Electricity price in Portugal

This article compares the price of electricity across the different european countries, showing the unbalance between earnings and electricity cost in Portugal. For that it was used the eurostat database and the programming language Python.

Step 1: import the needed libraries and find the needed eurostat databases.

# import the libraries

import pandas as pd

import eurostat

# import the database names

toc_df = eurostat.get_toc_df()

toc_df.describe()

# find specific databases based on a string

[i for i in toc_df.title if "Final energy consumption in households" in i]

# or

eurostat.subset_toc_df(toc_df, "Final energy consumption in households")

Step 2: import the needed eurostat databases.

# find the databases codes and import the databases

# Final energy consumption in households

cod = toc_df.loc[9079,'code']

cons_house = eurostat.get_data_df(cod)

cons_house.head()

cons_house.shape

cons_house = cons_house.loc[:,['geo\\time','unit',2019]]

cons_house.columns = ['geo','unit_ch','2019_ch']

cons_house.index = cons_house['geo']

# Final energy consumption in households per capita

cod = toc_df.loc[8528,'code']

cons_house_pc = eurostat.get_data_df(cod)

cons_house_pc.head()

cons_house_pc = cons_house_pc.loc[:,['geo\\time','unit',2019]]

cons_house_pc.columns = ['geo','unit_chpc','2019_chpc']

cons_house_pc.index = cons_house_pc['geo']

# Final energy consumption in households by type of fuel

cod = toc_df.loc[8519,'code']

cons_house_tf = eurostat.get_data_df(cod)

cons_house_tf.head()

cons_house_tf['siec'].unique()

# Final electricity consumption in households

cons_house_tf = cons_house_tf.loc[cons_house_tf.siec=='E7000',['siec','unit','geo\\time',2019]]

cons_house_tf.columns = ['siec','unit_ech','geo','2019_ech']

cons_house_tf.index = cons_house_tf['geo']

# Annual net earnings

cod = 'earn_nt_net'

earn = eurostat.get_data_df(cod)

earn.head()

earn.columns

for i in ['currency','estruct','ecase']:

earn[i].unique()

# Two-earner couple with two children, both earning 100% of the average earning

earn = earn.loc[(earn.estruct=='NET') & (earn.currency=='EUR') & (earn.ecase=='CPL_CH2_AW100_100'), ['geo\\time',2019]]

earn.columns = ['geo','2019_earn']

earn.index = earn['geo']

# Electricity prices (VAT and consumption)

cod = 'nrg_pc_204_c'

prices = eurostat.get_data_df(cod)

prices.head()

prices.columns

for i in ['nrg_cons','nrg_prc','currency']:

prices[i].unique()

prices_vat = prices.loc[(prices.nrg_cons=='TOT_KWH') & (prices.nrg_prc=='VAT') & (prices.currency=='EUR'),['geo\\time','2019']]

prices_vat.columns = ['geo','2019_prvat']

prices_vat.index = prices_vat['geo']

prices_eng = prices.loc[(prices.nrg_cons=='TOT_KWH') & (prices.nrg_prc!='VAT') & (prices.currency=='EUR'),['geo\\time','2019']].groupby(['geo\\time']).sum()

prices_eng.columns = ['2019_preng']

Step 3: join the dataframes and calculate the needed variables.

# join the data

energy = pd.concat([cons_house, cons_house_pc, cons_house_tf, earn, prices_vat, prices_eng], axis=1, join='outer', sort=False)

energy.columns

energy['geo'] = energy.index

# calculate the households electricty consumption per capita

energy['2019_echpc'] = energy['2019_ech'] * energy['2019_chpc'] / energy['2019_ch']

# calculate the households cost with electricty consumption with VAT per capita

energy['2019_ecthpc'] = energy['2019_echpc'] * (energy['2019_preng'] + energy['2019_prvat'])

Step 4: calculate the rankings of UE countries.

geo = ['NL', 'AT', 'BE', 'BG', 'CY', 'CZ', 'DE', 'DK', 'EE', 'EL', 'ES', 'FI', 'FR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'NL', 'PL', 'PT', 'RO', 'SE', 'SI', 'SK']

# households cost with electricty consumption with VAT per capita, portuguese ranking

energy.loc[geo,'2019_ecthpc'].rank(ascending=False)['PT']

# two-earner couple with one children, both earning 100% of the average earning, portuguese ranking

energy.rank(ascending=False).loc['PT','2019_earn']

# calculate the european countries average of the households electricty consumption per capita

mean_echpc = energy['2019_echpc'].mean()

# calculate the households cost with electricty consumption with VAT per capita if europeans consumption was equal

energy['2019_mecthpc'] = mean_echpc * (energy['2019_preng'] + energy['2019_prvat'])

Step 5: verifying Portugal's rankings

# households cost with electricty consumption with VAT per capita, portuguese ranking

energy.loc[geo, '2019_ecthpc'].rank(ascending=False)['PT']

# two-earner couple with one children, both earning 100% of the average earning, portuguese ranking

energy.loc[geo, '2019_earn'].rank(ascending=False).loc['PT']

# calculate the european countries average of the households electricty consumption per capita

mean_echpc = energy['2019_echpc'].mean()

# calculate the households cost with electricty consumption with VAT per capita if europeans consumption was equal

energy['2019_mecthpc'] = mean_echpc * (energy['2019_preng'] + energy['2019_prvat'])

# households cost with electricty consumption with VAT per capita if europeans consumption was equal, portuguese ranking

energy.loc[geo, '2019_mecthpc'].rank(ascending=False).loc['PT']

Conclusion:

Portugal has the 7th households cost with electricty consumption with VAT per capita higher in EU but, if we look to the earnings of a typical family with two-earner couple and one children, both earning 100% of the average earning, Portugal is in the 17th position. If we look just for the electricity consumption cost, we can conclude that Portugal has even an higher position.