def test_corrections():
years = [2006, 2007, 2008, 2009]
df = get_denombrements_fiscaux_data_frame(years=years)
index_by_variable_name = create_index_by_variable_name(formula_by_variable_name, level_2_formula_by_variable_name)
test_by_variable = dict(
# Correction of f5io in 2008 in Agrégats IPP
benefices_agricoles_forfait_imposables=[
{"year": 2006, "target": 896512850},
{"year": 2008, "target": 883970587},
],
benefices_agricoles_reels_imposables=[
{"year": 2006, "target": 5150417953},
{"year": 2008, "target": 6515953706},
],
benefices_agricoles_reels_sans_cga_imposables=[{"year": 2006, "target": 165830038}],
benefices_agricoles_reels_deficits=[{"year": 2006, "target": 519217942}],
benefices_agricoles_reels_sans_cga_deficits=[{"year": 2006, "target": 208934263}],
deficits_industriels_commerciaux_professionnels=[{"year": 2006, "target": 1427052021}],
deficits_industriels_commerciaux_non_professionnels=[{"year": 2006, "target": 301194784}],
plus_values_mobilieres_stock_options=[{"year": 2008, "target": 228873359}],
)
def assert_value_construction(variable_name, test):
year = test["year"]
target = test["target"]
value = get_or_construct_value(df, variable_name, index_by_variable_name, years=years)[0].loc[year]
assert all(value == target), "{} for {}: got {} instead of {}".format(variable_name, year, value.values, target)
for variable_name, tests in test_by_variable.iteritems():
for test in tests:
yield assert_value_construction, variable_name, test
def test_run_through():
years = [2006, 2007, 2008, 2009]
df = get_denombrements_fiscaux_data_frame(years=years)
index_by_variable_name = create_index_by_variable_name(
formula_by_variable_name, level_2_formula_by_variable_name)
variable_name = 'interets_imposes_au_prelevement_liberatoire'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years)
variable_name = 'dividendes_imposes_au_prelevement_liberatoire'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years)
variable_name = 'revenus_imposes_au_prelevement_liberatoire'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years,
fill_value=0)
variable_name = 'assurances_vie_imposees_au_prelevement_liberatoire'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years)
variable_name = 'f2da'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years)
def test_run_through():
years = [2006, 2007, 2008, 2009]
df = get_denombrements_fiscaux_data_frame(years=years)
index_by_variable_name = create_index_by_variable_name(formula_by_variable_name, level_2_formula_by_variable_name)
variable_name = "interets_imposes_au_prelevement_liberatoire"
get_or_construct_value(df, variable_name, index_by_variable_name, years=years)
variable_name = "dividendes_imposes_au_prelevement_liberatoire"
get_or_construct_value(df, variable_name, index_by_variable_name, years=years)
variable_name = "revenus_imposes_au_prelevement_liberatoire"
get_or_construct_value(df, variable_name, index_by_variable_name, years=years, fill_value=0)
variable_name = "assurances_vie_imposees_au_prelevement_liberatoire"
get_or_construct_value(df, variable_name, index_by_variable_name, years=years)
variable_name = "f2da"
get_or_construct_value(df, variable_name, index_by_variable_name, years=years)
def test_run_through():
years = [2006, 2007, 2008, 2009, 2010, 2011]
df = get_denombrements_fiscaux_data_frame(years=years)
index_by_variable_name = create_index_by_variable_name(
formula_by_variable_name, level_2_formula_by_variable_name)
variable_name = 'interets_imposes_au_prelevement_liberatoire'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years)
variable_name = 'dividendes_imposes_au_prelevement_liberatoire'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years)
variable_name = 'revenus_imposes_au_prelevement_liberatoire'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years,
fill_value=0)
variable_name = 'assurances_vie_imposees_au_prelevement_liberatoire'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years)
variable_name = 'f2da'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years)
variable_name = u'f5he'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=range(2010, 2012))
variable_name = u'f5jr'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=range(2007, 2012),
fill_value=0)
variable_name = 'plus_values_professionnelles_regime_normal'
get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=range(2007, 2012),
fill_value=0)
def test_run_through():
years = [2006, 2007, 2008, 2009, 2010, 2011]
df = get_denombrements_fiscaux_data_frame(years = years)
index_by_variable_name = create_index_by_variable_name(formula_by_variable_name, level_2_formula_by_variable_name)
variable_name = 'interets_imposes_au_prelevement_liberatoire'
get_or_construct_value(df, variable_name, index_by_variable_name, years = years)
variable_name = 'dividendes_imposes_au_prelevement_liberatoire'
get_or_construct_value(df, variable_name, index_by_variable_name, years = years)
variable_name = 'revenus_imposes_au_prelevement_liberatoire'
get_or_construct_value(df, variable_name, index_by_variable_name, years = years, fill_value = 0)
variable_name = 'assurances_vie_imposees_au_prelevement_liberatoire'
get_or_construct_value(df, variable_name, index_by_variable_name, years = years)
variable_name = 'f2da'
get_or_construct_value(df, variable_name, index_by_variable_name, years = years)
variable_name = u'f5he'
get_or_construct_value(df, variable_name, index_by_variable_name, years = range(2010, 2012))
variable_name = u'f5jr'
get_or_construct_value(df, variable_name, index_by_variable_name, years = range(2007, 2012), fill_value = 0)
variable_name = 'plus_values_professionnelles_regime_normal'
get_or_construct_value(df, variable_name, index_by_variable_name, years = range(2007, 2012), fill_value = 0)
def test_corrections():
years = [2006, 2007, 2008, 2009]
df = get_denombrements_fiscaux_data_frame(years=years)
index_by_variable_name = create_index_by_variable_name(
formula_by_variable_name, level_2_formula_by_variable_name)
test_by_variable = dict(
# Correction of f5io in 2008 in Agrégats IPP
benefices_agricoles_forfait_imposables=[
{
'year': 2006,
'target': 896512850
},
{
'year': 2008,
'target': 883970587
},
],
benefices_agricoles_reels_imposables=[
{
'year': 2006,
'target': 5150417953
},
{
'year': 2008,
'target': 6515953706
},
],
benefices_agricoles_reels_sans_cga_imposables=[
{
'year': 2006,
'target': 165830038
},
],
benefices_agricoles_reels_deficits=[
{
'year': 2006,
'target': 519217942
},
],
benefices_agricoles_reels_sans_cga_deficits=[
{
'year': 2006,
'target': 208934263
},
],
deficits_industriels_commerciaux_professionnels=[
{
'year': 2006,
'target': 1427052021
},
],
deficits_industriels_commerciaux_non_professionnels=[
{
'year': 2006,
'target': 301194784
},
],
plus_values_mobilieres_stock_options=[{
'year': 2008,
'target': 228873359
}],
)
def assert_value_construction(variable_name, test):
year = test['year']
target = test['target']
value = get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years)[0].loc[year]
assert all(value == target), "{} for {}: got {} instead of {}".format(
variable_name, year, value.values, target)
for variable_name, tests in test_by_variable.iteritems():
for test in tests:
yield assert_value_construction, variable_name, test
def test_corrections():
years = range(2006, 2013)
df = get_denombrements_fiscaux_data_frame(years=years)
index_by_variable_name = create_index_by_variable_name(
formula_by_variable_name, level_2_formula_by_variable_name)
test_by_variable = dict(
# Correction of f5io in 2008 in Agrégats IPP
benefices_agricoles_forfait_imposables=[
{
'year': 2006,
'target': 896512850
},
{
'year': 2008,
'target': 883970587
},
],
benefices_agricoles_reels_imposables=[
{
'year': 2006,
'target': 5150417953
},
{
'year': 2008,
'target': 6515953706
},
],
benefices_agricoles_reels_imposables_sans_cga=[
{
'year': 2006,
'target': 165830038
},
],
benefices_agricoles_reels_deficits=[
{
'year': 2006,
'target': 519217942
},
],
benefices_agricoles_reels_sans_cga_deficits=[
{
'year': 2006,
'target': 208934263
},
],
deficits_industriels_commerciaux_professionnels=[
{
'year': 2006,
'target': 1427052021
},
],
deficits_industriels_commerciaux_non_professionnels=[
{
'year': 2006,
'target': 301194784
},
],
plus_values_mobilieres_stock_options=[
{
'year': 2008,
'target': 228873359
},
# {'year': 2010, 'target': 690459289}, TODO: check dénombremenst DGFIP vs IPP
],
revenus_imposes_au_bareme=[
{
'year': 2010,
'target': 18907148239
},
],
plus_values_mobilieres_regime_normal=[
{
'year': 2010,
'target': 5393808406
},
],
plus_values_professionnelles_regime_normal=[
{
'year': 2011,
'target': 1101248065
},
{
'year': 2010,
'target': 1083102431
},
],
# Inversion 2ch et 2gr dans dénombrements fiscax (Agrégats IPP et en ligne)
assurances_vie_imposees_au_bareme=[
{
'year': 2009,
'target': 1063726777
},
],
# Test revenus exonérés
benefices_agricoles_forfait_exoneres=[
{
'year': 2011,
'target': (5826752 + 466632 + 467)
},
],
benefices_agricoles_reels_exoneres=[
{
'year': 2011,
'target': (64880784 + 15074222 + 3733)
},
],
benefices_agricoles_reels_exoneres_sans_cga=[
{
'year': 2011,
'target': (10214497 + 2275427 + 171787)
},
],
)
def assert_value_construction(variable_name, test):
year = test['year']
target = test['target']
value = get_or_construct_value(df,
variable_name,
index_by_variable_name,
years=years,
fill_value=0)[0].loc[year]
if year >= 2009:
assert all(
value == target), "{} for {}: got {} instead of {}".format(
variable_name, year, value.values, target)
for variable_name, tests in test_by_variable.iteritems():
for test in tests:
yield assert_value_construction, variable_name, test
def test_corrections():
years = range(2006, 2013)
df = get_denombrements_fiscaux_data_frame(years = years)
index_by_variable_name = create_index_by_variable_name(formula_by_variable_name, level_2_formula_by_variable_name)
test_by_variable = dict(
# Correction of f5io in 2008 in Agrégats IPP
benefices_agricoles_forfait_imposables = [
{'year': 2006, 'target': 896512850},
{'year': 2008, 'target': 883970587},
],
benefices_agricoles_reels_imposables = [
{'year': 2006, 'target': 5150417953},
{'year': 2008, 'target': 6515953706},
],
benefices_agricoles_reels_imposables_sans_cga = [
{'year': 2006, 'target': 165830038},
],
benefices_agricoles_reels_deficits = [
{'year': 2006, 'target': 519217942},
],
benefices_agricoles_reels_sans_cga_deficits = [
{'year': 2006, 'target': 208934263},
],
deficits_industriels_commerciaux_professionnels = [
{'year': 2006, 'target': 1427052021},
],
deficits_industriels_commerciaux_non_professionnels = [
{'year': 2006, 'target': 301194784},
],
plus_values_mobilieres_stock_options = [
{'year': 2008, 'target': 228873359},
# {'year': 2010, 'target': 690459289}, TODO: check dénombremenst DGFIP vs IPP
],
revenus_imposes_au_bareme = [
{'year': 2010, 'target': 18907148239},
],
plus_values_mobilieres_regime_normal = [
{'year': 2010, 'target': 5393808406},
],
plus_values_professionnelles_regime_normal = [
{'year': 2011, 'target': 1101248065},
{'year': 2010, 'target': 1083102431},
],
# Inversion 2ch et 2gr dans dénombrements fiscax (Agrégats IPP et en ligne)
assurances_vie_imposees_au_bareme = [
{'year': 2009, 'target': 1063726777},
],
# Test revenus exonérés
benefices_agricoles_forfait_exoneres = [
{'year': 2011, 'target': (5826752 + 466632 + 467)},
],
benefices_agricoles_reels_exoneres = [
{'year': 2011, 'target': (64880784 + 15074222 + 3733)},
],
benefices_agricoles_reels_exoneres_sans_cga = [
{'year': 2011, 'target': (10214497 + 2275427 + 171787)},
],
)
def assert_value_construction(variable_name, test):
year = test['year']
target = test['target']
value = get_or_construct_value(
df, variable_name, index_by_variable_name, years = years, fill_value = 0)[0].loc[year]
if year >= 2009:
assert all(value == target), "{} for {}: got {} instead of {}".format(
variable_name, year, value.values, target)
for variable_name, tests in test_by_variable.iteritems():
for test in tests:
yield assert_value_construction, variable_name, test
