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demoday.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# TaxBrain Python Demo Day"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# define reforms\n",
"iit_rate_json = \"\"\"{\n",
" \"II_brk5\": {\"2021\": [400000.0, 400000.0, 200000.0, 400000.0, 400000.0],\n",
" \"2026\": [482682.0, 482682.0, 241341.0, 482682.0, 482682.0]},\n",
" \"II_rt6\": {\"2021\": 0.33, \"2026\": 0.35},\n",
" \"II_brk6\": {\"2021\": [416700.0, 416700.0, 208350.0, 416700.0, 416700.0],\n",
" \"2026\": [484651.0, 545233.0, 272616.0, 514942.0, 545233.0]},\n",
" \"II_rt7\": {\"2021\": 0.35, \"2026\": 0.396},\n",
" \"II_brk7\": {\"2021\": [418400.0, 470700.0, 235350.0, 444550.0, 470700.0],\n",
" \"2026\": [9e99, 9e99, 9e99, 9e99, 9e99]},\n",
" \"II_rt8\": {\"2021\":0.396, \"2026\": 1.0},\n",
" \"PT_brk5\": {\"2021\": [400000.0, 400000.0, 200000.0, 400000.0, 400000.0],\n",
" \"2026\": [482682.0, 482682.0, 241341.0, 482682.0, 482682.0]},\n",
" \"PT_rt6\": {\"2021\": 0.33, \"2026\": 0.35},\n",
" \"PT_brk6\": {\"2021\": [416700.0, 416700.0, 208350.0, 416700.0, 416700.0],\n",
" \"2026\": [484651.0, 545233.0, 272616.0, 514942.0, 545233.0]},\n",
" \"PT_rt7\": {\"2021\": 0.35, \"2026\": 0.396},\n",
" \"PT_brk7\": {\"2021\": [418400.0, 470700.0, 235350.0, 444550.0, 470700.0],\n",
" \"2026\": [9e99, 9e99, 9e99, 9e99, 9e99]},\n",
" \"PT_rt8\": {\"2021\":0.396, \"2026\": 1.0}\n",
"}\"\"\"\n",
"qbid_json = \"\"\"{\n",
" \"PT_qbid_ps\": {\"2021\": [400000.00, 400000.00, 400000.00, 400000.00, 400000.00],\n",
" \"2026\": [0.0, 0.0, 0.0, 0.0, 0.0]},\n",
" \"PT_qbid_prt\": {\"2021\": 1.0},\n",
" \"PT_qbid_limit_switch\": {\"2021\": false}\n",
"}\"\"\"\n",
"payroll_json = \"\"\"{\"SS_Earnings_thd\": {\"2021\": 400000}}\"\"\"\n",
"CG_rate_json = \"\"\"{\n",
" \"CG_brk3\": {\"2021\": [1000000, 1000000, 1000000, 1000000, 1000000]},\n",
" \"CG_rt4\": {\"2021\": 0.396}\n",
"}\"\"\"\n",
"ded_limits_json = \"\"\"{\n",
" \"ID_ps\": {\"2021\": [400000.0,400000.0,200000.0,400000.0,400000.0],\n",
" \"2026\": [302907.0, 363489.0, 181744.0, 333198.0, 363489.0]},\n",
" \"ID_prt\": {\"2021\": 0.03},\n",
" \"ID_crt\": {\"2021\": 0.8},\n",
" \"ID_AllTaxes_c\": {\"2021\": [9e+99, 9e+99, 9e+99, 9e+99, 9e+99]},\n",
" \"ID_BenefitSurtax_trt\": {\"2021\": 1.0},\n",
" \"ID_BenefitSurtax_crt\": {\"2021\": 0.28},\n",
" \"ID_BenefitSurtax_Switch\": {\"2021\": [true, true, false, true, true, true, true]}\n",
"}\"\"\"\n",
"eitc_json = \"\"\"{\"EITC_MaxEligAge\": {\"2021\": 125}}\"\"\"\n",
"\n",
"retire_json = \"\"\"{ \n",
" \"ALD_IRAContributions_hc\": {\"2021\": 1.0},\n",
" \"ALD_KEOGH_SEP_hc\": {\"2021\": 1.0}\n",
"}\"\"\"\n",
"energy_credit = \"\"\"{\"CR_ResidentialEnergy_hc\": {\"2021\": 0.0}}\"\"\"\n",
"\n",
"dict_of_provisions = {\n",
" 'Repeal TCJA Rate Cuts': iit_rate_json,\n",
" 'Repeal QBID': qbid_json,\n",
" 'Apply payroll taxes on earnings above $400,000': payroll_json,\n",
" 'Increase rates on capital gain for high income filers': CG_rate_json,\n",
" 'Limit certain itemized deductions': ded_limits_json,\n",
" 'Expand EITC eligibility above age 64': eitc_json,\n",
" 'Changes to IRA and KEOGH plans': retire_json,\n",
" 'Residential energy credit': energy_credit}"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from taxbrain import TaxBrain, report\n",
"from taxbrain.utils import (volcano_plot, lorenz_curve, revenue_plot,\n",
" distribution_plot, differences_plot)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"tb = TaxBrain(2021, 2030, reform=dict_of_provisions, stacked=True, use_cps=True)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"tb.run()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\u001b[0;31mInit signature:\u001b[0m\n",
"\u001b[0mTaxBrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0mstart_year\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0mend_year\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mint\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m2030\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0mmicrodata\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mUnion\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0muse_cps\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0mreform\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mUnion\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0mbehavior\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mdict\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0massump\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0mbase_policy\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mUnion\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m \u001b[0mstacked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
"\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mDocstring:\u001b[0m <no docstring>\n",
"\u001b[0;31mInit docstring:\u001b[0m\n",
"Constructor for the TaxBrain class\n",
"\n",
"Parameters\n",
"----------\n",
"start_year: int\n",
" First year in the analysis. Must be no earlier than the\n",
" first year allowed in Tax-Calculator.\n",
"end_year: int\n",
" Last year in the analysis. Must be no later than the last\n",
" year allowed in Tax-Calculator.\n",
"microdata: str or Pandas DataFrame\n",
" Either a path to a micro-data file or a Pandas DataFrame\n",
" containing micro-data.\n",
"use_cps: bool\n",
" A boolean value to indicate whether or not the analysis should\n",
" be run using the CPS file included in Tax-Calculator.\n",
" Note: use_cps cannot be True if a file was also specified with\n",
" the microdata parameter.\n",
"reform: str or dict\n",
" Individual income tax policy reform. Can be either a string\n",
" pointing to a JSON reform file, or the contents of a JSON file,\n",
" or a properly formatted JSON file.\n",
"behavior: dict\n",
" Individual behavior assumptions use by the Behavior-Response\n",
" package.\n",
"assump: str\n",
" A string pointing to a JSON file containing user specified\n",
" economic assumptions.\n",
"base_policy: str or dict\n",
" Individual income tax policy to use as the baseline for\n",
" the analysis. This policy will be implemented in the base\n",
" calculator instance as well as the reform Calculator\n",
" before the user provided reform is implemented. Can either\n",
" be a string pointing to a JSON reform file, the contents\n",
" of a JSON file, or a properly formatted dictionary.\n",
"verbose: bool\n",
" A boolean value indicated whether or not to write model\n",
" progress reports.\n",
"stacked: bool\n",
" A boolean value indicating wheather the provided reform is in the\n",
" format used for stacked reform analysis\n",
"\n",
"Returns\n",
"-------\n",
"None\n",
"\u001b[0;31mFile:\u001b[0m ~/Tax-Brain/taxbrain/taxbrain.py\n",
"\u001b[0;31mType:\u001b[0m type\n",
"\u001b[0;31mSubclasses:\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"TaxBrain?"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>count</th>\n",
" <th>c00100</th>\n",
" <th>count_StandardDed</th>\n",
" <th>standard</th>\n",
" <th>count_ItemDed</th>\n",
" <th>c04470</th>\n",
" <th>c04600</th>\n",
" <th>c04800</th>\n",
" <th>taxbc</th>\n",
" <th>c62100</th>\n",
" <th>...</th>\n",
" <th>othertaxes</th>\n",
" <th>refund</th>\n",
" <th>iitax</th>\n",
" <th>payrolltax</th>\n",
" <th>combined</th>\n",
" <th>ubi</th>\n",
" <th>benefit_cost_total</th>\n",
" <th>benefit_value_total</th>\n",
" <th>expanded_income</th>\n",
" <th>aftertax_income</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0-10n</th>\n",
" <td>0.118482</td>\n",
" <td>-10.838082</td>\n",
" <td>0.118482</td>\n",
" <td>2.051739</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-10.838082</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>3.034663</td>\n",
" <td>0.052946</td>\n",
" <td>3.087609</td>\n",
" <td>0.0</td>\n",
" <td>0.734674</td>\n",
" <td>0.734674</td>\n",
" <td>-10.099247</td>\n",
" <td>-13.186856</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0-10z</th>\n",
" <td>8.899731</td>\n",
" <td>-0.097303</td>\n",
" <td>8.899731</td>\n",
" <td>136.025749</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.097303</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.027245</td>\n",
" <td>0.000000</td>\n",
" <td>0.027245</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.027245</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0-10p</th>\n",
" <td>12.879608</td>\n",
" <td>28.358837</td>\n",
" <td>12.829139</td>\n",
" <td>201.243503</td>\n",
" <td>0.049951</td>\n",
" <td>0.142807</td>\n",
" <td>0.0</td>\n",
" <td>0.195581</td>\n",
" <td>0.012364</td>\n",
" <td>28.235885</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>0.858970</td>\n",
" <td>-0.762970</td>\n",
" <td>3.284062</td>\n",
" <td>2.521092</td>\n",
" <td>0.0</td>\n",
" <td>21.504754</td>\n",
" <td>21.504754</td>\n",
" <td>50.917029</td>\n",
" <td>48.395937</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10-20</th>\n",
" <td>21.897844</td>\n",
" <td>220.919768</td>\n",
" <td>21.328227</td>\n",
" <td>321.206999</td>\n",
" <td>0.569617</td>\n",
" <td>8.817800</td>\n",
" <td>0.0</td>\n",
" <td>23.369588</td>\n",
" <td>2.164673</td>\n",
" <td>212.914754</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>10.919807</td>\n",
" <td>-8.700111</td>\n",
" <td>29.979519</td>\n",
" <td>21.279408</td>\n",
" <td>0.0</td>\n",
" <td>110.590079</td>\n",
" <td>110.590079</td>\n",
" <td>345.598949</td>\n",
" <td>324.319541</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20-30</th>\n",
