt.ylabel(unit);
In [8]:
consumption = read_datapackage("https://github.com/openclimatedata/global-carbon-budget", "consumption-emissions")
In [9]:
consumption.head()
Out[9]:
Consumption-Emissions
Code Year
ALB 1990 1.533
1991 1.246
1992 0.775
1993 0.718
1994 0.626
In [10]:
unit_consumption = "MtC"
In [11]:
parties = ["USA", "CHN"]
for code in parties:
    ax = consumption.loc[code].plot()
    emissions.loc[code].plot(ax=ax)
    assert unit == unit_consumption
    plt.title(to_name(code))
    plt.ylabel(unit)
In [ ]: