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Merge pull request #1902 from martinholmer/fix-tables
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Improve handling of non-positive incomes in tables and graphs
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@martinholmer
martinholmer authored Mar 8, 2018
2 parents f55d018 + eb3ce9d commit 8fc3308
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Showing 4 changed files with 154 additions and 331 deletions.
77 changes: 14 additions & 63 deletions taxcalc/calculate.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -38,8 +38,7 @@
ce_aftertax_expanded_income,
mtr_graph_data, atr_graph_data, xtr_graph_plot,
dec_graph_data, dec_graph_plot,
pch_graph_data, pch_graph_plot,
qin_graph_data, qin_graph_plot)
pch_graph_data, pch_graph_plot)
# import pdb


Expand Down Expand Up @@ -991,7 +990,7 @@ def pch_graph(self, calc):
title='')
return fig

def decile_graph(self, calc, set_bottom_decile_result_to_zero=True):
def decile_graph(self, calc, hide_negative_incomes=True):
"""
Create graph that shows percentage change in aftertax expanded
income (from going from policy in self to policy in calc) for
Expand All @@ -1001,8 +1000,6 @@ def decile_graph(self, calc, set_bottom_decile_result_to_zero=True):
immediately in an interactive or notebook session (following
the instructions in the documentation of the xtr_graph_plot
utility function).
Note that some deciles may contain filing units with negative
or zero baseline (self) expanded income.
Parameters
----------
Expand All @@ -1011,11 +1008,16 @@ def decile_graph(self, calc, set_bottom_decile_result_to_zero=True):
where both self and calc have calculated taxes for this year
before being used by this method
set_bottom_decile_result_to_zero : boolean
specify whether or not bottom decile (which contains filing
units with non-positive expanded income) result is shown in the
graph (default value is True; set to False to show the bottom
decile result)
hide_negative_incomes : boolean
if True (which is the default), the bottom table bin containing
filing units with non-positive expanded_income is not shown in
the graph and the table bin containing filing units with positive
expanded_income in the bottom decile is shown with its bar width
adjusted to the number of weighted filing units in bottom decile
who have positive expanded_income; if False, the bottom table bin
containing filing units with non-positive expanded_income is shown,
which may be misleading because the percentage change is correctly
calculated with a negative divisor.
Returns
-------
Expand All @@ -1030,9 +1032,8 @@ def decile_graph(self, calc, set_bottom_decile_result_to_zero=True):
income_measure='expanded_income',
tax_to_diff='combined')
# construct data for graph
data = dec_graph_data(diff_table, year=self.current_year)
if set_bottom_decile_result_to_zero:
data['bars'][0]['value'] = 0
data = dec_graph_data(diff_table, year=self.current_year,
hide_negative_incomes=hide_negative_incomes)
# construct figure from data
fig = dec_graph_plot(data,
width=850,
Expand All @@ -1042,56 +1043,6 @@ def decile_graph(self, calc, set_bottom_decile_result_to_zero=True):
title='')
return fig

def quintile_graph(self, calc, set_bottom_quintile_result_to_zero=True):
"""Create graph that shows percentage change in aftertax expanded
income (from going from policy in self to policy in calc) for
each expanded-income quintile and subgroups of the top quintile.
The graph can be written to an HTML file (using the
write_graph_file utility function) or shown on the screen
immediately in an interactive or notebook session (following
the instructions in the documentation of the xtr_graph_plot
utility function).
Note that some quintiles may contain filing units with negative
or zero baseline (self) expanded income.
Parameters
----------
calc : Calculator object
calc represents the reform while self represents the baseline,
where both self and calc have calculated taxes for this year
before being used by this method
set_bottom_quintile_result_to_zero : boolean
specify whether or not bottom quintile (which contains filing
units with non-positive expanded income) result is shown in the
graph (default value is True; set to False to show the bottom
quintile result)
Returns
-------
graph that is a bokeh.plotting figure object
"""
# check that two Calculator objects are comparable
assert isinstance(calc, Calculator)
assert calc.current_year == self.current_year
assert calc.array_len == self.array_len
diff_table = self.difference_table(calc,
groupby='weighted_deciles',
income_measure='expanded_income',
tax_to_diff='combined')
# construct data for graph
data = qin_graph_data(diff_table, year=self.current_year)
if set_bottom_quintile_result_to_zero:
data['bars'][0]['value'] = 0
# construct figure from data
fig = qin_graph_plot(data,
width=850,
height=500,
xlabel='',
ylabel='',
title='')
return fig

@staticmethod
def read_json_param_objects(reform, assump):
"""
Expand Down
2 changes: 1 addition & 1 deletion taxcalc/consumption.json
View file
Original file line number Diff line number Diff line change
Expand Up @@ -94,7 +94,7 @@

"_BEN_vet_value": {
"long_name": "Consumption value of veterans benefits",
"description": "Consumption value per dollar of veterans benefits, some of which are in-kind benefits (about 40% are in-kind medical benefits).",
"description": "Consumption value per dollar of veterans benefits, some of which are in-kind benefits (about 40% are in-kind medical benefits and overall about 51% are in-kind benefits).",
"section_1": "",
"section_2": "",
"notes": "",
Expand Down
154 changes: 77 additions & 77 deletions taxcalc/tests/test_utils.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -87,17 +87,17 @@ def test_create_tables(cps_subsample):
tax_to_diff='combined')
assert isinstance(diff, pd.DataFrame)
expected = [0.00,
0.02,
0.58,
0.72,
0.67,
0.78,
0.77,
0.64,
0.56,
0.17,
0.53]
tabcol = 'perc_aftertax'
-0.02,
-0.58,
-0.72,
-0.67,
-0.78,
-0.77,
-0.64,
-0.56,
-0.17,
-0.53]
tabcol = 'pc_aftertaxinc'
if not np.allclose(diff[tabcol].values, expected,
atol=0.005, rtol=0.0, equal_nan=True):
test_failure = True
Expand All @@ -112,19 +112,19 @@ def test_create_tables(cps_subsample):
tax_to_diff='iitax')
assert isinstance(diff, pd.DataFrame)
expected = [0.00,
0.02,
0.58,
0.72,
0.67,
0.78,
0.77,
0.64,
0.56,
0.22,
0.08,
0.06,
0.53]
tabcol = 'perc_aftertax'
-0.02,
-0.58,
-0.72,
-0.67,
-0.78,
-0.77,
-0.64,
-0.56,
-0.22,
-0.08,
-0.06,
-0.53]
tabcol = 'pc_aftertaxinc'
if not np.allclose(diff[tabcol].values, expected,
atol=0.005, rtol=0.0, equal_nan=True):
test_failure = True
Expand All @@ -139,26 +139,26 @@ def test_create_tables(cps_subsample):
tax_to_diff='iitax')
assert isinstance(diff, pd.DataFrame)
expected = [0.00,
0.01,
0.03,
0.24,
0.78,
0.66,
0.76,
0.67,
0.78,
0.77,
0.64,
0.56,
0.22,
0.08,
0.08,
0.07,
0.05,
0.03,
-0.01,
-0.03,
-0.24,
-0.78,
-0.66,
-0.76,
-0.67,
-0.78,
-0.77,
-0.64,
-0.56,
-0.22,
-0.08,
-0.08,
-0.07,
-0.05,
-0.03,
0.00,
0.53]
tabcol = 'perc_aftertax'
-0.53]
tabcol = 'pc_aftertaxinc'
if not np.allclose(diff[tabcol].values, expected,
atol=0.005, rtol=0.0, equal_nan=True):
test_failure = True
Expand All @@ -172,7 +172,8 @@ def test_create_tables(cps_subsample):
income_measure='expanded_income',
tax_to_diff='combined')
assert isinstance(diff, pd.DataFrame)
expected = [171711,
expected = [0,
171711,
15725179,
26767322,
33151429,
Expand All @@ -193,7 +194,8 @@ def test_create_tables(cps_subsample):
print('diff', tabcol)
for val in diff[tabcol].values:
print('{:.0f},'.format(val))
expected = [0.03,
expected = [0.00,
0.03,
2.94,
5.00,
6.20,