" <td>21.895494</td>\n",
" <td>386.740715</td>\n",
" <td>20.641372</td>\n",
" <td>341.963497</td>\n",
" <td>1.254122</td>\n",
" <td>22.645155</td>\n",
" <td>0.0</td>\n",
" <td>147.638144</td>\n",
" <td>14.907157</td>\n",
" <td>366.759006</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>17.215700</td>\n",
" <td>-3.461963</td>\n",
" <td>54.792825</td>\n",
" <td>51.330861</td>\n",
" <td>0.0</td>\n",
" <td>249.449473</td>\n",
" <td>249.449473</td>\n",
" <td>666.084834</td>\n",
" <td>614.753973</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30-40</th>\n",
" <td>21.900754</td>\n",
" <td>434.643629</td>\n",
" <td>20.470455</td>\n",
" <td>387.634643</td>\n",
" <td>1.429612</td>\n",
" <td>27.352031</td>\n",
" <td>0.0</td>\n",
" <td>215.120705</td>\n",
" <td>22.784529</td>\n",
" <td>411.482899</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>13.129981</td>\n",
" <td>6.675016</td>\n",
" <td>60.651737</td>\n",
" <td>67.326753</td>\n",
" <td>0.0</td>\n",
" <td>434.614029</td>\n",
" <td>434.614029</td>\n",
" <td>905.336763</td>\n",
" <td>838.010010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40-50</th>\n",
" <td>21.898575</td>\n",
" <td>576.578474</td>\n",
" <td>19.899362</td>\n",
" <td>385.892052</td>\n",
" <td>1.999213</td>\n",
" <td>39.809258</td>\n",
" <td>0.0</td>\n",
" <td>309.902460</td>\n",
" <td>33.604745</td>\n",
" <td>543.984393</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>12.059958</td>\n",
" <td>15.983914</td>\n",
" <td>77.118905</td>\n",
" <td>93.102819</td>\n",
" <td>0.0</td>\n",
" <td>508.057680</td>\n",
" <td>508.057680</td>\n",
" <td>1133.916321</td>\n",
" <td>1040.813501</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50-60</th>\n",
" <td>21.897641</td>\n",
" <td>791.857075</td>\n",
" <td>19.041281</td>\n",
" <td>382.308407</td>\n",
" <td>2.856360</td>\n",
" <td>59.080303</td>\n",
" <td>0.0</td>\n",
" <td>457.881130</td>\n",
" <td>51.880720</td>\n",
" <td>744.978671</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>12.968392</td>\n",
" <td>30.116200</td>\n",
" <td>102.201503</td>\n",
" <td>132.317703</td>\n",
" <td>0.0</td>\n",
" <td>572.105281</td>\n",
" <td>572.105281</td>\n",
" <td>1418.747211</td>\n",
" <td>1286.429507</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60-70</th>\n",
" <td>21.895865</td>\n",
" <td>1064.339576</td>\n",
" <td>18.456728</td>\n",
" <td>400.348770</td>\n",
" <td>3.439136</td>\n",
" <td>75.558292</td>\n",
" <td>0.0</td>\n",
" <td>681.991459</td>\n",
" <td>83.792209</td>\n",
" <td>1006.434209</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>14.377419</td>\n",
" <td>56.494989</td>\n",
" <td>132.286583</td>\n",
" <td>188.781572</td>\n",
" <td>0.0</td>\n",
" <td>686.730255</td>\n",
" <td>686.730255</td>\n",
" <td>1793.099707</td>\n",
" <td>1604.318135</td>\n",
" </tr>\n",
" <tr>\n",
" <th>70-80</th>\n",
" <td>21.901060</td>\n",
" <td>1475.963134</td>\n",
" <td>17.350656</td>\n",
" <td>411.974372</td>\n",
" <td>4.550404</td>\n",
" <td>112.773848</td>\n",
" <td>0.0</td>\n",
" <td>1026.954334</td>\n",
" <td>134.064369</td>\n",
" <td>1392.281613</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>12.419573</td>\n",
" <td>103.541186</td>\n",
" <td>177.375772</td>\n",
" <td>280.916958</td>\n",
" <td>0.0</td>\n",
" <td>817.415142</td>\n",
" <td>817.415142</td>\n",
" <td>2323.144844</td>\n",
" <td>2042.227886</td>\n",
" </tr>\n",
" <tr>\n",
" <th>80-90</th>\n",
" <td>21.898049</td>\n",
" <td>2302.263423</td>\n",
" <td>14.900410</td>\n",
" <td>378.925933</td>\n",
" <td>6.997639</td>\n",
" <td>209.232870</td>\n",
" <td>0.0</td>\n",
" <td>1738.716930</td>\n",
" <td>244.624805</td>\n",
" <td>2151.140688</td>\n",
" <td>...</td>\n",
" <td>0.000000</td>\n",
" <td>7.204477</td>\n",
" <td>211.866523</td>\n",
" <td>266.873621</td>\n",
" <td>478.740144</td>\n",
" <td>0.0</td>\n",
" <td>840.132935</td>\n",
" <td>840.132935</td>\n",
" <td>3165.507978</td>\n",
" <td>2686.767834</td>\n",
" </tr>\n",
" <tr>\n",
" <th>90-100</th>\n",
" <td>21.898826</td>\n",
" <td>6711.871844</td>\n",
" <td>8.643838</td>\n",
" <td>230.545962</td>\n",
" <td>13.254988</td>\n",
" <td>569.836530</td>\n",
" <td>0.0</td>\n",
" <td>5888.726938</td>\n",
" <td>1342.588350</td>\n",
" <td>6372.715816</td>\n",
" <td>...</td>\n",
" <td>16.010641</td>\n",
" <td>1.663627</td>\n",
" <td>1330.769875</td>\n",
" <td>627.020923</td>\n",
" <td>1957.790798</td>\n",
" <td>0.0</td>\n",
" <td>687.880791</td>\n",
" <td>687.880791</td>\n",
" <td>7544.543273</td>\n",
" <td>5586.752475</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALL</th>\n",
" <td>218.981928</td>\n",
" <td>13982.601088</td>\n",
" <td>182.579680</td>\n",
" <td>3580.121626</td>\n",
" <td>36.401042</td>\n",
" <td>1125.248894</td>\n",
" <td>0.0</td>\n",
" <td>10490.497270</td>\n",
" <td>1930.423921</td>\n",
" <td>13219.992548</td>\n",
" <td>...</td>\n",
" <td>16.010641</td>\n",
" <td>102.817904</td>\n",
" <td>1745.584566</td>\n",
" <td>1531.638397</td>\n",
" <td>3277.222963</td>\n",
" <td>0.0</td>\n",
" <td>4929.215093</td>\n",
" <td>4929.215093</td>\n",
" <td>19336.797662</td>\n",
" <td>16059.574699</td>\n",
" </tr>\n",
" <tr>\n",
" <th>90-95</th>\n",
" <td>10.948697</td>\n",
" <td>1805.654788</td>\n",
" <td>5.653266</td>\n",
" <td>149.998753</td>\n",
" <td>5.295431</td>\n",
" <td>181.211514</td>\n",
" <td>0.0</td>\n",
" <td>1471.964167</td>\n",
" <td>236.593179</td>\n",
" <td>1684.882842</td>\n",
" <td>...</td>\n",
" <td>0.042038</td>\n",
" <td>1.394090</td>\n",
" <td>219.980284</td>\n",
" <td>194.619732</td>\n",
" <td>414.600016</td>\n",
" <td>0.0</td>\n",
" <td>401.028380</td>\n",
" <td>401.028380</td>\n",
" <td>2229.843259</td>\n",
" <td>1815.243243</td>\n",
" </tr>\n",
" <tr>\n",
" <th>95-99</th>\n",
" <td>8.759570</td>\n",
" <td>2534.498524</td>\n",
" <td>2.599590</td>\n",
" <td>70.482909</td>\n",
" <td>6.159980</td>\n",
" <td>261.363170</td>\n",
" <td>0.0</td>\n",
" <td>2183.678523</td>\n",
" <td>418.466239</td>\n",
" <td>2380.649835</td>\n",
" <td>...</td>\n",
" <td>1.486253</td>\n",
" <td>0.269536</td>\n",
" <td>408.638973</td>\n",
" <td>232.201912</td>\n",
" <td>640.840885</td>\n",
" <td>0.0</td>\n",
" <td>247.713784</td>\n",
" <td>247.713784</td>\n",
" <td>2859.036040</td>\n",
" <td>2218.195155</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Top 1%</th>\n",
" <td>2.190559</td>\n",
" <td>2371.718532</td>\n",
" <td>0.390982</td>\n",
" <td>10.064300</td>\n",
" <td>1.799577</td>\n",
" <td>127.261846</td>\n",
" <td>0.0</td>\n",
" <td>2233.084248</td>\n",
" <td>687.528931</td>\n",
" <td>2307.183140</td>\n",
" <td>...</td>\n",
" <td>14.482350</td>\n",
" <td>0.000000</td>\n",
" <td>702.150618</td>\n",
" <td>200.199280</td>\n",
" <td>902.349898</td>\n",
" <td>0.0</td>\n",
" <td>39.138627</td>\n",
" <td>39.138627</td>\n",
" <td>2455.663974</td>\n",
" <td>1553.314077</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>16 rows × 24 columns</p>\n",
"</div>"
],
"text/plain": [
" count c00100 count_StandardDed standard \\\n",
"0-10n 0.118482 -10.838082 0.118482 2.051739 \n",
"0-10z 8.899731 -0.097303 8.899731 136.025749 \n",
"0-10p 12.879608 28.358837 12.829139 201.243503 \n",
"10-20 21.897844 220.919768 21.328227 321.206999 \n",
"20-30 21.895494 386.740715 20.641372 341.963497 \n",
"30-40 21.900754 434.643629 20.470455 387.634643 \n",
"40-50 21.898575 576.578474 19.899362 385.892052 \n",
"50-60 21.897641 791.857075 19.041281 382.308407 \n",
"60-70 21.895865 1064.339576 18.456728 400.348770 \n",
"70-80 21.901060 1475.963134 17.350656 411.974372 \n",
"80-90 21.898049 2302.263423 14.900410 378.925933 \n",
"90-100 21.898826 6711.871844 8.643838 230.545962 \n",
"ALL 218.981928 13982.601088 182.579680 3580.121626 \n",
"90-95 10.948697 1805.654788 5.653266 149.998753 \n",
"95-99 8.759570 2534.498524 2.599590 70.482909 \n",
"Top 1% 2.190559 2371.718532 0.390982 10.064300 \n",
"\n",
" count_ItemDed c04470 c04600 c04800 taxbc \\\n",
"0-10n 0.000000 0.000000 0.0 0.000000 0.000000 \n",
"0-10z 0.000000 0.000000 0.0 0.000000 0.000000 \n",
"0-10p 0.049951 0.142807 0.0 0.195581 0.012364 \n",
"10-20 0.569617 8.817800 0.0 23.369588 2.164673 \n",
"20-30 1.254122 22.645155 0.0 147.638144 14.907157 \n",
"30-40 1.429612 27.352031 0.0 215.120705 22.784529 \n",
"40-50 1.999213 39.809258 0.0 309.902460 33.604745 \n",
"50-60 2.856360 59.080303 0.0 457.881130 51.880720 \n",
"60-70 3.439136 75.558292 0.0 681.991459 83.792209 \n",
"70-80 4.550404 112.773848 0.0 1026.954334 134.064369 \n",
"80-90 6.997639 209.232870 0.0 1738.716930 244.624805 \n",
"90-100 13.254988 569.836530 0.0 5888.726938 1342.588350 \n",
"ALL 36.401042 1125.248894 0.0 10490.497270 1930.423921 \n",
"90-95 5.295431 181.211514 0.0 1471.964167 236.593179 \n",
"95-99 6.159980 261.363170 0.0 2183.678523 418.466239 \n",
"Top 1% 1.799577 127.261846 0.0 2233.084248 687.528931 \n",
"\n",
" c62100 ... othertaxes refund iitax payrolltax \\\n",
"0-10n -10.838082 ... 0.000000 0.000000 3.034663 0.052946 \n",
"0-10z -0.097303 ... 0.000000 0.000000 0.027245 0.000000 \n",
"0-10p 28.235885 ... 0.000000 0.858970 -0.762970 3.284062 \n",
"10-20 212.914754 ... 0.000000 10.919807 -8.700111 29.979519 \n",
"20-30 366.759006 ... 0.000000 17.215700 -3.461963 54.792825 \n",
"30-40 411.482899 ... 0.000000 13.129981 6.675016 60.651737 \n",
"40-50 543.984393 ... 0.000000 12.059958 15.983914 77.118905 \n",
"50-60 744.978671 ... 0.000000 12.968392 30.116200 102.201503 \n",
"60-70 1006.434209 ... 0.000000 14.377419 56.494989 132.286583 \n",
"70-80 1392.281613 ... 0.000000 12.419573 103.541186 177.375772 \n",
