UBI_PP = 10000 reform['ubi'] = reform.XTOT * UBI_PP reform['aftertax_income'] = reform.aftertax_income + reform.ubi mdf.add_weighted_metrics(reform, 'aftertax_income') ## Charts ### Change to income percentiles ax = mdf.quantile_chg_plot(base.aftertax_income, reform.aftertax_income, base.XTOT_m, reform.XTOT_m) plt.show() ### Percent change to income percentiles mdf.quantile_pct_chg_plot(base.aftertax_income, reform.aftertax_income, base.XTOT_m, reform.XTOT_m) plt.show() Make the title and labels more descriptive to this data. mdf.quantile_pct_chg_plot(base.aftertax_income, reform.aftertax_income, base.XTOT_m, reform.XTOT_m) # Note: Must set `loc='left'`, otherwise two titles will overlap. plt.title('Change to disposable income percentiles', loc='left') plt.xlabel('Disposable income percentile') plt.ylabel('Change to disposable income at the percentile boundary') plt.show() ### Other percentiles and labels mdf.quantile_chg_plot(base.aftertax_income, reform.aftertax_income,
def test_quantile_pct_chg_plot(): mdf.quantile_pct_chg_plot(DF1, DF2, 'v', 'w', 'v', 'w')
def test_quantile_pct_chg_plot(): mdf.quantile_pct_chg_plot(DF1, DF2, "v", "w", "v", "w")
), loc="left", y=1.05, fontsize=24, ) return ax ax = dist_plot("ei_bin", "pct_chg_bin", "household_weight") plt.show() # Reform 1 Quantile % change to disposable income mdf.quantile_pct_chg_plot( df1=df, df2=df, col1="baseline_equiv_household_net_income_bhc", col2="reform_1_equiv_household_net_income_bhc", w1="household_weight", w2="household_weight", ) # Note: Must set `loc='left'`, otherwise two titles will overlap. plt.title("Reform 1: Change to disposable income percentiles", loc="left") plt.xlabel("Disposable income percentile") plt.ylabel("Change to disposable income at the percentile boundary") plt.show() # Reform 2 Quantile % change to disposable income mdf.quantile_pct_chg_plot( df1=df, df2=df, col1="baseline_equiv_household_net_income_bhc",
def test_quantile_pct_chg_plot(): mdf.quantile_pct_chg_plot(v1=V1, v2=V2, w1=W1, w2=W2)