# -*- coding: utf-8 -*-
"""
Created on Wed Feb 10 18:40:27 2016
@author: thomas.douenne
"""
from __future__ import division
from openfisca_france_indirect_taxation.examples.utils_example import simulate
simulated_variables = [
'pondmen',
'decuc',
'depenses_diesel_ht',
'depenses_diesel_htva',
'diesel_ticpe',
'depenses_diesel',
'depenses_diesel_recalculees'
]
# Merge des deux listes
for year in [2000]:
# Constition d'une base de données agrégée par décile (= collapse en stata)
df = simulate(simulated_variables = simulated_variables, year = year)
df['check_diesel_ht'] = df['depenses_diesel_ht'] - (df['depenses_diesel_htva'] - df['diesel_ticpe'])
assert (df['check_diesel_ht'] == 0).any()
df['check_diesel_recalcule'] = df['depenses_diesel'] - df['depenses_diesel_recalculees']
assert (df['check_diesel_recalcule'] == 0).any()
list_coicop12 = []
for coicop12_index in range(1, 13):
list_coicop12.append('coicop12_{}'.format(coicop12_index))
simulated_variables = [
'pondmen',
'niveau_vie_decile',
'somme_coicop12',
]
simulated_variables += list_coicop12
p = dict()
df_to_graph = None
for year in [2000, 2005, 2011]:
simulation_data_frame = simulate(
simulated_variables=simulated_variables, year=year)
aggregates_data_frame = df_weighted_average_grouped(
dataframe=simulation_data_frame,
groupe='niveau_vie_decile',
varlist=simulated_variables)
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_percent(df_to_graph, 1, 1)
list_coicop12 = ['coicop12_2']
# for coicop12_index in range(1, 13):
# list_coicop12.append('coicop12_{}'.format(coicop12_index))
# Liste des variables que l'on veut simuler
simulated_variables = [
'pondmen', 'decuc', 'niveau_vie_decile', 'revtot', 'niveau_de_vie',
'rev_disponible', 'depenses_cigarettes', 'depenses_cigares',
'depenses_tabac_a_rouler', 'depenses_alcools_forts', 'depenses_vin',
'depenses_biere'
]
# Merge des deux listes
simulated_variables += list_coicop12
for year in [2000, 2005, 2011]:
# Constition d'une base de données agrégée par décile (= collapse en stata)
df = simulate(simulated_variables=simulated_variables, year=year)
if year == 2011:
df.niveau_vie_decile[df.decuc == 10] = 10
var_to_concat = list_coicop12 + ['rev_disponible']
Wconcat = df_weighted_average_grouped(dataframe=df,
groupe='niveau_vie_decile',
varlist=simulated_variables)
list_alcool_tabac = []
Wconcat['part_alcool'] = \
(Wconcat['depenses_alcools_forts'] + Wconcat['depenses_vin'] + Wconcat['depenses_biere']) \
/ Wconcat['rev_disponible']
list_alcool_tabac.append('part_alcool')
Wconcat['part_tabac'] = \
(Wconcat['depenses_cigarettes'] + Wconcat['depenses_cigares'] +
Wconcat['depenses_tabac_a_rouler']) / Wconcat['rev_disponible']
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))
simulated_variables = [
'pondmen',
'niveau_vie_decile',
'somme_coicop12',
]
simulated_variables += list_coicop12
p = dict()
df_to_graph = None
for year in [2000, 2005, 2011]:
simulation_data_frame = simulate(simulated_variables = simulated_variables, year = year)
aggregates_data_frame = df_weighted_average_grouped(dataframe = simulation_data_frame,
groupe = 'niveau_vie_decile', varlist = simulated_variables)
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_percent(df_to_graph, 1, 1)
