import sys
logging.basicConfig(level = logging.INFO, stream = sys.stdout)
list_coicop12 = []
for coicop12_index in range(1, 13):
list_coicop12.append('coicop12_{}'.format(coicop12_index))
var_to_be_simulated = [
'pondmen',
'niveau_vie_decile',
'somme_coicop12',
]
var_to_be_simulated += list_coicop12
p = dict()
df_to_graph = None
for year in [2000, 2005, 2011]:
simulation_data_frame = simulate_df(var_to_be_simulated = var_to_be_simulated, year = year)
aggregates_data_frame = df_weighted_average_grouped(dataframe = simulation_data_frame,
groupe = 'niveau_vie_decile', varlist = var_to_be_simulated)
aggregates_data_frame[year] = aggregates_data_frame['coicop12_4'] / aggregates_data_frame['somme_coicop12']
appendable = aggregates_data_frame[year]
if df_to_graph is not None:
df_to_graph = concat([df_to_graph, appendable], axis = 1)
else:
df_to_graph = appendable
graph_builder_line(df_to_graph)
df.rev_disponible = df.rev_disponible * 1.33
Wconcat2 = df_weighted_average_grouped(dataframe = df, groupe = 'niveau_vie_decile', varlist = varlist)
Wconcat2['taux_d_effort_rev_disponible_{}'.format(year)] = \
Wconcat2['total_taxes_indirectes'] / Wconcat2['rev_disponible']
appendable2 = Wconcat2['taux_d_effort_rev_disponible_{}'.format(year)]
Wconcat3 = df_weighted_average_grouped(dataframe = df, groupe = 'niveau_vie_decile', varlist = varlist)
Wconcat3['taux_d_effort_rev_disp_loyerimput_{}'.format(year)] = \
Wconcat3['total_taxes_indirectes'] / Wconcat3['rev_disp_loyerimput']
appendable3 = Wconcat3['taux_d_effort_rev_disp_loyerimput_{}'.format(year)]
if df_to_graph1 is not None:
df_to_graph1 = concat([df_to_graph1, appendable1], axis = 1)
else:
df_to_graph1 = appendable1
if df_to_graph2 is not None:
df_to_graph2 = concat([df_to_graph2, appendable2], axis = 1)
else:
df_to_graph2 = appendable2
if df_to_graph3 is not None:
df_to_graph3 = concat([df_to_graph3, appendable3], axis = 1)
else:
df_to_graph3 = appendable3
graph_builder_line(df_to_graph1)
graph_builder_line(df_to_graph2)
graph_builder_line(df_to_graph3)