Expand All @@ -214,28 +216,30 @@ def test_create_tables(cps_subsample):
print('diff', tabcol)
for val in diff[tabcol].values:
print('{:.2f},'.format(val))
expected = [0.02,
0.63,
0.72,
0.69,
0.77,
0.75,
0.75,
0.62,
0.59,
0.28,
0.53,
0.52,
0.23,
0.06]
tabcol = 'perc_aftertax'
expected = [0.00,
-0.02,
-0.63,
-0.72,
-0.69,
-0.77,
-0.75,
-0.75,
-0.62,
-0.59,
-0.28,
-0.53,
-0.52,
-0.23,
-0.06]
tabcol = 'pc_aftertaxinc'
if not np.allclose(diff[tabcol].values, expected,
atol=0.005, rtol=0.0, equal_nan=True):
test_failure = True
print('diff', tabcol)
for val in diff[tabcol].values:
print('{:.2f},'.format(val))
expected = [-0.02,
expected = [0.00,
-0.02,
-0.63,
-0.72,
-0.69,
Expand Down Expand Up @@ -264,7 +268,8 @@ def test_create_tables(cps_subsample):
income_measure='expanded_income',
result_type='weighted_sum')
assert isinstance(dist, pd.DataFrame)
expected = [-58122959,
expected = [0,
-58122959,
-69644449,
-67116585,
47133880,
Expand All @@ -285,7 +290,8 @@ def test_create_tables(cps_subsample):
print('dist', tabcol)
for val in dist[tabcol].values:
print('{:.0f},'.format(val))
expected = [1202,
expected = [0,
1202,
13625,
22333,
27220,
Expand All @@ -306,7 +312,8 @@ def test_create_tables(cps_subsample):
print('dist', tabcol)
for val in dist[tabcol].values:
print('{:.0f},'.format(val))
expected = [795716514,
expected = [0,
795716514,
2643384899,
3946422611,
5277286335,
Expand All @@ -327,7 +334,8 @@ def test_create_tables(cps_subsample):
print('dist', tabcol)
for val in dist[tabcol].values:
print('{:.0f},'.format(val))
expected = [782122416,
expected = [0,
782122416,
2478134056,
3682019346,
4789142820,
Expand Down Expand Up @@ -707,17 +715,9 @@ def test_add_quantile_bins():
default_labels = set(range(1, 101))
for lab in bin_labels:
assert lab in default_labels
# custom labels
dfb = add_quantile_bins(dfx, 'expanded_income', 100,
weight_by_income_measure=True)
assert 'bins' in dfb
custom_labels = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
dfb = add_quantile_bins(dfx, 'expanded_income', 10,
labels=custom_labels)
assert 'bins' in dfb
bin_labels = dfb['bins'].unique()
for lab in bin_labels:
assert lab in custom_labels


def test_dist_table_sum_row(cps_subsample):
Expand Down Expand Up @@ -988,10 +988,10 @@ def test_dec_qin_graph_plots(cps_subsample):
assert calc1.current_year == calc2.current_year
calc1.calc_all()
calc2.calc_all()
fig_dec = calc1.decile_graph(calc2)
assert fig_dec
fig_qin = calc1.quintile_graph(calc2)
assert fig_qin
fig_dec_hide = calc1.decile_graph(calc2)
assert fig_dec_hide
fig_dec_show = calc1.decile_graph(calc2, hide_negative_incomes=False)
assert fig_dec_show


def test_nonsmall_diffs():
Expand Down
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