"80-90 2151.140688 ... 0.000000 7.204477 211.866523 266.873621 \n",
"90-100 6372.715816 ... 16.010641 1.663627 1330.769875 627.020923 \n",
"ALL 13219.992548 ... 16.010641 102.817904 1745.584566 1531.638397 \n",
"90-95 1684.882842 ... 0.042038 1.394090 219.980284 194.619732 \n",
"95-99 2380.649835 ... 1.486253 0.269536 408.638973 232.201912 \n",
"Top 1% 2307.183140 ... 14.482350 0.000000 702.150618 200.199280 \n",
"\n",
" combined ubi benefit_cost_total benefit_value_total \\\n",
"0-10n 3.087609 0.0 0.734674 0.734674 \n",
"0-10z 0.027245 0.0 0.000000 0.000000 \n",
"0-10p 2.521092 0.0 21.504754 21.504754 \n",
"10-20 21.279408 0.0 110.590079 110.590079 \n",
"20-30 51.330861 0.0 249.449473 249.449473 \n",
"30-40 67.326753 0.0 434.614029 434.614029 \n",
"40-50 93.102819 0.0 508.057680 508.057680 \n",
"50-60 132.317703 0.0 572.105281 572.105281 \n",
"60-70 188.781572 0.0 686.730255 686.730255 \n",
"70-80 280.916958 0.0 817.415142 817.415142 \n",
"80-90 478.740144 0.0 840.132935 840.132935 \n",
"90-100 1957.790798 0.0 687.880791 687.880791 \n",
"ALL 3277.222963 0.0 4929.215093 4929.215093 \n",
"90-95 414.600016 0.0 401.028380 401.028380 \n",
"95-99 640.840885 0.0 247.713784 247.713784 \n",
"Top 1% 902.349898 0.0 39.138627 39.138627 \n",
"\n",
" expanded_income aftertax_income \n",
"0-10n -10.099247 -13.186856 \n",
"0-10z 0.000000 -0.027245 \n",
"0-10p 50.917029 48.395937 \n",
"10-20 345.598949 324.319541 \n",
"20-30 666.084834 614.753973 \n",
"30-40 905.336763 838.010010 \n",
"40-50 1133.916321 1040.813501 \n",
"50-60 1418.747211 1286.429507 \n",
"60-70 1793.099707 1604.318135 \n",
"70-80 2323.144844 2042.227886 \n",
"80-90 3165.507978 2686.767834 \n",
"90-100 7544.543273 5586.752475 \n",
"ALL 19336.797662 16059.574699 \n",
"90-95 2229.843259 1815.243243 \n",
"95-99 2859.036040 2218.195155 \n",
"Top 1% 2455.663974 1553.314077 \n",
"\n",
"[16 rows x 24 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tb.distribution_table(2025, 'weighted_deciles', income_measure='expanded_income', calc='reform')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>2021</th>\n",
" <th>2022</th>\n",
" <th>2023</th>\n",
" <th>2024</th>\n",
" <th>2025</th>\n",
" <th>2026</th>\n",
" <th>2027</th>\n",
" <th>2028</th>\n",
" <th>2029</th>\n",
" <th>2030</th>\n",
" <th>Total</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Base</th>\n",
" <td>2.571828e+12</td>\n",
" <td>2.715400e+12</td>\n",
" <td>2.846491e+12</td>\n",
" <td>2.990706e+12</td>\n",
" <td>3.151490e+12</td>\n",
" <td>3.537569e+12</td>\n",
" <td>3.728943e+12</td>\n",
" <td>3.912164e+12</td>\n",
" <td>4.090795e+12</td>\n",
" <td>4.268168e+12</td>\n",
" <td>3.381356e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Reform</th>\n",
" <td>2.669995e+12</td>\n",
" <td>2.820909e+12</td>\n",
" <td>2.956879e+12</td>\n",
" <td>3.108171e+12</td>\n",
" <td>3.277223e+12</td>\n",
" <td>3.683130e+12</td>\n",
" <td>3.885423e+12</td>\n",
" <td>4.077311e+12</td>\n",
" <td>4.266392e+12</td>\n",
" <td>4.453768e+12</td>\n",
" <td>3.519920e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Difference</th>\n",
" <td>9.816664e+10</td>\n",
" <td>1.055090e+11</td>\n",
" <td>1.103875e+11</td>\n",
" <td>1.174644e+11</td>\n",
" <td>1.257325e+11</td>\n",
" <td>1.455613e+11</td>\n",
" <td>1.564804e+11</td>\n",
" <td>1.651463e+11</td>\n",
" <td>1.755966e+11</td>\n",
" <td>1.856001e+11</td>\n",
" <td>1.385645e+12</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 2021 2022 2023 2024 \\\n",
"Base 2.571828e+12 2.715400e+12 2.846491e+12 2.990706e+12 \n",
"Reform 2.669995e+12 2.820909e+12 2.956879e+12 3.108171e+12 \n",
"Difference 9.816664e+10 1.055090e+11 1.103875e+11 1.174644e+11 \n",
"\n",
" 2025 2026 2027 2028 \\\n",
"Base 3.151490e+12 3.537569e+12 3.728943e+12 3.912164e+12 \n",
"Reform 3.277223e+12 3.683130e+12 3.885423e+12 4.077311e+12 \n",
"Difference 1.257325e+11 1.455613e+11 1.564804e+11 1.651463e+11 \n",
"\n",
" 2029 2030 Total \n",
"Base 4.090795e+12 4.268168e+12 3.381356e+13 \n",
"Reform 4.266392e+12 4.453768e+12 3.519920e+13 \n",
"Difference 1.755966e+11 1.856001e+11 1.385645e+12 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tb.weighted_totals('combined', include_total=True)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>2021</th>\n",
" <th>2022</th>\n",
" <th>2023</th>\n",
" <th>2024</th>\n",
" <th>2025</th>\n",
" <th>2026</th>\n",
" <th>2027</th>\n",
" <th>2028</th>\n",
" <th>2029</th>\n",
" <th>2030</th>\n",
" <th>Total</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>iitax</th>\n",
" <td>1.387127e+12</td>\n",
" <td>1.478811e+12</td>\n",
" <td>1.556443e+12</td>\n",
" <td>1.645171e+12</td>\n",
" <td>1.745585e+12</td>\n",
" <td>2.077558e+12</td>\n",
" <td>2.202374e+12</td>\n",
" <td>2.317601e+12</td>\n",
" <td>2.433904e+12</td>\n",
" <td>2.548467e+12</td>\n",
" <td>1.939304e+13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>combined</th>\n",
" <td>2.669995e+12</td>\n",
" <td>2.820909e+12</td>\n",
" <td>2.956879e+12</td>\n",
" <td>3.108171e+12</td>\n",
" <td>3.277223e+12</td>\n",
" <td>3.683130e+12</td>\n",
" <td>3.885423e+12</td>\n",
" <td>4.077311e+12</td>\n",
" <td>4.266392e+12</td>\n",
" <td>4.453768e+12</td>\n",
" <td>3.519920e+13</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 2021 2022 2023 2024 \\\n",
"iitax 1.387127e+12 1.478811e+12 1.556443e+12 1.645171e+12 \n",
"combined 2.669995e+12 2.820909e+12 2.956879e+12 3.108171e+12 \n",
"\n",
" 2025 2026 2027 2028 \\\n",
"iitax 1.745585e+12 2.077558e+12 2.202374e+12 2.317601e+12 \n",
"combined 3.277223e+12 3.683130e+12 3.885423e+12 4.077311e+12 \n",
"\n",
" 2029 2030 Total \n",
"iitax 2.433904e+12 2.548467e+12 1.939304e+13 \n",
"combined 4.266392e+12 4.453768e+12 3.519920e+13 "
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tb.multi_var_table(['iitax', 'combined'], calc='reform', include_total=True)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>count</th>\n",
" <th>tax_cut</th>\n",
" <th>perc_cut</th>\n",
" <th>tax_inc</th>\n",
" <th>perc_inc</th>\n",
" <th>mean</th>\n",
" <th>tot_change</th>\n",
" <th>share_of_change</th>\n",
" <th>ubi</th>\n",
" <th>benefit_cost_total</th>\n",
" <th>benefit_value_total</th>\n",
" <th>pc_aftertaxinc</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0-10n</th>\n",
" <td>0.127360</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.127360</td>\n",
" <td>100.000000</td>\n",
" <td>28548.425175</td>\n",
" <td>3.635925</td>\n",
" <td>2.070613</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>29.877067</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0-10z</th>\n",
" <td>9.317286</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.229518</td>\n",
" <td>2.463352</td>\n",
" <td>3.359134</td>\n",
" <td>0.031298</td>\n",
" <td>0.017824</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0-10p</th>\n",
" <td>13.516065</td>\n",
" <td>0.047737</td>\n",
" <td>0.353191</td>\n",
" <td>0.195589</td>\n",
" <td>1.447086</td>\n",
" <td>5.012975</td>\n",
" <td>0.067756</td>\n",
" <td>0.038586</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.118762</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10-20</th>\n",
" <td>22.967251</td>\n",
" <td>0.110719</td>\n",
" <td>0.482074</td>\n",
" <td>0.327151</td>\n",
" <td>1.424424</td>\n",
" <td>2.891639</td>\n",
" <td>0.066413</td>\n",
" <td>0.037821</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.017193</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20-30</th>\n",
" <td>22.963506</td>\n",
" <td>0.028243</td>\n",
" <td>0.122991</td>\n",
" <td>0.866300</td>\n",
" <td>3.772507</td>\n",
" <td>15.196724</td>\n",
" <td>0.348970</td>\n",
" <td>0.198734</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.047757</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30-40</th>\n",
" <td>22.965008</td>\n",
" <td>0.188819</td>\n",
" <td>0.822205</td>\n",
" <td>1.241304</td>\n",
" <td>5.405198</td>\n",
" <td>19.764185</td>\n",
" <td>0.453885</td>\n",
" <td>0.258482</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.045805</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40-50</th>\n",
" <td>22.963626</td>\n",
" <td>0.265455</td>\n",
" <td>1.155982</td>\n",
" <td>0.893003</td>\n",
" <td>3.888772</td>\n",
" <td>19.371119</td>\n",
" <td>0.444831</td>\n",
" <td>0.253326</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.036277</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50-60</th>\n",
" <td>22.963783</td>\n",
" <td>0.102927</td>\n",
" <td>0.448213</td>\n",
" <td>0.792758</td>\n",
" <td>3.452209</td>\n",
" <td>25.943654</td>\n",
" <td>0.595764</td>\n",
" <td>0.339280</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.039489</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60-70</th>\n",
" <td>22.963858</td>\n",
" <td>0.075591</td>\n",
" <td>0.329172</td>\n",
" <td>0.922169</td>\n",
" <td>4.015742</td>\n",
" <td>41.900316</td>\n",
" <td>0.962193</td>\n",
" <td>0.547957</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.051233</td>\n",
" </tr>\n",
" <tr>\n",
" <th>70-80</th>\n",
" <td>22.963832</td>\n",
" <td>0.116813</td>\n",
" <td>0.508682</td>\n",
" <td>0.773757</td>\n",
" <td>3.369461</td>\n",
" <td>53.408915</td>\n",
" <td>1.226473</td>\n",
" <td>0.698461</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.051305</td>\n",
" </tr>\n",
" <tr>\n",
" <th>80-90</th>\n",
" <td>22.965928</td>\n",
" <td>0.026866</td>\n",
" <td>0.116984</td>\n",
" <td>0.980743</td>\n",
" <td>4.270425</td>\n",
" <td>124.597783</td>\n",
