Energy Stats
Oil Price (Futures, Continuous Contract, Front Month)
import pandas as pd
import impl as u
fbp = 'bp-stats-review-2022-consolidated-dataset-panel-format.csv'
df = u.get_yahoofin(2010,"CL=F")
print (df.tail(5))
df.plot(); plt.savefig('oil.png')
Date
2023-02-13 80.139999
2023-02-14 79.059998
2023-02-15 78.589996
2023-02-16 78.489998
2023-02-17 76.500000
Name: Close, dtype: float64
World Oil Reserves
Data from BP. Unit is billion barrels.
df = pd.read_csv(fbp)
df = df[df.Country == 'Total World']
df = df.set_index('Year')
print (df.oilreserves_bbl.tail(4))
df.oilreserves_bbl.plot(grid=True)
plt.savefig('oilreserves.png')
Year
2018 1736.144020
2019 1734.810537
2020 1732.366175
2021 NaN
Name: oilreserves_bbl, dtype: float64
Natural Gas Price
df = u.get_yahoofin(2010,"NG=F")
print (df.tail(7))
df.plot(); plt.savefig('natgas.png')
Date
2023-02-09 2.430
2023-02-10 2.514
2023-02-13 2.405
2023-02-14 2.567
2023-02-15 2.471
2023-02-16 2.389
2023-02-17 2.322
Name: Close, dtype: float64
Energy Production by Source
Global production, units terrawatt hours
kbd Thousand of Barrels Per Day
Ej = Exajoules = 277.778 TWh
pd.set_option('display.max_columns', None)
fbp = 'bp-stats-review-2022-consolidated-dataset-panel-format.csv'
df = pd.read_csv(fbp)
df = df[df.Country == 'Total World']
df = df.set_index('Year')
df = df[df.index > 1980]
df = df[['wind_twh','solar_twh','oilprod_kbd','nuclear_twh','hydro_twh','gasprod_ej','coalprod_ej']]
df['oil_twh'] = df.oilprod_kbd * 365 * 1700 * 1000 / 1e9
df['coal_twh'] = df.coalprod_ej * 277.778
df['gas_twh'] = df.gasprod_ej * 277.778
cols = [x for x in df.columns if '_twh' in x]
df[cols].plot()
plt.savefig('energy-sources.png')
print (df[cols].tail(3))
wind_twh solar_twh nuclear_twh hydro_twh oil_twh \
Year
2019 1420.544110 703.949763 2796.354063 4231.376747 58895.185992
2020 1596.428212 846.229368 2693.978613 4345.990451 54910.671018
2021 1861.939824 1032.501231 2800.267792 4273.827522 55768.604518
coal_twh gas_twh
Year
2019 46428.036448 39677.369853
2020 44068.508171 38615.184559
2021 46550.642074 40368.860045
df2 = df[cols].tail(1).unstack()
df2 = (df2 / df2.sum())*100.0
df2.plot(kind="pie")
plt.savefig('source-pie.png')
df2
Out[1]:
Year
wind_twh 2021 1.219691
solar_twh 2021 0.676355
nuclear_twh 2021 1.834357
hydro_twh 2021 2.799634
oil_twh 2021 36.532052
coal_twh 2021 30.493689
gas_twh 2021 26.444221
dtype: float64
Global Primary Energy Consumption
In terrawatt hours. 'Primary energy comprises commercially-traded fuels, including modern renewables. Energy from all sources of non-fossil power generation is accounted for on an input-equivalent basis'.
df = pd.read_csv(fbp)
df = df[df.Country == 'Total World']
df = df.set_index('Year')
df = df[['primary_ej']]
df['primary_twh'] = df.primary_ej * 277.778
df['primary_gw'] = df['primary_twh']*1000 / (365*24)
print (df[['primary_twh','primary_gw']].tail(4))
df.primary_twh.plot()
plt.savefig('world-energy-combined.png')
primary_twh primary_gw
Year
2018 161772.761640 18467.210233
2019 163174.086345 18627.178806
2020 156670.066530 17884.710791
2021 165319.812784 18872.124747
Energy Consumption Per Country
For 2021. Units are Gigawatts (not GWh or TWh, shows the necessary power input required at each instant).
df = pd.read_csv('bp-stats-review-2022-consolidated-dataset-panel-format.csv')
year = df.Year.max()
df = df[df.Year == year]
df = df.set_index('Country')
df = df[['primary_ej']]
df['primary_twh'] = df.primary_ej * 277.778
df = df['primary_twh'].sort_values(ascending=False).dropna()
df = df[df.index.str.contains('Total')==False]
df = (df*1000 / (365*24)).astype(int)
df.head(20)
Out[1]:
Country
China 4998
US 2948
India 1123
Russian Federation 992
Japan 562
Canada 441
Germany 400
South Korea 398
Brazil 398
Iran 386
Saudi Arabia 343
France 298
Indonesia 263
Other Africa 247
United Kingdom 227
Turkey 216
Mexico 215
Italy 201
Australia 181
Spain 177
Name: primary_twh, dtype: int64
Individual Countries
u.country_bp("US")
Year
wind_twh 2021 1.654620
solar_twh 2021 0.713243
nuclear_twh 2021 3.533104
hydro_twh 2021 1.111511
oil_twh 2021 42.327231
gas_twh 2021 35.659344
coal_twh 2021 12.666405
biogeo_twh 2021 0.989210
ethanol_twh 2021 1.345333
dtype: float64
Production As Percentage of Consumption
Perc Commodity
0 104.87 Oil
1 113.00 Gas
2 110.18 Coal
Electricity 17.06 %
Total
2646.55 GW
LNG Traffic per Year
In billion cubic meters
df = pd.read_csv('lng.csv',sep=';',index_col=0)
df.plot(); plt.savefig('lng.png')
Coal Price
df = u.get_yahoofin(2018,"MTF=F").interpolate();
print (df.tail(4))
df.plot(); plt.savefig('coal.png')
Date
2023-02-13 130.000000
2023-02-14 134.000000
2023-02-15 136.399994
2023-02-16 136.850006
Name: Close, dtype: float64
Lumber
df = u.get_yahoofin(2015,"LBS=F"); df.plot(); plt.savefig('lumber.png')