" <td>2.861504</td>\n",
" <td>1.629590</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.091139</td>\n",
" </tr>\n",
" <tr>\n",
" <th>90-100</th>\n",
" <td>22.964168</td>\n",
" <td>0.000164</td>\n",
" <td>0.000716</td>\n",
" <td>3.894890</td>\n",
" <td>16.960726</td>\n",
" <td>7180.819580</td>\n",
" <td>164.901550</td>\n",
" <td>93.909327</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-2.481368</td>\n",
" </tr>\n",
" <tr>\n",
" <th>ALL</th>\n",
" <td>229.641673</td>\n",
" <td>0.963335</td>\n",
" <td>0.419495</td>\n",
" <td>11.244542</td>\n",
" <td>4.896560</td>\n",
" <td>764.654602</td>\n",
" <td>175.596562</td>\n",
" <td>100.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.927041</td>\n",
" </tr>\n",
" <tr>\n",
" <th>90-95</th>\n",
" <td>11.481263</td>\n",
" <td>0.000164</td>\n",
" <td>0.001431</td>\n",
" <td>0.748162</td>\n",
" <td>6.516377</td>\n",
" <td>247.893906</td>\n",
" <td>2.846135</td>\n",
" <td>1.620838</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.134523</td>\n",
" </tr>\n",
" <tr>\n",
" <th>95-99</th>\n",
" <td>9.185571</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.370969</td>\n",
" <td>14.925250</td>\n",
" <td>996.222892</td>\n",
" <td>9.150876</td>\n",
" <td>5.211307</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.357924</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Top 1%</th>\n",
" <td>2.297334</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.775758</td>\n",
" <td>77.296450</td>\n",
" <td>66557.369070</td>\n",
" <td>152.904539</td>\n",
" <td>87.077182</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-7.749033</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" count tax_cut perc_cut tax_inc perc_inc mean \\\n",
"0-10n 0.127360 0.000000 0.000000 0.127360 100.000000 28548.425175 \n",
"0-10z 9.317286 0.000000 0.000000 0.229518 2.463352 3.359134 \n",
"0-10p 13.516065 0.047737 0.353191 0.195589 1.447086 5.012975 \n",
"10-20 22.967251 0.110719 0.482074 0.327151 1.424424 2.891639 \n",
"20-30 22.963506 0.028243 0.122991 0.866300 3.772507 15.196724 \n",
"30-40 22.965008 0.188819 0.822205 1.241304 5.405198 19.764185 \n",
"40-50 22.963626 0.265455 1.155982 0.893003 3.888772 19.371119 \n",
"50-60 22.963783 0.102927 0.448213 0.792758 3.452209 25.943654 \n",
"60-70 22.963858 0.075591 0.329172 0.922169 4.015742 41.900316 \n",
"70-80 22.963832 0.116813 0.508682 0.773757 3.369461 53.408915 \n",
"80-90 22.965928 0.026866 0.116984 0.980743 4.270425 124.597783 \n",
"90-100 22.964168 0.000164 0.000716 3.894890 16.960726 7180.819580 \n",
"ALL 229.641673 0.963335 0.419495 11.244542 4.896560 764.654602 \n",
"90-95 11.481263 0.000164 0.001431 0.748162 6.516377 247.893906 \n",
"95-99 9.185571 0.000000 0.000000 1.370969 14.925250 996.222892 \n",
"Top 1% 2.297334 0.000000 0.000000 1.775758 77.296450 66557.369070 \n",
"\n",
" tot_change share_of_change ubi benefit_cost_total \\\n",
"0-10n 3.635925 2.070613 0.0 0.0 \n",
"0-10z 0.031298 0.017824 0.0 0.0 \n",
"0-10p 0.067756 0.038586 0.0 0.0 \n",
"10-20 0.066413 0.037821 0.0 0.0 \n",
"20-30 0.348970 0.198734 0.0 0.0 \n",
"30-40 0.453885 0.258482 0.0 0.0 \n",
"40-50 0.444831 0.253326 0.0 0.0 \n",
"50-60 0.595764 0.339280 0.0 0.0 \n",
"60-70 0.962193 0.547957 0.0 0.0 \n",
"70-80 1.226473 0.698461 0.0 0.0 \n",
"80-90 2.861504 1.629590 0.0 0.0 \n",
"90-100 164.901550 93.909327 0.0 0.0 \n",
"ALL 175.596562 100.000000 0.0 0.0 \n",
"90-95 2.846135 1.620838 0.0 0.0 \n",
"95-99 9.150876 5.211307 0.0 0.0 \n",
"Top 1% 152.904539 87.077182 0.0 0.0 \n",
"\n",
" benefit_value_total pc_aftertaxinc \n",
"0-10n 0.0 29.877067 \n",
"0-10z 0.0 NaN \n",
"0-10p 0.0 -0.118762 \n",
"10-20 0.0 -0.017193 \n",
"20-30 0.0 -0.047757 \n",
"30-40 0.0 -0.045805 \n",
"40-50 0.0 -0.036277 \n",
"50-60 0.0 -0.039489 \n",
"60-70 0.0 -0.051233 \n",
"70-80 0.0 -0.051305 \n",
"80-90 0.0 -0.091139 \n",
"90-100 0.0 -2.481368 \n",
"ALL 0.0 -0.927041 \n",
"90-95 0.0 -0.134523 \n",
"95-99 0.0 -0.357924 \n",
"Top 1% 0.0 -7.749033 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tb.differences_table(2029, groupby='weighted_deciles', tax_to_diff='combined')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/andersonfrailey/opt/anaconda3/envs/taxbrain-dev/lib/python3.7/site-packages/pandas/core/arraylike.py:358: RuntimeWarning: divide by zero encountered in log\n",
" result = getattr(ufunc, method)(*inputs, **kwargs)\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"vol_fig = volcano_plot(tb, 2030, y_var='expanded_income', x_var='combined', min_y=0, max_y=100000)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"vol_fig.savefig('biden_volcano.png', dpi=300, bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"dist_fig = distribution_plot(tb, 2025)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"dist_fig.savefig('biden_dist_fig.png', dpi=300, bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>2021</th>\n",
" <th>2022</th>\n",
" <th>2023</th>\n",
" <th>2024</th>\n",
" <th>2025</th>\n",
" <th>2026</th>\n",
" <th>2027</th>\n",
" <th>2028</th>\n",
" <th>2029</th>\n",
" <th>2030</th>\n",
" <th>2021-2030</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Repeal TCJA Rate Cuts</th>\n",
" <td>1.944811e+10</td>\n",
" <td>2.091922e+10</td>\n",
" <td>2.219167e+10</td>\n",
" <td>2.363228e+10</td>\n",
" <td>2.526862e+10</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>1.114599e+11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Repeal QBID</th>\n",
" <td>-1.066686e+09</td>\n",
" <td>-1.132504e+09</td>\n",
" <td>-1.221608e+09</td>\n",
" <td>-1.277382e+09</td>\n",
" <td>-1.354201e+09</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>-6.052381e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Apply payroll taxes on earnings above $400,000</th>\n",
" <td>6.893831e+10</td>\n",
" <td>7.501463e+10</td>\n",
" <td>8.089178e+10</td>\n",
" <td>8.746919e+10</td>\n",
" <td>9.483340e+10</td>\n",
" <td>1.029119e+11</td>\n",
" <td>1.114545e+11</td>\n",
" <td>1.198176e+11</td>\n",
" <td>1.278213e+11</td>\n",
" <td>1.354880e+11</td>\n",
" <td>1.004641e+12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Increase rates on capital gain for high income filers</th>\n",
" <td>1.943691e+10</td>\n",
" <td>1.994599e+10</td>\n",
" <td>1.884626e+10</td>\n",
" <td>1.920345e+10</td>\n",
" <td>2.011179e+10</td>\n",
" <td>2.135084e+10</td>\n",
" <td>2.257682e+10</td>\n",
" <td>2.177177e+10</td>\n",
" <td>2.301009e+10</td>\n",
" <td>2.412731e+10</td>\n",
" <td>2.103812e+11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Limit certain itemized deductions</th>\n",
" <td>-2.024216e+10</td>\n",
" <td>-2.143057e+10</td>\n",
" <td>-2.307510e+10</td>\n",
" <td>-2.493433e+10</td>\n",
" <td>-2.718919e+10</td>\n",
" <td>4.987721e+09</td>\n",
" <td>5.205878e+09</td>\n",
" <td>5.460407e+09</td>\n",
" <td>5.702162e+09</td>\n",
" <td>5.979632e+09</td>\n",
" <td>-8.953554e+10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Expand EITC eligibility above age 64</th>\n",
" <td>-3.116851e+08</td>\n",
" <td>-3.122856e+08</td>\n",
" <td>-3.141890e+08</td>\n",
" <td>-3.191060e+08</td>\n",
" <td>-3.210939e+08</td>\n",
" <td>-3.229633e+08</td>\n",
" <td>-3.196877e+08</td>\n",
" <td>-3.169682e+08</td>\n",
" <td>-3.155153e+08</td>\n",
" <td>-3.135237e+08</td>\n",
" <td>-3.167018e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Changes to IRA and KEOGH plans</th>\n",
" <td>1.196385e+10</td>\n",
" <td>1.250455e+10</td>\n",
" <td>1.306867e+10</td>\n",
" <td>1.369032e+10</td>\n",
" <td>1.438318e+10</td>\n",
" <td>1.663384e+10</td>\n",
" <td>1.756286e+10</td>\n",
" <td>1.841349e+10</td>\n",
" <td>1.937848e+10</td>\n",
" <td>2.031875e+10</td>\n",
" <td>1.579180e+11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Residential energy credit</th>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" <td>0.000000e+00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Total</th>\n",
" <td>9.816664e+10</td>\n",
" <td>1.055090e+11</td>\n",
" <td>1.103875e+11</td>\n",
" <td>1.174644e+11</td>\n",
" <td>1.257325e+11</td>\n",
" <td>1.455613e+11</td>\n",
" <td>1.564804e+11</td>\n",
" <td>1.651463e+11</td>\n",
" <td>1.755966e+11</td>\n",
" <td>1.856001e+11</td>\n",
" <td>1.385645e+12</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 2021 \\\n",
"Repeal TCJA Rate Cuts 1.944811e+10 \n",
"Repeal QBID -1.066686e+09 \n",
"Apply payroll taxes on earnings above $400,000 6.893831e+10 \n",
"Increase rates on capital gain for high income ... 1.943691e+10 \n",
"Limit certain itemized deductions -2.024216e+10 \n",
"Expand EITC eligibility above age 64 -3.116851e+08 \n",
"Changes to IRA and KEOGH plans 1.196385e+10 \n",
"Residential energy credit 0.000000e+00 \n",
"Total 9.816664e+10 \n",
"\n",
" 2022 \\\n",
"Repeal TCJA Rate Cuts 2.091922e+10 \n",
"Repeal QBID -1.132504e+09 \n",
"Apply payroll taxes on earnings above $400,000 7.501463e+10 \n",
"Increase rates on capital gain for high income ... 1.994599e+10 \n",
"Limit certain itemized deductions -2.143057e+10 \n",
"Expand EITC eligibility above age 64 -3.122856e+08 \n",
"Changes to IRA and KEOGH plans 1.250455e+10 \n",
"Residential energy credit 0.000000e+00 \n",
"Total 1.055090e+11 \n",
"\n",
" 2023 \\\n",
"Repeal TCJA Rate Cuts 2.219167e+10 \n",
"Repeal QBID -1.221608e+09 \n",
"Apply payroll taxes on earnings above $400,000 8.089178e+10 \n",
"Increase rates on capital gain for high income ... 1.884626e+10 \n",
"Limit certain itemized deductions -2.307510e+10 \n",
"Expand EITC eligibility above age 64 -3.141890e+08 \n",
"Changes to IRA and KEOGH plans 1.306867e+10 \n",
"Residential energy credit 0.000000e+00 \n",
"Total 1.103875e+11 \n",
"\n",
" 2024 \\\n",
"Repeal TCJA Rate Cuts 2.363228e+10 \n",
"Repeal QBID -1.277382e+09 \n",
"Apply payroll taxes on earnings above $400,000 8.746919e+10 \n",
"Increase rates on capital gain for high income ... 1.920345e+10 \n",
"Limit certain itemized deductions -2.493433e+10 \n",
"Expand EITC eligibility above age 64 -3.191060e+08 \n",
"Changes to IRA and KEOGH plans 1.369032e+10 \n",
"Residential energy credit 0.000000e+00 \n",
"Total 1.174644e+11 \n",
"\n",
" 2025 \\\n",
"Repeal TCJA Rate Cuts 2.526862e+10 \n",
"Repeal QBID -1.354201e+09 \n",
"Apply payroll taxes on earnings above $400,000 9.483340e+10 \n",
"Increase rates on capital gain for high income ... 2.011179e+10 \n",
"Limit certain itemized deductions -2.718919e+10 \n",
"Expand EITC eligibility above age 64 -3.210939e+08 \n",
"Changes to IRA and KEOGH plans 1.438318e+10 \n",
"Residential energy credit 0.000000e+00 \n",
"Total 1.257325e+11 \n",
"\n",
" 2026 \\\n",
"Repeal TCJA Rate Cuts 0.000000e+00 \n",
"Repeal QBID 0.000000e+00 \n",
"Apply payroll taxes on earnings above $400,000 1.029119e+11 \n",
"Increase rates on capital gain for high income ... 2.135084e+10 \n",
"Limit certain itemized deductions 4.987721e+09 \n",
"Expand EITC eligibility above age 64 -3.229633e+08 \n",
"Changes to IRA and KEOGH plans 1.663384e+10 \n",
"Residential energy credit 0.000000e+00 \n",
"Total 1.455613e+11 \n",
"\n",
" 2027 \\\n",
"Repeal TCJA Rate Cuts 0.000000e+00 \n",
"Repeal QBID 0.000000e+00 \n",
"Apply payroll taxes on earnings above $400,000 1.114545e+11 \n",
"Increase rates on capital gain for high income ... 2.257682e+10 \n",
"Limit certain itemized deductions 5.205878e+09 \n",
"Expand EITC eligibility above age 64 -3.196877e+08 \n",
"Changes to IRA and KEOGH plans 1.756286e+10 \n",
"Residential energy credit 0.000000e+00 \n",
"Total 1.564804e+11 \n",
"\n",
" 2028 \\\n",
"Repeal TCJA Rate Cuts 0.000000e+00 \n",
"Repeal QBID 0.000000e+00 \n",
"Apply payroll taxes on earnings above $400,000 1.198176e+11 \n",
"Increase rates on capital gain for high income ... 2.177177e+10 \n",
"Limit certain itemized deductions 5.460407e+09 \n",
"Expand EITC eligibility above age 64 -3.169682e+08 \n",
"Changes to IRA and KEOGH plans 1.841349e+10 \n",
"Residential energy credit 0.000000e+00 \n",
"Total 1.651463e+11 \n",
"\n",
" 2029 \\\n",
"Repeal TCJA Rate Cuts 0.000000e+00 \n",
"Repeal QBID 0.000000e+00 \n",
"Apply payroll taxes on earnings above $400,000 1.278213e+11 \n",
"Increase rates on capital gain for high income ... 2.301009e+10 \n",
"Limit certain itemized deductions 5.702162e+09 \n",
"Expand EITC eligibility above age 64 -3.155153e+08 \n",
"Changes to IRA and KEOGH plans 1.937848e+10 \n",
"Residential energy credit 0.000000e+00 \n",
"Total 1.755966e+11 \n",
"\n",
" 2030 2021-2030 \n",
"Repeal TCJA Rate Cuts 0.000000e+00 1.114599e+11 \n",
"Repeal QBID 0.000000e+00 -6.052381e+09 \n",
"Apply payroll taxes on earnings above $400,000 1.354880e+11 1.004641e+12 \n",
"Increase rates on capital gain for high income ... 2.412731e+10 2.103812e+11 \n",
"Limit certain itemized deductions 5.979632e+09 -8.953554e+10 \n",
"Expand EITC eligibility above age 64 -3.135237e+08 -3.167018e+09 \n",
"Changes to IRA and KEOGH plans 2.031875e+10 1.579180e+11 \n",
"Residential energy credit 0.000000e+00 0.000000e+00 \n",
"Total 1.856001e+11 1.385645e+12 "
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tb.stacked_table"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"diff_fig = differences_plot(tb, tax_type='combined');"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"diff_fig.savefig('biden_diff_fig.png', dpi=300, bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/andersonfrailey/opt/anaconda3/envs/taxbrain-dev/lib/python3.7/site-packages/matplotlib/cbook/__init__.py:1402: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version. Convert to a numpy array before indexing instead.\n",
" ndim = x[:, None].ndim\n",
"/Users/andersonfrailey/opt/anaconda3/envs/taxbrain-dev/lib/python3.7/site-packages/matplotlib/axes/_base.py:276: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version. Convert to a numpy array before indexing instead.\n",
" x = x[:, np.newaxis]\n",
"/Users/andersonfrailey/opt/anaconda3/envs/taxbrain-dev/lib/python3.7/site-packages/matplotlib/axes/_base.py:278: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version. Convert to a numpy array before indexing instead.\n",
" y = y[:, np.newaxis]\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"lorenz_curve(tb, 2021);"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/andersonfrailey/opt/anaconda3/envs/taxbrain-dev/lib/python3.7/site-packages/pandas/core/indexes/range.py:780: FutureWarning: Support for multi-dimensional indexing (e.g. `obj[:, None]`) is deprecated and will be removed in a future version. Convert to a numpy array before indexing instead.\n",
" return super().__getitem__(key)\n"
]
},
{
"data": {
"image/png": 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dDurCy4ZgJCcHTKkASaSQBAZCEhQMcd++ICH/FX+3KCsrE8XExAT079+/qTkouV/x/7Ucx3F3CabXQ1NUCGVmJlQ52WAKOUgsgTggANKgYIj7+YBEpv+1rrhaCU2THNZ9+pi8rfuFm5ubtqioKPPm4xEREcp7bbTkVnhgwnEc14MxpoemuBiqrEwos7PAmppAZmKI/f0hDQ6B2McHJDIzeT8aiotQkpiIkgOJqPrzHDzGx2PYlwkmb5e7//DAhOM4rodhjEFbVgplViZUWVnQN9QDIhEkfv6QBIdA4usLMhObvA91+fkoObAfJYmJqMkxpOSwCw5B2NJX4Dl+vEnb5+5fPDDhOI7rARhj0F65AlVWBpRZmdDX1gJCIcQ+vpAGj4XYzx8CicS0fdDrcT09/UYw0lB4GSCCY2QkBvzrDXiMGwdLD0+T9oHjeGDCcRx3B2mvXoUyKwOqzEzoqq8DAgHEfftCEjcCkoAACKTmJm1fr9Xi6h9nUXogESUHD0BeUQESidB7SAwCnn0WHmPGwtzJ2aR94LiWeGDCcRzXzbTXr98YGdFdvQoQwczbG7KYByAJDIRAZnHrSjpBp1Lhyu8nUXIgEaWHDkJVUwOhRAKXuOEIf2U53EaNgsTG1qR9uNNkMlmEXC5PvdP9uJW8vDxxeHh4iLe3t5IxBplMpv/mm28uh4eHq+5030yFByYcx3HdQFdbY5wzkgltRQUAwMzTE+bxD0ISFAShpZVJ29c0NaH82FGUHEhE2dEj0DY2wszKCm4jR8Fj3Hi4xg2HSCYzaR+4v8fDw0OVm5ubDQDvv/++w4oVK1x27NhReIe7ZTI8MOE4jjMRXX09VNmZUGZlQltaCgAQubnBcuw4SIJCILSxMWn7qtpalP12CCWJiShPSoJerYLE3h5eD06Ex/h49B4SA6GJ5630dHv27LFauXKlq729vSYvL888NDRU/ssvv1wWCAQ4fvy4bMmSJZ5yuVwgFotZUlJSnkQiYXPmzPFKT0+XCYVCvPfeeyWTJk1q+OSTT3rt2rXLVq/XU15envmiRYuuqNVqwY8//thLLBbrDx48eMHZ2VmXlZUlef755z2rq6tFUqlUv2HDhqKIiIgOZ2utr68X2tra6gDDaMqMGTP6NO/T8/HHHxePGTOmqaioyGzKlCl9GxsbhTqdjj799NOi8ePHN+7YscN65cqVrmq1mry8vFQ//PBDoY2NTYf38ukuPDDhOI7rQvqmRiizs6HKyoCmqBgAg6h3b1iMGg1pcAiEdvYmbV9xtRIlBw+iJHE/Kk+fAtPpIHN1he+MGfAYFw/HgQMhEPacLLAv/nDSI6eipkuHagJd7OSfTo8t6ej1OTk55ufPn7/k7e2tiYyMDDh06JBlXFxc08yZM/tt2bKlIC4uTl5dXS2wtLTUv/POO84AkJ+fn52amiqdMGGCb0FBQabxmHlaWlq2QqEQ+Pv7h7zxxhtlOTk52XPnzvVISEjo9eabb1599tlnvdavX18UGhqqOnLkiMWCBQs8T58+nb9lyxabP/74w+Kjjz4qv7l/JSUlkoCAgKCmpiaBUqkUJCcn5wKAq6ur9sSJE/kymYxlZGRInnjiib6ZmZk5GzdutB81alTdmjVrrmi1WjQ0NAgqKipEq1evdklKSsq3trbW/+tf/+r99ttvO3/wwQcVXfW+dxUemHAcx3WSXiGHKicHyqwMaC5fBhiD0NERFsOHQxIcCpGDg0nbvznHCABY9emLoPnPw2PceNiHhoGITNqHu1loaGhTv379NAAQHBwsLygoENvZ2emcnJw0cXFxcgCwt7fXA0BycrLliy++eBUwJD9zdXVVZ2RkSAEgJiamwc7OTm9nZ6e3tLTUTZ06tdZYvzw9PV1WV1cnSE1NtZw6dWq/5rbVajUBwMyZM+tmzpxZ11r/Wt7K+frrr+2eeeYZrxMnTlxQq9U0d+5cr+zsbHOBQICioiIJAAwePLhp/vz53hqNRvDYY4/VxMTEKLZu3WpVUFAgjY6ODgAAjUZDkZGRjaZ5RzuHByYcx3F/g16phCovF6qsDKgLCgC9HkJ7e8hih0IaEgqRCVeydCTHiLWP710RjNzOyIapSCSSG5vGCYVCaLVaYoyBiP6ymVx7+8uJxeIbJwUCAaRSKWt+rNVqSafTwcrKStscZPwdTzzxRO3ixYu9AWDVqlXOTk5Omu3bt1/W6/UwNzePBID4+PjGpKSkvO3bt9s89dRTfRYvXlxpb2+vjY2Nrd+9e/flv9t2d+GBCcdxXAcxtRqq/DzDzr0XLgA6LQQ2NpANHgJJSChEvV1MFgwwxnA9LY3nGOkm4eHhysrKSvHx48dlcXFx8pqaGoGlpaU+Nja2cfPmzfaTJ09uSE9Pl1RUVIjDwsKUZ86cueXtKHt7e727u7t648aNds8880yNXq/HmTNnzIcMGaLoaL8OHTpk5eHhoQKAuro6obu7u1ooFOKzzz7rpdPpAAD5+fniPn36qJctW1bV1NQk+PPPP2XvvPNOxbJlyzwzMzMlISEhqoaGBsHly5fNwsLCetzqHh6YcBzHtYNpNVBfuGBYUZOfB2g0EFhZwTwqyjAy4uZusmBEr9Ph2h9/GIKRA4k8x0g3kkqlbMuWLQWLFy/2VCqVAqlUqk9KSspfvnz51dmzZ3v5+fkFCYVCJCQkFJqbm7c9jHKTrVu3Xpo3b57XmjVrXLRaLT3yyCPVQ4YMUXRkjgljDGZmZuyrr74qAoAlS5ZcnTJlSr9ffvnFLjY2tsHc3FwPAAcOHLD65JNPeotEIiaTyXRbtmy57Orqqk1ISCicPn163+bbR//7v/9b1hMDE2pvWIprX1RUFEtJSbnT3eA4rosxnQ7qy5egysyAKjcHTKUCySwgDQqCJCQUZp6eIBKYpG2dWo3KU6dQkrgPJYcOQnX9OgRiCVzj4uAxbjzcRo2GxPbuzjGSlpZWFB4eXnWn+8HdOWlpaQ7h4eHerZ3jIyYcx3FosVleZoZhszy5HCSRQhJoCEbEffqABKZZzaJVKlGRdBwliftR9tthqOvrIbKwgNuIkfAYHw/X4SNgZmHapGsc11OYPDAhIm8Awxlj39x0/DEAPwEYyBj7y7ADEY0H8DEAIYANjLF3jcftAfwIwBtAIYDHGWM1xnP/ADAXgA7AYsbYgVbq7VR5juPuHYwxaCvKoczMgCorE/r6ekBkBom/P6QhoRD7+IJEpvk1qWloQNmxoyjZvw9lx45Cp1BAbGMD97Hj4DFuPFyGDoVQIjVJ2xzXk5k0MCGiBQCWAJAR0VMApjPGrhCRFYDFAM60UU4I4HMAYwCUAviDiHYxxrIBvA7gN8bYu0T0uvH5a0QUBGA6gGAArgAOE5EfY0x3U/WdLc9x3F1Oe+2qIRjJzICuuhoQCCH28YF09FiI/f0hEJsm6Ziqpgalhw+hJHE/Kk6egF6thtTBEX0fnQKP8fFwHjQYAjMzk7TNcXcLkwUmxuBjBYBJAAIBHAPQZDz9NoD3ALzSRvFoABcZY5eMdf0A4CEA2cbvw43XfWus9zXj8R8YYyoAl4noorGeUzfV3dnyHMfdhXQ1NcbN8jKgraw07k/TB7IHhhr2pzE3TTr2/yQ824fK06eNCc/c4Dd7DjzGjYfDgMgelfCM4+40U46Y6AGIAVgDAGOsEACIKAKAB2NsDxG1FZi4AWi5tr0UwCDjY2fGWIWxzgoicmpR5vRNZdxaqbtT5YnoOQDPAYCnJ1+ax3E9ma6hAaqsTCizMv6TEt7dA5bjJ0ASHGyy/WkaS0uMCc/249q5cwBj/0l4Nj4e9iGhd0WOEY67E0wWmDDGmohoDoDVAHoTUQiANwF8COCpWxRv7Sf2VsuH/k6Z2y7PGFsPYD1gWJVzG/VzHNcN9Ao5VNnZhiyshYUAa04JPwbSkBAIbe1M0m5dwUVDMJK4D9WZmQAAu8AghC1ZCo/x42Hj68eDEY7rAJPOMWGM7SKidBhu50QBeBVACIBjxh/Q3gB2EdHkmybAlgLwaPHcHUDz2u5KInIxjna4ALjagTItdbY8x3E9jF6tgjo3F8rMDKgLLhqysPbqBdmwOEiDQyFydOzyNhljqMnJRsn+/Sg5sB91Fy4AABwiBiDi9X/CY/x4WHl5d3m7XNeQyWQRcrk89U7341by8vLE4eHhId7e3kqNRkNhYWFNP/zwQ1HLbLWtmT9/vvtvv/1mM2rUqLqEhITS7upvVzDlHBNLAL2MTxsA5ACwZ4w5tLjmGIBXmoMSIspljAUA+AOALxH1AVAGw6TUGcZiuwA8CeBd4/dfWxz/nojWwTB51RfA2Va61tnyHMf1ADcSn2VmQJWfD2g1EFibNgsr0+tRdT71xm2axuJikEAAp+hB8J05Gx5jx0Hm4tKlbXJc8145Wq0WsbGxfhs3brRbsGBBdXtltmzZ4njt2rXzHU3+ptFoYNZDJl6bcsTEDEACAAcYApRi/Ce4+AsicoDxdgpjTEtELwA4AMNy4Y2MsSzjpe8C2EZEc411TjWWySKibTBMkNUCWNS8ooaINgD4yhgA3XZ5juN6BqbXQX3pr4nPzCMiDInPPDy6PPGZIfvqWRTv24eSg4lQVFZCYGaG3g/EInjBIriPGQtpr163rojrkfbs2WO1cuVKV3t7e01eXp55aGio/JdffrksEAhw/Phx2ZIlSzzlcrlALBazpKSkPIlEwubMmeOVnp4uEwqFeO+990omTZrU8Mknn/TatWuXrV6vp7y8PPNFixZdUavVgh9//LGXWCzWHzx48IKzs7MuKytL8vzzz3tWV1eLpFKpfsOGDUURERHKjvRVJBJhwIABTWVlZWYAoNVqsWjRIvfff//dSq1W07x5866++uqrVSNHjvRRKBSCiIiIwGXLllXExcU1Pfnkk97Xr18X9erVS7tp06ZCX19f9ZQpU7zt7Oy0GRkZsrCwMLmVlZW+sLBQXFlZaVZYWChdvXp1yalTpyyPHDli7ezsrDl8+PDFW43UdAVTzjGpATC+rTwmxmuGt3g6GIYlws3n9gHY10qZ6wBGtdHmKgCrWjn+bGfKcxx357SX+EwaEgozEyQ+02u1uHrmNIr370NJYiKU16sglErhGjccHuPj4TZyFMTW1l3a5v3qx9xqjytNmi5dEtXbwkw+LcC+w5sD5uTkmJ8/f/6St7e3JjIyMuDQoUOWcXFxTTNnzuy3ZcuWgri4OHl1dbXA0tJS/8477zgDQH5+fnZqaqp0woQJvgUFBZnGY+ZpaWnZCoVC4O/vH/LGG2+U5eTkZM+dO9cjISGh15tvvnn12Wef9Vq/fn1RaGio6siRIxYLFizwPH36dH57KembyeVyOnfunMUnn3xSAgAfffSRg42NjS4zMzNHoVDQwIEDAyZNmlR/5MiRizKZLKJ5s8CRI0f6zJgx4/qLL754/aOPPuq1YMECj8OHDxcAQEFBgfT333/PF4lEWLp0qWtRUZEkOTk5/88//5SOHDky4Ntvvy346quvSseMGdNv27ZtNrNnz67tzL9NR3RH5tdaAOdvdRFjbE839IXjuLuE9upVKNPOQ5mZ3i2Jz/RaLSpPJRuCkYMHoLp+HUJzc7iNHAXP+AlwGzESIplplhRzd1ZoaGhTv379NAAQHBwsLygoENvZ2emcnJw0cXFxcsCwAR8AJCcnW7744otXASAiIkLp6uqqzsjIkAJATExMg52dnd7Ozk5vaWmpmzp1aq2xfnl6erqsrq5OkJqaajl16tR+zW0371szc+bMupkzZ9a11r/mvXKKiook8fHxNYMGDVIAwOHDh61zc3Nlu3btsgOAhoYGYXZ2tjQgIEDdsnxqaqrF/v37CwBgwYIF1StWrHBvPvfoo4/WiFr8LI0ePbpOIpGw6OhohU6no8cee6ze+L4oLl++LO7UG91BJg9MGGMdCkw4juP0jY1QZqZDmZYG7ZUKQCAwaeIzvUaDK8nJKN6/F6UHD0BVUwORTAa3UaPhGT8BrsNHQGRu3qVtcv/tdkY2TKXl7QmhUAitVkuMMRBRaysz26xHLBbfOCkQCCCVSlnzY61WSzqdDlZWVtrmkYyOap5jUlRUZBYXF+e/ZcsWm5kzZ9Yxxmjt2rXFU6ZMqb+d+lqytCnvTTUAACAASURBVLTUt3ze/F4IhUKIRCImEAhuvB6tVtsty8pMswsVx3FcBzGNBsrMDNRu+Q5V6z5A44FEQECwHD8BDktfhe0TsyANDeuyoESnVqPs2FGcfu1VbI+OxNGnZqNoz264DIvDsK/WY8q584j95DN4xk/gQcl9LDw8XFlZWSk+fvy4DABqamoEGo0GsbGxjZs3b7YHgPT0dElFRYU4LCysQ3NE7O3t9e7u7uqNGzfaAYBer8epU6c6/J/My8tLs3LlytL333/fBQDGjBlT9+WXXzqqVCpq7k99ff1fPtcjIiKaNmzYYAcACQkJ9lFRUY0dbfNO4Jv4cRzX7RjTQ1NUBGVaGlTZWWBqlWFFzQMPQBrWv8uX9+rUalw5eQLF+/ai9NBBqOvrYWZlBbdRo+E14UG4DBvG96Xh/otUKmVbtmwpWLx4sadSqRRIpVJ9UlJS/vLly6/Onj3by8/PL0goFCIhIaGwoytfAGDr1q2X5s2b57VmzRoXrVZLjzzySPWQIUMUHZljAgCzZs2qXbVqlWtiYqLlyy+/XFVYWCgJDQ0NZIyRvb29Zt++fQU3l/nyyy+Ln3zySe+PP/64d/Pk17/xlnQbam9YimtfVFQUS0n5y/6DHMe1QVt1Dcq0NCgz0qCvqwOJJZAEBUEaFg4zb+8uXVGjU6lQcSLJEIwcPgxNQz3MrKzhPmYMPCc8CJfYoRBKTLMnDte+tLS0ovDw8Ko73Q/uzklLS3MIDw/3bu0cHzHhOM6k9PImKDMzoUw7D215GUAEcT8fSEeNgSQgAGTWdfPpdColyo8bgpGyI4ehaWiA2NoaHuPGwXPCg+gd8wAPRjiuh+OBCcdxXY5pNVDl50OZdh7qixcAvR6i3r1hOXY8JKGhXbpHjVapRMXxYyjatxdlvx2GtqkJYltbeMZPgOeEB+E8JAZCcbcsJuA4rgvwwITjuC7BGIOmpNgwbyQrE0ylhMDKCrLBQwzzRpydu6wtrUKB8mNHjSMjv0Erl0NiZweviZPgNWEinIcMgaCHZLHkOO728MCE47hO0VZf/8+8kZoakJkYksBASMP7w8y7D0jQNfNGtHI5yo4eMQQjR49Ap1BAYm8P74ceNoyMDB4CQRfnNuE4rvvxn2KO426bXiE3zBtJT4O2tAQAwaxvX1jEjYAkMLDLlvZq5XKUHjmM4r17UX7sKHRKJaS9HND30SnwnPAgnKIH8WCE4+4x/Cea47gOYTqtYdO8tPOGTfP0OgidnGAxeiykoWEQdlGKdp1KhfLjx1G0+1eU/nYYOoUCUgdH9H3scXg9+CAcB0ZDIOzaFPQcx/UcPDDhOK5NjDFoy0oNqeGzMsEUCggsLGEePQjS8HCInHt3yQ6+eq0WlcnJKNz9K0oOHICmoR4SOzv0fXQKvCZOhuPAgTwY4bqUUCiM9PX1Veh0OvLx8VFs27at0MrKSn/rkn+Pm5tbaEpKSo6Li4tWJpNFyOXy1Pauj46O9r969aqZVCrVq9VqWrhwYeUrr7xyXyyx5oEJx3F/wbQayE+dgvJ8KnTV1w371AQEQBreH+K+fbtk0zym1+Nayh8o3L0bxfv3QnX9OsysrOAxdhy8Jk1G75gH+ARWzmQkEom+OTX85MmT+6xdu9bxrbfeqvy79en1ejDGIOzCAHrTpk2Xhg0bJq+srBT6+vqGvvDCC9eb09zfy24ZmJDhz6EQAK4AFACyjDv0chx3D9JWXUP9zz9BW3kFZt59IIsdCklQEARdkBmVMYbqjHQU7d6Nor27Ia+ogFAqhduo0fCeNBmuw4fzDKxct4uNjW1MT083B4DRo0f3q6ioEKtUKsHzzz9f+corr1R9+OGHDpmZmeb//ve/SwBg7dq1Djk5OdJXX331anx8vG9MTEzDuXPnLH/99deLR48etVy7dm1vxhiNHj269ssvvyzrbP/q6+uF5ubmepFIxABg5syZnmlpaRZKpVIwadKkmg8//LAcABYuXOh24MABW6FQyIYPH16/fv360vLyctHTTz/tVVZWJgaAdevWFY8dO7aps30ypTYDEyLyBrAcwHgAlwFcAyAF4EtEtQC+ArCZ8dSxHHdPYIxBeT4VDfv3gszMYPPETEj8/Luk7tr8PEMwsmcXGgoLITAzg8uwOPR/7R9wHz0GZhYWXdIOd/d5b/97HpevXe7SbZv7OPaRL49f3qHNATUaDQ4cOGA9duzYegDYsmVLobOzs66xsZEiIiKCZs2aVTN37tzq4ODgIJVKVSqRSNjmzZsdEhISigCgsLBQ+vXXXxdu3ry5uLCw0Oytt95yO3fuXI6jo6N26NChft99953t7Nmza9tqPyAgIKitTf3mzJnTVywW64uLi6Vvv/12cfMuwOvWrStzdnbWabVaxMTE+J85c8bc29tbvW/fPrtLly5lCgQCVFVVCQFg/vz5HkuXLq0cN25c44ULF8Tjxo3zvXTpUtZtvqXdqr0Rk/cAfAngBcbYf913IyIXADMBPAngG5P1juO4bqFXKdGwdw9UGekw8/aG9SOPdXoya0NxkSEY2b0LtXm5IIEAzkNiEPT8QniMGw+JrW0X9Z7jbp9KpRIEBAQEAcCgQYMaXnrppSoAWLNmjfPevXttAeDKlStmWVlZ0lGjRjU98MADDT/++KNNaGioUqPRUHR0tCIvL0/s4uKiHjVqVBMAnDx50mLw4MENrq6uWgCYNm1a9fHjxy3bC0za22m4+VZOeXm5aMiQIQEPPfRQvZ+fn/rbb7+1/+abbxy0Wi1du3bNLC0tTTpgwACFRCLRT58+3evBBx+smzZtWh0A/P7779YXLly4sVFgY2OjsKamRmBnZ2ey+TSd1WZgwhh7vJ1zFQA+MEmPOI7rVpryMtT//BN0tTWwGDESsthhfzv3iPzKFRTt3YOi3btwPe08AMAhMhJRb62E54QJMHd06squc/eAjo5sdLWWc0ya7dmzx+r48eNWKSkpuVZWVvro6Gh/hUIhAIDnnnuuatWqVb39/PyUs2bNujEJVSaT3fiAN9UNBFdXV21ISIg8KSnJQq/X47PPPnM2jsropkyZ4q1UKgVmZmY4f/58zq5du6x/+OEHuy+//NLp9OnT+YwxpKSk5FhaWt41dzdu+duHiB4lIivj49eJaBsR9Td91ziOMyXG9JCf+h01/94AptPB9qlnYDFs+G0HJcrqauRv+Q6Hpj+OnTGD8Oc7K6HXatH/tX/goRPJGPfzTvg/+RQPSrger7a2VmhjY6OzsrLSp6amStPS0m7cYxw5cmRTRUWFeOfOnb3mzp1b3Vr5YcOGNZ05c8aqoqJCpNVq8dNPP9kPHz68sbP9amhoEGRlZcn8/f1VNTU1QnNzc729vb2upKREdOzYMRsAqKurE1RXVwunTZtW99VXX5Xk5OTIACA2NrZ+zZo1N374kpOTzdtqp6foyKqctxhjO4goBsAkAOtgmF8y2KQ94zjOZPRNjaj/ZSfUFy9AHBAI68kPQWDe8dv86vp6lB46gMLdu3Hl5AkwnQ7Wffsh9KUl8J44Gdb9+pmw9xxnGlOmTKlbv369o5+fX1C/fv2U4eHh/zVJ9OGHH65JT0+XOTo66lor7+XlpXnzzTfL4uLi/BhjNGrUqLpZs2a1eRsHuPUck+blwtOnT68aOnSoHABCQkLkvr6+wZ6enqrIyMhGwBBUTZw40UelUhEAvPPOOyUAsH79+pJnn33W08/PL0in09GgQYMaYmJiim//3ek+dKuhJyJKZYxFENFqGFbkbGk+1j1d7LmioqJYSkrKne4Gx90W9aUC1O/cDr1CCctx42EeNbBDuUi0CgXKjvyGot27UHb0KPRqFSzc3OE1aRK8Jz0E28DALslpwt370tLSisLDw++6nBwjRozwWbJkSeVDDz3UcKf7crdLS0tzCA8P927tXEdGTCqI6HMYVudEEZEYHbgFxHFcz8L0OjQdPQr5yRMQOvSC/aw5EDn3breMTq1GxYkkFO3ehdJDB6GVyyF1dITvjBnwmjQZDhEDeDDC3fOqqqqEUVFRgYGBgXIelJheRwKTxwFMAPApY6yGiFwBvG7abnEc15V0tbWo3/ETNCUlkEYMgNX4CSCxuM3rldevI/3DtSjasxvqujqIbWzgPfkheE2aDKdBg3kWVu6+4uDgoCssLMy80/24X9wyMGGMNRLRTwAcjUEJAKR1tAFjPpThjLFvjM+fB7AIgA5AI4DnGGN/ub9GRIUAGozXaRljUcbj9gB+BOANoBDA44yxGuO5fwCYayyzmDF2oJV6O1We4+42yuwsNOz+FdAzWE+ZCmlIaLvXlx35DadfWw51fR08JzwI70mT0Tt2KITtBDIcx3FdpSOZXxcCWAngOoDmZVEMQFAHyi4AsASAjIieAjAdwPeMsa+M5yfDMJl2fBtVjGCM3Xwf8nUAvzHG3iWi143PXyOiIGP9wTBkqT1MRH6MsZsnKXW2PMfdFZhGg8YDiVCc+wMiVzdYT5kKkb19m9dr5XL8ufodXNiyGbb+ARi5aTPsAgO7scccx3Edu5WzFEAgY+za7VRsXGK8AoaVPIEAjgFoYoy1vD9nAUOQczseAjDc+PhbY72vGY//wBhTAbhMRBcBRAM41ZXlieg5AM8BgKen5212neO6h/baVdT9vA26q1chi3kAFiNHgYRt/7hXpaYieekSNBQVInDefIQvW8ZTw3Mcd0d0JDApBdDqmu1b0AMQA7AGAMZYYfMJIloEQ8AjBjCyjfIMwEEiYgASGGPrjcedjQnewBirIKLm9dluAE7f1G+3VurtVHljP9YDhlU5bfSd4+4IxhiUqX+iYf8+kFgMm5mzIfHxbfN6vUaDzM8/ReZnn8LcuTdGf/8DnAcP6cYecxzH/beOBCYXARwhoj0AVM0HGWOftFeIMdZERHMArAbQm4hCALzJGJMzxj4H8DkRzQDwPzCktr/ZA4yxcmPgcIiIchljSe002drSgNsJHDpbnuPuKL1SiYY9u6DKyoRZ376wfngKhFZWbV5fX1CA5KVLcD09DX0eeRRRb62EuJNp6DnubiEUCiN9fX0VOp2OfHx8FNu2bSu0srIyWZp2Nze30JSUlBwXFxetTCaLkMvlqe1dHx0d7X/16lUziUSiNzMzY+vXry+MiYlRtFcmMTHR8oUXXvASiUTsbsv22lJHlv1WAEiCYeTDscXXLTHGdgGYCsO+O44Alt10yQ8AHm6jbLnx+1UAO2G4rQIAlca9epr37LlqPF4KwKNFFe4AylupurPlOa7H0ZSWoDrhS6iys2ExajRsZ81pMyhhjCF/83fYNzEeDcVFiP3sC8Ss+4gHJdx9pTkl/YULF7LMzMzY2rVrO/S51ha9Xg+drmunJG7atOlSXl5e9rx5866+8sor7h243v7FF1+8kpubm92RoESr1XZNR7vYLQMTxtgbjLE3YBj5WN3iebuIyJKIvIxPGwDkALAiopbjyg8CuNCiTK7xu0WLNPgWAMYCaF6qtQv/GWF5EsCvLY5PJyIJEfUB4AvgbCtd62x5jusxGNOj6eQJ1Py/fwOMwe7pZ2AROwxErf9oK65W4tgzT+GPN/4Fp4HReDDxILwenNjNvea4niU2Nrbx4sWLEgAYPXp0v+Dg4EAfH5/gDz74wAEAPvzwQ4e5c+fe+MN17dq1Ds8++6x7Xl6euG/fvsGzZs3yDA4ODiooKBAnJCTY+/n5Bfn6+gYvWLCgtekEt23YsGFNlZWVN5bF7dixw7p///4BQUFBgfHx8X3r6uoE69atc9i7d6/9e++95zp58uQ+er0e8+fPd/f19Q328/ML+vrrr+0Aw35AgwYN8ps0aVIff3//4Ly8PHGfPn2Cp02b5uXr6xs8efLkPr/88ovVgAEDAry8vEKOHj3apTs/d0RHVuUEwTBJ1MXwlEoBPMUYy7lFUTMACQAcAPQCUAxgBoDlRDQagAZADYxBAhE54D+3U5wB7DQmbhLBsJIn0XjuXQDbiGiusc6pAMAYyyKibQCyAWgBLGpeUUNEGwB8xRhL+TvlOa4n0jc2om7ndmguFUASFAyrSZMhkLa9DUZx4n6c/efr0MrliFrxNvxmz+HJ0bg77ljxIY9q5fUu/fCzl/aSD/cc06HNATUaDQ4cOGA9duzYegDYsmVLobOzs66xsZEiIiKCZs2aVTN37tzq4ODgIJVKVSqRSNjmzZsdEhISigCgsLBQ+vXXXxdu3ry5uLCw0Oytt95yM26wpx06dKjfd999Z9ve7sLtpaRvtnv3buv4+PhaAKioqBCtXr3aJSkpKd/a2lr/r3/9q/fbb7/t/MEHH1T8/vvvlhMnTqx7+umna7755hvbjIwM85ycnKyKigpRdHR04NixYxsBID093SI1NTUrICBAnZeXJy4pKZH++OOPlyIjI4vCwsICt2zZ0islJSX3+++/t121apXLiBEjCjr63neFjswxWQ/gn4yxQwBgDCq+BhDbXiFjbpDxN+cxAfBSG0UGA/jcWPYSgPA26r0OYFQb51YBWNXK8Wc7U57jehpVwUU07NwBvUoJq4mTIR0Q2WaQoa6vx7mVb+HS9p9hHxaGmHUfwaafTzf3mON6FpVKJQgICAgCgEGDBjW89NJLVQCwZs0a571799oCwJUrV8yysrKko0aNanrggQcafvzxR5vQ0FClRqOh6OhoRV5entjFxUU9atSoJgA4efKkxeDBgxtcXV21ADBt2rTq48ePW7YXmLQXlMyZM6evQqEQ6PV6pKSk5ADAsWPHLAoKCqTR0dEBAKDRaKh5v5yWTpw4YfX4449Xi0QieHh4aAcNGtR48uRJmY2NjT4sLKwpICBA3Xytm5ubKjo6WgEAfn5+ipEjR9YLBAIMGDBA/s4777jeXLepdSQwsWoOSgCAMXaYiNbeRhu1AM7f6iLG2J7bqJPj7ktMp0PT0d8g//0khI5OsJ/zJEROzm1eX3nmDE4texnyinKEvPgSQl9cDIGZWTf2mOPa19GRja7WPMek5bE9e/ZYHT9+3ColJSXXyspKHx0d7a9QKAQA8Nxzz1WtWrWqt5+fn3LWrFk38mvJZLIbE2Zvtffc7dq0adOlQYMGKV544QW3efPmeR48eLCAMYbY2Nj63bt3X26vbHt9adlnABCLxTcuFggEkEqlDACEQiF0Ol23D6t2ZPJrIRH9g4jcjV+vAyjqaAOMsVrG2C0DE47j2qerqUHN//s35L+fhDQyCvbznmszKNGpVEh9dzUOP/E4SCTEmJ+2I3zpMh6UcFw7amtrhTY2NjorKyt9amqqNC0tzaL53MiRI5sqKirEO3fu7DV37txWU2gMGzas6cyZM1YVFRUirVaLn376yX748OF/Gc24HRKJhH344Ydl58+ft/jzzz+lw4cPb0pJSbHMzMyUAEBDQ4MgPT1dcnO5uLi4hp9//tleq9WivLxcdPbsWcuhQ4c2/bWFnqcjgckzMKxW2Qdgv/Hx06bsFMdx/02ZlYnqhC+gq6qC9WOPw3riZJBZ6ynia/PycOCRh5Cd8BV8pj+BCXsT4Tggspt7zHF3nylTptRptVry8/ML+uc//+kaHh7+Xx/kDz/8cE1UVFSjo6Njq/MPvby8NG+++WZZXFycX2BgYHBYWJh81qxZbd7GAQxzTG7VL0tLS7ZgwYLKd99919nV1VWbkJBQOH369L5+fn5BkZGRARkZGX/Jhjh79uza4OBgRWBgYPDw4cP9VqxYUerp6dkzl+HchLp66Ol+EhUVxVJSUu50N7h7GNOo0ZC4H8o/z0Hk7g6bKVMhtLVr/Vq9Hrkb/43z76+B2Moag9a8B/dRo7u5xxx3a2lpaUXh4eE3bzfS440YMcJnyZIllXyH4c5LS0tzCA8P927tXJtzTIhoLWNsGRHtRCuJxhhjj3ZdFzmOu5m2shJ127dBd60KstihsBg+EtTGrr5NZWU49eoyVJ5KhvvoMRj0f2sgdXDo5h5z3L2pqqpKGBUVFRgYGCjnQYnptTf59Ufj98+6oyMcxxkwxqA8l4KGA/shkEphO3sOxH37tXlt4a+/4I833wDT6zB4zfvoO/VxvgyY47qQg4ODrrCwMPPWV3Jdoc3AhDF21vj9t+7rDsfdv/QKOdQXLkCZngZ1wUWI+/nA+pFHIbCwbPV6VW0tzv7PP1G8dw8cIiMRs+4jWHl6tXotx3Hc3aK9WzmpaGevGMbYAJP0iOPuI9rqaqjzcqHKz4WmqBhgeggsLWE5ZhzMhwxpM4NrxYkknHp1GZTXryP81eUImr8AgjZu83Acx91N2ruV81i39YLj7hNMr4e2rBSqvDyo8nOhu3YNACB0coYsNhYS/wCIXF3bDEi0SiXOv7saed9+A2sfHwzfsBH2IaHd+RI4juNMqr1bOd2agpbj7lVMo4a6oMAQjFzIA2tqAgQCmHl5wzxyICR+/hDatb7SpqXrGelIfnkJ6gsuwv/pZ9B/+esQSf+ySpDjOO6u1t6tnBq0fiuHADDGmL3JesVxdzldYwPU+flQ5eVCfakA0GpBEgnEvn6Q+PlD7OMLgXnb+9q0pNdqkf3Vl0j/+ENIe/XCyE2b4TJ0mIlfAcfd24qLi0ULFy70TEtLk4nFYubu7q769NNPS8LCwlSdqXfKlCnezfvVtDyelJQk27hxY69vvvmm05luP/nkk14pKSkWmzZtKm7rmry8PHF4eHiIt7e3kjEGmUym/+abby6Hh4d36vV1h/Zu5fC1hhzXQYwx6K5dhSovF6q8PGjLSgEAAhtbmA+IgsTfH2ZeXiBhR3aB+I+GokIkL3sZVefOwWviJAx8exUktrameAkcd9/Q6/WYPHmyz4wZM67v2bPnEgAkJyebl5eXm3U2MGnLsGHD5MOGDZObou62eHh4qJrT7r///vsOK1ascNmxY0dhd/bh72gv86vUuLuuRRtfHHdfYzod1JcvoSFxH65/8hGqv/wcTUd+A8BgMWIU7J9fhF4vvQyr+AkQ9+13W0EJYwwXf9iKfRPGoy7/AmI++gSxn37OgxKO6wJ79uyxEolEbPny5deaj8XExCjGjx/fqNfrMX/+fHdfX99gPz+/oK+//tquuczAgQP9J0yY0Nfb2ztk4cKFbl9++aV9aGhooJ+fX1BWVtaNtPCHDh2yioyM9Pf29g7ZunWrTXP5ESNG+ADA0qVLXadOneodHR3t7+7uHvrOO+84NZf94osv7ENDQwMDAgKCZsyY4aXVGpK1fvzxx728vb1DBg4c6J+cnNz6Ur121NfXC21tbXWAYTQlMjLSPygoKDAoKCjw0KFDFgBQVFRkFhUV5R8QEBDk6+sbnJiYaAkAO3bssO7fv39AUFBQYHx8fN+6urqOZI3/29r7TfkzgHgAWTDc0mmZGIEB8DRhvziuR9IrFVBfvGi4RXPhAphKCQhFEPftC0nsUIj9/CG0supUG8qqKpz5x2soPXwIzjExGPL+Oli4dvsGnxzXLU4tf8WjLi9P1pV12vj7y4e890Gbt0zS09PNw8PDWx292LRpk21GRoZ5Tk5OVkVFhSg6Ojpw7NixjQCQm5tr/vPPP19ycnLSenl5hUokkqqMjIyct99+22nt2rVOGzduLAGAkpISydmzZ/Oys7Mlo0eP9n/ooYcybm7n4sWL0uTk5Lza2lphYGBgyKuvvnotKytL8vPPP9unpKTkSiQSNmvWLM+vvvqq16RJk+rfffdd13PnzuXY29vrYmJi/ENCQuQAsGXLFps//vjD4qOPPiq/uY2SkhJJQEBAUFNTk0CpVAqSk5NzAcDV1VV74sSJfJlMxjIyMiRPPPFE38zMzJyNGzfajxo1qm7NmjVXtFotGhoaBBUVFaLVq1e7JCUl5VtbW+v/9a9/9X777bedP/jgg4q/969za+1Nfo03fvcwVeMcdzfQ1dYYJq7m5UJTVAjo9SCZBSSBgZD4BxhGQ8St71vTUY2lpSg/dhTlR4/gSvLvYHqGAf/zJgKefgYkMOkfJxzHtXDixAmrxx9/vFokEsHDw0M7aNCgxpMnT8psbGz0oaGhTV5eXhoA8PT0VMXHx9cBQHh4uOL48eM3/iKZMmVKtVAoRGhoqMrDw0N1/vz5v8xSHzt2bK25uTkzNzfX2tvba0pLS0WJiYlWmZmZsvDw8EAAUCqVAicnJ21SUpLF4MGDG1xdXbUA8Oijj1bn5+dLAWDmzJl1M2fOrGvttbS8lfP111/bPfPMM14nTpy4oFarae7cuV7Z2dnmAoEARUVFEgAYPHhw0/z58701Go3gscceq4mJiVFs3brVqqCgQBodHR0AABqNhiIjIzu1MeGttDu2TEQCxpje+NgVQDSAi4wxngGPu2cxpoe2vMI4XyQXuquVAAChgyNkQ2IMS3rd3DsVMOg1Glw7l4KyI0dQfuwI6i5cAABYenrCZ9p0+M6cBRtfvy55PRzXk7U3smEqoaGhil9++aXVpXDt7R8nkUhunBQIBJBKpaz5sU6nu3FX4ebMy61lYm5Zl1AohFarJcYYTZ069frnn39e1vLa7777zraz2ZyfeOKJ2sWLF3sDwKpVq5ydnJw027dvv6zX62Fubh4JAPHx8Y1JSUl527dvt3nqqaf6LF68uNLe3l4bGxtbv3v37sud6sBtaPM3KxE9A6CKiIqNj48DmAVgJxG90l0d5LjuoFepoMrLRf3uXbi+bi1qNiRAfjIJAnNzWI4dB/sXXkKvRS/CcvRYmHl4/q2gRHG1EgU/bUPSgvn4ObI/Dj8xDXnfbIS5kzMG/M+bmHT4KCYfO4Got1byoITjTGjSpEkNarWa1q5de2ORx/Hjx2V79+61jIuLa/j555/ttVotysvLRWfPnrUcOnRoU3v13WzHjh12Op0OWVlZkpKSEkl4eLiyI+XGjx9fv2fPHruysjIRAFRWVgrz8/PFw4YNazp9+rTVlStXhCqVinbu3Hnr/AI3OXTokJWHh4cKAOrq9W8+vwAAIABJREFU6oQuLi4aoVCIL774opdOZ9gsOT8/X+zm5qZZtmxZ1axZs6r+/PNP2fDhw5tSUlIsMzMzJQDQ0NAgSE9Pl7TTVKe1N2KyFIAvACsY5pl4M8auEZEFgLMAPjBlxzjOlJheD21FOdQFF6EuKICmtMRwi0YshtjH13CLxscXAtnfv/Wt1+lwPe08yo8eRfmxI6jONAw0mvfuDa8HJ8J1xEj0jnkAZpa3PY+N47hOEAgE2LVrV8HChQs9Pvroo94SieTGcuH4+PjG5ORky8DAwGAiYitWrCj19PTUpqend7h+Hx8fVXR0tP//Z+/NwyMr67zvz11rUmuWSlWSztorvW/pBpp9U/QRXBAXQBk3tHUWRx9E3/GZedDRYXRQ5BpleZVXmEEZZUQZFJ1BQIQGuht6gWbtJemks1eWWpLUer9/nJNKJZ1Opztrd/8+13Wuc+rUue/c5ySpfPNbw+Gw/Y477mhyuVzHNsPksXHjxqGvf/3rRy677LKl2WwWu92u77zzzsOXXXZZ/JZbbmk955xzlpeVlaXWrFkzMGyhmUyMidYau92u77777iaAL37xi53XXHPNol//+tfF559/frSwsDAL8Ic//MF75513lttsNu1yuTIPPvjgocrKyvQ999zT+JGPfGRhMplUAP/wD/9wZKaylwDUscxWSqldWuv15vEerfXa8d47k2loaNA7d+6c62UIkyTT10fy4AFDjBw8iB4aBMBWUYFj4WIcixYZ1hDbiaX05pPo7aX1mT/R+tRTtD3zNIneXpTFQmDDRiovuYQFF19K0fLl0mRPOKPZs2dP09q1a7vneh3C3LFnz57A2rVr68Z7b6JP4EKl1GoMd4/DPFbmJuUmhXlPNpEg1XiI5IEDJA8eIBM2PgctXh/Os87CsWgxjvqFWNwnn/2utab3tX20PvUUR55+kvCuXehsFmdJCZUXX0LlJZdSccGFkuYrCIIwSSYSJt3Aj8Y5Hn4tCPMKwz3TZlpE9pNqNtwz2Ow46uoobGjAsWgx1kDZlCwWqWiUtueepfWpJ2l9+ikGOzsBKFmzhlV/+VdUXnwpJWvWSFM9QRCEk2CidOHzp+MLKKXqgIu11j81X38O+AKQAWLATVrr18YZdyXwA8AK/FhrfZt5vgT4D6AOaAQ+pLXuNd/7GvApc+6/1lr/YZx5pzRemF9k+vtyFpHkwQPowRH3jOvc86bFPaO1JnJgv5lB8xSdO7aj02nsXh8VF1xA5SWXUnnRxRSWlU3XbQmCIJyxTNQr5xyt9QsTvO8BasYTFXnXbAW+CLiUUn8BfAT4mdb6bvP9q4HvAVeOGWcFfghcAbQAO5RSj5pf66vAH7XWtymlvmq+vkUptcKcfyVQCTyhlFpqVq/NZ6rjhTkkm0yQamzMBa2OuGe8uZoijoULsbinFlCaHhyk4/ltHHnqKVqffop4i5HR6F+2jOWf/gyVF19K2YYNWOz2Kd+TIAiCMMJE/0Zer5T6LvA48BLQhRFbshi4xNwfM21YKeUFbgWuApYDTwNxrXU07zI34zcKHK6XctCc6yHgvcBr5v5i87r7zXlvMc8/pLVOAIeUUvvNeZ4fM/dUxwuziM5mSbe3jWTPNDdDNmO6Z2op3Gi6Z8qm5p7RWhNraqL1T0/T+vRTdDy/jUwigbWwkPIt57Fy61YqL7oE94IF03h3giAIwlgmcuX8lVIqAFwLfAyoAAaB14H7tdZPH2fuLOAAfOZ8jcNvKKW+gJGO7AAuHWfsAiC/6E4LcLZ5HNJat5lztimlgnljXhgzZry/IlMar5S6CbgJoKZGqvLPBJn+fjNOZIx7prwC17nn4li0GHt1Nco2NWvFQEc7Hdu20b7tOdq3bWOg1ahp5K2rY/F117Pg4ksJnr0Zq1NivQVBEGaLCR3vWutu4C5zOyG01nGl1MeBbwPlSqlVwN9rrQe01j8EfqiUug74OnDjmOHj/et7vDzwkxlzwuO11vcC94KRLnwC8wvHIJtIkGpqNGNF9pPpNt0zHi/OpcuM7JlpcM8k+vroeOH5nBiJHNgPgMPvJ3TuFlZ+bivl552Pb+HCKd+TIAjzm8OHD9s+//nP1+zZs8flcDhydUymWp/jmmuuqXvPe97T/4lPfKI3//wzzzzjuu+++0p/+tOfTrnS7Z133lm6c+dO9wMPPHD4WNe8+eabjrVr166qq6sbSqVSas2aNfGHHnqoKb/i7Hh89rOfrfrjH//ov+yyy/rvueeelqmu9WQ4+YjASaC1flQptRfDndMAfBn4Zt4lDzG+6GkB8nv0VAHDxWM6lFIVprWjAuicxJh8pjpemCLZoUFSTU2kmppINjWSbmsDnR1xz2xowLFoEday4JTcM+mBATp37KB927N0PL/NKHCmNdbCQoKbz2bRhz5M+ZYtFK9YKf1oBOEMIpvNcvXVVy++7rrrwo899thBgG3bthW2trbaZ6pw2IUXXjhw4YUXjts4cKYY7pWTTqc5//zzl953333FW7du7ZlozIMPPljW1dW1u7CwcFL/eKdSKezTHGs3Y8LEDI4tNV9GMVxAJUqpJVrrt83z/wt4O2/MG1rrs4AdwBKlVD1wBCMo9TrzskcxLCy3mfvf5J3/mVLqexjBq0swKtSOZarjhRMkOxAn2dREqqmRVFMj6fYOQIPVin1BFa7zL8BRV4e9pmZK7plMMkl49y7an99G+3PPEd69i2wqhcVuJ7B+A6v/5ouUbzmP0rXrsE6x6Z4gCKcujz32mNdms+mvfOUrXcPntmzZMgiGaNm6dWvVk08+6VdK6ZtvvrntM5/5TO9jjz3mvfXWWyvLyspSr732muvd73537+rVqwd/9KMfhcwy8QdWrlyZAKP8+7/+678Gw+Gw/Z/+6Z+aP/rRj/Y/9thj3ttvvz301FNP7f/Sl75U2dzc7GhqanK2trY6Pve5z3V8/etf7wT40Y9+VHLXXXeFUqmU2rBhQ/yBBx5ostls/OAHPyj9/ve/X1FWVpZatGjRkMPhmLTF3mazsWHDhviRI0fsAOl0mi984QtVzz33nDeZTKrPfOYznTfffHP3pZdeunhwcNCyfv365V/+8pfbLrrooviNN95YFw6HbaWlpekHHnigccmSJclrrrmmrri4OP3KK6+41qxZM+D1erONjY2Ojo4Oe2NjY8G3v/3t5ueff97z5JNP+kKhUOqJJ57YfzxLzaj1TvbCk8AO3AMEMATKYQxx8RWl1OVACujFdOOY8SwKQGudVkr9JfAHjHTh+7TW+8x5bwN+oZT6lDnnteaYfUqpX2AEyKaBLwxn1CilfgzcrbXeeTLjhRMjE4saFpHGRpJNjWS6TKOUzY69ugr3xRdjr63DvqAKNQWlrbNZel/bR/tzz9H+/Da6dmwnPTAASlGyahVnffJTlG85n7KGBmxTKC0vCMLMEfnNI9Xpzs5p/QW1BYMDvve+/5guk7179xauXbt2XOvFAw88UPTKK68Uvv766/va2tpsmzdvXv6Od7wjBvDGG28UPvzwwweDwWC6trZ2tdPp7H7llVde/+Y3vxm8/fbbg/fdd18zGKXgt2/f/uZrr73mvPzyy5e9973vfWXs19m/f3/Btm3b3uzr67MuX7581c0339y1b98+58MPP1yyc+fON5xOp77hhhtq7r777tKrrroqctttt1W+9NJLr5eUlGS2bNmybNWqVQMwcUn6YQYGBtRLL73kvvPOO5sB7rjjjoDf78+8+uqrrw8ODqpNmzadddVVV0WefPLJ/S6Xa/1wR+JLL7108XXXXRf+q7/6q/Add9xRunXr1uonnnjiAMCBAwcKnnvuubdsNhtf+tKXKpuampzbtm176+WXXy649NJLz7r//vsP3H333S1XXHHFol/84hf+j33sY32T/v4d7wKl1IvAfcDPtdaRyU5s1ga5cmwdE+BvjjHkHIwU4eHxvwN+N868YeCyY3zNbwHfGuf8p6cyXpiYTKQ/J0JSTY1kwmEAlMOBvbqGgtWrTSGyAGWdYj2RgwdyMSIdLzxPss/4WfctXszCD36I8i1bCJ5zDk6/VFoVBOHE+fOf/+z90Ic+1GOz2aiurk6fffbZsWeffdbl9/uzq1evjtfW1qYAampqEu9617v6AdauXTv4pz/9yTs8xzXXXNNjtVpZvXp1orq6OrF79+6jIujf8Y539BUWFurCwsJ0SUlJqqWlxfb73//e++qrr7rWrl27HGBoaMgSDAbTzzzzjPucc86JVlZWpgE+8IEP9Lz11lsFANdff33/9ddf3z/evQz3ymlqanK+613v6j377LMHAZ544gnfG2+84Xr00UeLAaLRqPW1114rOOuss5L543ft2uV+/PHHDwBs3bq159Zbb60afu8DH/hAry2vPtTll1/e73Q69ebNmwczmYz64Ac/GAFYuXLl4KFDh07IRD2ZvxI3Ap8AdiultgH/n9b6jyfwNfqA3ce7SGv92AnMKcwRWmuyfX05EZJsbCTbZ8R4KWcB9toaCtZvxFFXh62iAmWZWvXTeGurIUK2PUf7tucY7OgAwFW5gKor3kH5lvMInXsurlD5lO9NEITZZyLLxkyxevXqwV//+tfjdug9Vv84gHx3hMVioaCgQA8fDzfVA46KjRsvVi5/LqvVSjqdVlprde2114Z/+MMfHsm/9t/+7d+KTibebjjGpKmpyX7RRRcte/DBB/3XX399v9Za3X777YevueaaSRsbxuLxeLLj3Y/VasVms2mLGbdnsVhIp9MntPjjRvxprd/QWt+CEXPxn8ADSqlDSqn/o5Q67r+lWus+rfVxhYkwP9Fakw53M/jSTvof+U/Cd3yP8J3fJ/qbR0i8+Sb28nI877yS4pu2EvjKVyn66A24zzvfcNOchCgZ6umh6beP8eLffY1HL7mQX593Di/c/GVan/kTwU2b2fytf+Lqp5/hfc9u49zv/Av173u/iBJBEE6Iq666KppMJtXtt98eGD73pz/9yfXb3/7Wc9FFF0UffvjhknQ6TWtrq2379u2eCy64IH4i8//qV78qzmQy7Nu3z9nc3Oxcu3bt0GTGXXnllZHHHnus+MiRIzaAjo4O61tvveW48MIL4y+88IK3vb3dasazjCuqjkVtbW3qG9/4Rst3v/vdCoArrrii/6677ipLJBIKYO/evc5IJHKUHli/fn38xz/+cTHAPffcU9LQ0BA7ka97skzKrm5WRf0ERnbNb4AHgfOBJ4ENM7Y6YdbRWpPp6spZRFJNjWRjxs+ixe3BXluLvfZ8HHV1ZlGzqWWzJHp76XppJx0vvEDHtufofd0oJGzzeAidfQ5LP/ZxQlvOp2jpUsmcEQRhWrBYLDz66KMHPv/5z1ffcccd5U6nM5cu/K53vSu2bds2z/Lly1cqpfStt97aUlNTk967d++k51+8eHFi8+bNy8LhsP2OO+5ocrlckwr83Lhx49DXv/71I5dddtnSbDaL3W7Xd9555+HLLrssfsstt7Sec845y8vKylJr1qwZGLbQTCbGBOCGG27o+9a3vlX5+9//3vO3f/u33Y2Njc7Vq1cv11qrkpKS1O9+97sDY8fcddddh2+88ca6H/zgB+XDwa+TfghTQE1ktoJcjMkgRpzJL7XWg3nvPaq1vnpmlzh/aWho0Dt37pzrZUwJrbOkOzpzIiTZ1IgeMGLCLF4f9ro6HLV12GvrsJaWTil9FyDW0kLXju107txB147t9L9tJGVZHE7KGjZSvuV8yrecR8nq1Vim0N9GEIT5y549e5rWrl0rzWDPYPbs2RNYu3Zt3XjvTeaT/2Na67fyTyilarTWh89kUXIqk+ntGWl8d+gQesjQmpaiIpxLlmKvrcNRV4elqHhqZd6zWfreeouunTvo3LGdrp07GGg1RL3d66VsYwN173s/wYZNlK5dKxVWBUEQhEkJk4c42l3z63HOCfOU7NAQqcZDI43veo36Oha/H+fy5Tjq6rHX1mKdYiZLJpEg/MrenBDp3rmTZMSIrSoMhQhu2kzZZ7cSbNiEf9kyLNapBcYKgiAIpx8TdRdeitF8z292AR7Gh9HMT5in6GyG9JEjuRLvqZYjoLNG+m5dPYXnnItj4aIpu2aSkQhdL79E1w5DiIT37CGbNIom+hYtpubd/4uyhk0EN2/GXVU9ZTeQIAinDdlsNqssFou09TgDyWazCqOf3rhMZDFZCXwAKMIsQmYSBT47LasTpo10Tw/JA/tJHTxA8tBBdCIBSmGrrDQqqy5ahL2qGjUFK8VAR7vhktmxk64d2+l943XQGmWzUbJyFUs/9nGCmzdTtrGBgtLS408oCMKZyqtdXV0rysrK+kWcnFlks1nV1dXlB1491jUTdRd+BHhEKXW+1vrZmVigcPJkhwZJHjqU68Kb7TVqiVj8RThXrjIa39XXYyk8uYKKw8XMuraPBKrGmo1yAzaXK1fiPbhpM4F166WyqiAIkyadTn+6vb39x+3t7auYRNkK4bQiC7yaTqc/fawLjpmVo5T6stb6dqXU9xm/y+6Xpm2ZpyizmZWjMxlSR1pyQavpIy2GtcLhxF5fj2PhIhyLFmMtKTkpl0k2laJn375RgaqJHiMWxVlaSrBhE2WbNhNs2ETxihVYprlpkyAIZxTi1xWOyUSunOGc5mOaW4SZQ2s9kj1zYD+pxkMj7pkFC3BdcCGORYuNQmYn4Z7JJBJ073qZjheeNwJVd+0iM2hk53hqalhwyaU5IeJduFDiQwRBEIRZYSJXzq/N/U9mbzlnNtnBQZKHDuaCVrNmHxhLURHOVasNq0j9QiyFhSc+dzpNz6uv0r7tWTq2baNr5w4yptApXr6CxR/6MGUNmyjbtEkqqQqCIAhzxkRZOY8wjgtnGK31B2ZkRWcQOpMh1dJs1BM5cIB06xHDPeN0Yq9fiGPL+TgWLcJafOLumeEaIh3bnqV92zY6t79IKhoFoGjZWSy+7nrKz91C8Oyzcfj8M3F7giAIgnDCTOTK+ddZW8UZRrqrk9gfnyB16BA6OeyeqcJ14UU4Fy3GtmDBCfeZ0VoTa2qi3Wx21/HC8yTMLr/eujpq33MVoS1bCJ19LoVlZTNxW4IgCIIwZSZy5ZxIB2HhBFB2B+nODgpWrzHSeOvrsRScuHtmoL3dECHPb6N923O5qqqFoRCVF15EaMt5hM45F09V1XFmEgRBEIT5wURZOT/XWn9UKbWL8bNyzvjKr7PdK2eop4fOF56n/flttD/3HNFDBwFwFBUROudcys87n/Jzt0iwqiAI8x35gBKOyUSunJvN/QdnYyHC0aRiMTq3v0j7tm10PL+N3tf2AWBzuwluPpsl111PaMsWis9aLp13BUEQhNOCiVw5Leb+gFKqDNiEYTnZqbXumqX1nVFkEkN0vfwy7c8Z7pnwnt3oTMbovLtxI2u+9L8pP+88SlevkToigiAIwmnJcZv4KaU+AXwD+BOG+e1updTfa63vn+nFne5k02l6XtlL+7ZttG97lq6dL5FNJlBWK6Vr1rLis1sp37KFwMYGbAXSnkgQBEE4/ZlMd+GvAhuGrSRKqQDwHCDC5CTpe+tNdv/zbXRsf5F0LAZA0VnLWfqxjxE6dwuhzWdj93rneJWCIAiCMPtMRpgcAfryXvcDLTOznDMDm8tN5OBB6t/7PkOInHOuNL0TBOGUIJPVtMVTKGCB1zHXyxFOQyYqsPbX5uFh4Hml1K8xYkzeB+yYhbWdtniqqrj6qT/N9TIEQRAmJKs1XQNpmqNJY4skaY0lSWtYHSjkxlWBuV6icBoykcVkuApXs7k5zde/P5EvoJSqAy7WWv/UfP0l4NNAGugCPqm1bhpnXCMQBTJAWmvdYJ4vAf4DqAMagQ9prXvN974GfMoc89da6z+MM++UxguCIJyOaK3pGcrkREiLuSUyRrUIh0VR5XVw3gIv1T4HNWItEWaIY9YxmZbJldoKfBFwYTQF/AiwHHhRaz1gvn+x1vrD44xtBBq01t1jzn8H6NFa36aU+ipQrLW+RSm1Avg5sBmoBJ4AlmqtM9M5Pp/ZrmMiCIIwXUQSIyJkWIjEU1kArAoqPQ6qvebmcxB02bAohdaaxnCUVCbL0lDRyX55qWMiHJPJZOUEgC8DK4FcaojW+h3HGecFbgWuwhAjTwNxrfVTeZe9ANxwgmt+L3CxeXy/Oe8t5vmHtNYJ4JBSaj+GyHh+OscrpW4CbgKoqak5waULgiDMPgOpLC15IqQ5mqQ/YfzPpYByt52VpYVUeR3U+ByUu+3YLIYIae6NsX3/EXY1d7O7uZs9LWH6B5O8b10dP/n4JXN7Y8JpyWSCX/8deAR4P/AF4EagfRLjsoAD8AForRvHueZTwOPHGK+B/1ZKaeAerfW95vmQ1rrNnLNNKRU0zy/AEDrDtJjnxjKl8eY67gXDYnKMtQuCIMwJiUyW1mhqlAjpHkzn3g8U2ljod+asIZVeO06rBa01rX1xdh1qY3dLN3uaw+xu6aYnngDAZlGsrCzhfWvrWFcdYHN98FhLEIQpMRlhUqa1vkcp9QWt9R+VUk8CTx1vkNY6rpT6OPBtoFwptQr4e631AIBS6gagAbjoGFOcp7VuNYXD/yil3tBaPzPBlxzPNHgiwmGq4wVBEGaVdFbTHk9xOJLMWUTa46ncB5ffaaXa62BTuZtqr4MqrwOX3agS3dY/wO7mDh4yrSC7m7vpig0BYLUolpcX8+5VNayrDrC2qpQVFcUU2CfzJ0MQpsZkfspS5r5dKfVOoBWonszkWutHlVJ7Mdw5DRguoW8qpS4H/g64yHSdjDe21dx3KqUewXCrPAN0KKUqTGtHBdBpDmkZs64qc61jmep4QRCEWSerNZ0DaZojI5aQ1lgSMzYVl81Ctc/BykBhzhricxpdyjujg+xp7uI3OwwryK7mbjoigwBYlGJZyM9ly6tYV1XKuuoAqypLKHSICBHmhsn85H1bKeUH/jfwQwzXzM0TDwGllAcYLs4RBV4HSpRS64F7gCu11p1jxryhtT5LKeUGLFrrqHn8DozqswCPYriTbjP3v8k7/zOl1PcwgleXANvHWdpUxwuCIMwoWmv6zODUw5GR4NThDBmn1ciQOb/KmxMhJQVWlFKEY0PsaQnz+11GTMjulm5a+wYAUAoWl/m5cEkl66tHRIjbKS0uhPnDcYWJ1vpR83AvcMEJzG3HECABDIFyGLgOI+DUA/zS7IB7WGt9tRlkO+xOCQGPmO/bgJ9prYfTlG8DfqGU+pQ557XmOvcppX4BvIaRivyF4YwapdSPgbu11jtPZrwgCMJMMpDK5OqEHDb30TEZMhtDbqp9hggZzpDpG0iwuyXM06+YIqQ5THNvLDfvojIf59aXs84UIasXlOItEBEizG+OmS6slPqy1vp2pdT3GSfWQmv9pUl9gTF1TCa47j3AQq31nZOZdz4g6cKCIJwoqUyWI7FUzhIyNjg16LJRbWbHVHsdVHoc2CyKyFDSCEg1rSB7msMcCkdz4+pKvYYAqQqwrjrAmqoS/IXO8ZYwH5B0YeGYTGQxOWDuXx3nvRMJCu0Ddh/vIq31YycwpyAIwrwnk9V0DKRGWUPaYymy5vt+p5Uar4PN5YY1pMrroNBmYSCZ5tUjYR7ffZhdzWF2NXezv7M/N291sYd11aXccM5S1lYZYqTYPW9FiCCcEMcUJlrrX5v7n4x9Tyl122S/gNZ6UsJEEAThVGZU5VRThLREk6Syxv9xhTZFtdfBJTW+nEvG77SSTGd4ra2XZ19vZXdzN7sOd/NGRx8Zc1zIW8j6mgDXbljIumrDGhLwSLdx4fTlZMOur8PoOiwIgnBGEkuODk5tzqucalNGg7uzK9w5l0xpoQ2tNW919PPywRbuN0XIvtYekhljXLHLybrqUt65spr1NQHWVQWoLHLP5W0KwqxzssJE/IOCIJwxJDJZjkRTHI4mcum6PUMjlVNDbjsrSgtzsSHlbjtWBQe7I+xu7uBXpgjZeyTMQNKIJ/E47ayrKuWmC1YYIqQ6QG2JBzPoXxDOWCbqLuw71lsztBZBEIQ5J79o2bAlpCOvaFmx00q1z8G5lYYIWeBx4LQqjvTF2dXczRO7jDohw6XbAQpsVlZXlXD95iU5EbKkzI/FIh+ngjCWiSwm+zCCXPN/c4ZfS0VUQRBOebJa0zWQHuWSaYslSZufcG67hWqvg9XDRct8DrwOK53RQXY3d/Pwa925HjLDVVPzS7evryljfXWAZeVF2K2WObxTQTh1mCj4dVLVXQVBEE4FtNb0JjKjKqeOLVq2wOPgvDFFyyJDSXY1h/nD7iZ2NXexuznMkb44YBQsWxYq4vLlVayrDrC+OsDKSindLghTQX57BEE4LRkOTs23hsTHK1pmWkKCLhtDqQyvHAnzwutHuKvZsIYc6Irk5lwY8HJOfYh11aWsrzEKlnmkaqogTCsiTARBOOUZSmdzTeyG03V7EyPBqUGXjeWlBUZwqtdJhceO1prX23p5+VAz/z5Omm6F38X66gAf2bSY9aY1pMgltUIEYaYRYSIIwilFOqtpjSVH1QvpGkjnAt9KCqzU+BycZ1pCqjwO7BbF/q5+djV38F8vGpaQV4/0MJQ2xEuxy8n66gBXrqoxREhNgHKfa+5uUhDOYI4rTJRSF2utnx5z7nqt9YMztipBEASM4NSOeGqUJaQtnsp11PXaLVT5HKwLukxriAOX3UJLr5Eh8297unIZMtEho1G622FjTVUpnzzvLNbXGJaQulKvpOkKwjxhMhaTbymlXga+gtF8714M66gIE0EQppXBdJbDkSSN/QmaIkkORxIMmSqkwOyoe2GVl2qfIUL8TivdsSF2NXfz6BuGJWRXczfdZoaM3WphZWUJH9ywiPU1ATZUB1ga8mO1SIaMIMxXJiNMLsAQJbsAK/ANrfW/zeiqBEE47dFa0z2YpjGSpKk/QWNkpF6IAircdtYYfjJHAAAgAElEQVSHXNT6nNT4HAQKbcQSKfY0h3n6lWZDhBzuznXTVQqWBo0MmfXVATbUBFhZWYLTZp3T+xQE4cSYjDDxAWuBFqACCCmllD5WW2JBEIRxSGayNEeTNPYnaYwkaOpPMpA2smQKrIpav5O1ZYXU+Z1Uex1Y0Lza2sNLbzfxE1OE7O/qZ/iTp7bEw8baAJ8+/yzWV5expqoUb4FkyAjCqc5khMl24F+01vcqpdzAd4E/A+fP6MoEQThlGa4Z0mS6ZBr7E7TmddUNumysDBRS53NQ63cSdNnoiAyyo7GTf9/bxY6mTvY0h3PBqUFvIRtqAnxww0LWm43sSqWRnSCclkxGmLxTa30IQGsdBz6vlLp0ZpclCMKpRDqrORJN0pgXHxJJGqLCblHU+IyuurV+B7U+BzYFe1vCvPR2G/c2dbKzqYuWXqNomcNqYU1VKZ847yw21ZaxsbaMBUVuCU4VhDOE4woTrfUhpZQfWAQM/4syNKOrEgRhXhNJZGiKJHLxIS3RkTLuJQVWFhU5qfM7qPM5KXfbae+Ps6Opi5+90sWOxk72toRzHXWrit001Jax9cKVbKw1XDISFyIIZy6TSRf+JPBlYAHwCrAJeAG4eEZXJgjCvCCT1bTFU4YQ6U/SFEnkOutaFVR7jTLudT4HtT4nDotmT0uYnW+38f82GtaQtv4BwGhmt646wE0XrKChroyG2iAVfqkXIgjCCJNx5fwt0AA8r7W+QCm1Evj6zC5LEIS5ZDCV5c9HohzoS9AcSZI0q6H6HBZqfU7OW+Ckzueg0mOnrT/OjsYufra3kx2NXbza2kPKtIbUlnjYsrDcFCFlrKoswSHWEEEQJmAywmRIaz2olEIp5dBa71NKnTXjKxMEYdbJas1L7QP89mAf8VSWBR47myvc1JpBqk41Yg35cWMnLzV10REdBKDQbmV9dYCtF62kodYQIiGpnioIwglyTGGilLJprdNAm1KqCPgv4A9KqR6gY7YWKAjC7HAkmuRXb/fSFElS63Pw6dVFpJIJdjR28fO9hkvm1daeXC+ZhQEvFy6tZJNpDVlRUYLdKoXLBEGYGupY5UiUUi9rrTeMOXcZ4Ad+q7VOTOoLKFUHXKy1/qn5+kvAp4E00AV8UmvdNM64K4EfYBR1+7HW+jbzfAnwH0Ad0Ah8SGvda773NeBTQAb4a631H8aZd0rj82loaNA7d+6czGMQhHnLQCrL7w/183xrDJfdwrvrfbzZ1MZ3/ntXLjbE7bCxvibAprqgaQ0JEpB0XeHkkRQr4ZhMJEx2aa3XT2lypbYCXwRcwAHgI8By4EWt9YD5/sVa6w+PGWcF3gKuwCjstgP4qNb6NaXUd4AerfVtSqmvAsVa61uUUiuAnwObgUrgCWCp1jozZu4pjc9HhIlwKpPVmp3tcX57sJ+BVJYtCzyUqCH+72+2s/dID5vrgny4YRENtUGWVxRJGXdhOhFhIhyTiWJMykzrxrhorb830cRKKS9wK3AVhhh5GohrrZ/Ku+wF4IZxhm8G9mutD5pzPQS8F3jN3F9sXne/Oe8t5vmHTEvOIaXUfnOe58fMPdXxgnDK0xJN8ojptqnzOdhS7+RHT+zmkd2HqCxyce8NF/GB9fVSO0QQhFlnImFixWjad7KfTFnAgVHSHq114zjXfAp4fJzzC4DmvNctwNnmcUhr3WbO2aaUCuaNeWHMmAXjzD2l8Uqpm4CbAGpqasaZXhDmL/luG7fdwvsX+/nzqwe46qFXAPjKO9bxl5eswu2U0u6CIMwNEwmTNq31N052Yq11XCn1ceDbQLlSahXw91rrAQCl1A0YacgXjTN8PDF0vN48JzPmhMdrre/F6LBMQ0OD9AsSTgmyWrOjPc7vTLfNeQs8JKO9fO6+Z2ntG+D96+r5h/c0UF3imeulCoJwhjORMJmyDVdr/ahSai+GO6cBo1DbN5VSlwN/B1x0jCDaFqA673UV0GoedyilKkxrRwXQOYkx+Ux1vCCcUrREk/zqrV4OR5PU+x2s8Cq++/g2XjzUyZoFJdx7w0Wcu7B8rpcpCIIAwETRbJdNZWKllEcpVWu+jAKvA16l1HrgHuBqrXXnmDFvmIc7gCVKqXqllAMjaPZR871HgRvN4xuB3+Sd/4hSyqmUqgeWYDQgHMtUxwvCKcFAKsN/vtXDD17qoHcozbtrPbz55ttce9dvOdAV4Y4PnccTf3uViBJBEOYVx7SYaK17pji3HUOABIBS4DBwHUbAqQf4pRlYd1hrfbVSKoBppdFap5VSfwn8ASPW5T6t9T5z3tuAXyilPmXOea05Zp9S6hcYAbJp4AvDGTVKqR8Dd2utd57MeEE4lchqzY42I9tmKJ3l3Eo3zS1H+MS9T5FIZ/jCRav48hVr8RU65nqpwimK1pp0No3dKrFIwvRzzHThafsCY+qYTHDde4CFWus7Z3RB04ikCwvzjeaIUSStOZqk3ucgaE3wnd9u52B3lHeuqOYbV29icdA/18sUTgGSmQTRZIRIop9IMkI02U8k0U80GSGajLCwaAmX1r7zZKeXdC/hmEymJP1U6QN2H+8irfVjs7AWQTgtiacyPH6wnxfb4ngcFi6qKOD+p1/mqTdbWRL084vPXMFly6vmepnCPCKjM8STMSLJ/jwBYgqPRD9DmdFN5B0WBz6nn+KCUmp89ZS7K+do5cLpzowLE631pISJIAgnTlZrtrcZ2TZD6SybQoW8/MYBPvWr13E77Hz7fZv55HnLpVT8GYjWmqHMIJGEae1I9hNNRHLiI5aMovMSDy1Y8Di8+Jx+AkWL8Tn8+Jx+vA4fPocfp00q/Qqzw2xYTARBmAEORxI88nZfzm3DQB//z4N/pn8wycfPXcrXrtwgZeNPc9LZdM7aYYgPw9oxLD5S2dSo6wttLnwOPyF3BUuKz8qJDq/Th9vuwaJEwApzjwgTQTjFiCcz/O5QP9tNt82GYsWP/rCN19v7OH9ROd9+/9msrCyZ62UK04DWmngqdpTgMOI9Igyk46Out1lshtBw+Kj0VI+yeHgdPglWFU4JRJgIwilCVmtebIvzuOm2WRtw8j8793Hn3kZqSjz89C8u4T2ra6WM/ClGIpMYJTryg02jySjZvORAhcJt9+Bz+qn21easHT6HH5/DT4GtUL7/wimPCBNBOAU4HEnwq7d6aYmlqPXaCXd0cfP9e7BbLfzduzfw+YtWUmCXX+f5SCabIZaK5jJajFiPEfGRyIyuMem0FuBz+CgtLKPevwivw4/P6cPr8OOxe7FarHN0J4IwO8gnmSDMY8a6beqdKX74X8/RERnkQw2L+D/v3khlkXuul3lGo7VmMD0wYuXICzCNJPqJp2Kjg0yVFZ/Dh9fhI+guN4/9OeuH0+qcw7sRhLlHhIkgzEOyWvNCa5zHD/WTyGRZ6rPy8LO72NnYyYaaAPf/xaVsqgsefyJhWkhlU6OsHCOZLsY+nU2Put5ld+Nz+KjwLDBiPJz+XJyH2+45Zdwt6Uya7lg3nZFOOiKddEY76ejvoDPawfKKFdx43sfneonCaYgIE0GYRwylszRFkvzuYB9HYimqPTbePHiYr/7mDUK+Qn503QVcu2ERFsup8YftVCKRHqI/2WfEeCT6Rx2PDTK1W+x4HX78ziKqvDVmaq1h+fA6fNgs8/+jVWtNPBGnPdJBZ6TDEB6RTuM4ahyHY2GyOjtqnL/QT9AnoliYOeb/b48gnIZktaZnME1rPEVbLEVrLEVbPEnPkBHo6HVYKM7EuP3hnaSzmr+9fA1fvGwNHqdkVZwsWmsG0vFxhEcfkXFiPVx2N35HUS7INGf1cPopsBbMe6vHsLWjI9IxYvGIdNIZHREhA8mBUWPsVjtl3jJCvhAbazcQ9IUI+oKEfEGC3iBBX5ACu6SgCzOLCBNBmGEG01naYyla48mcCGmPp0hmjbgDBZS5bFR5HCz0ZOiJRLnv6T0c6o7wntW13Hr1JupKvXN7E6cIWZ0llowSSfbRbwqQYeERGeNyUaicm2WRK4TfWTRKfNgt81cEaq2JJWKmwDja2tHR30FPvOcoa0eRq4igN0h1cVVOeIR8huAIeUMUuYuklokw54gwEYRpIqs14cG0af1I0RZL0hpL0ZsYSfd02SxUeOysDjhJJROE+yLsb+vh8dYwb3b0k0gb166oKOaRre/kwiVS9nssRlGxflN4GKJj+DiWjJJl5I+xVVnxOYvwOfws8Nbgd/rxOQwB4nF4sar5meGSyqTojnabcR2jLR7DFpDB1OCoMXarPWfVaKjbKNYO4ZRFhIkgnAQDqSxtpgWkLT5iBUmZVhALphXEa6fOYyEai9PS1currWF+2dZLZ3Tkj0rIV8jKihIuWlrJiooSVlQUs7yiCKvlzP3PNZlJGGIjaQiO/kRfrpdLPBUbda3Rw6WIgCvIouKlObeL31GEy+6edy4XrTWRwYghMKLDlo6R4NLOSAfhWM+oTB7Is3aUVOWERyjP4lHkEmuHcHogwkQQJiCrNd0Dw7EgyVxMSN8YK0ilx87qEgeJRILO3gj727p5trWH/V39ZEyxUmCzsqy8iMuXV7GyopgVlcWsqCg5I8vGa61JZIZylo6xQadD6dHWAJfNhc/pZ4FZzXRYePicfpzzLN4jmU7SFe2aMLYjkR4dz+KwOQh5gwR9ITbVb86JjaAvRNBbRtAbxGmXNGLhzEBprY9/lTAuDQ0NeufOnXO9DGGaiKcyOQtImxkT0h5Pkx62gigIuuyUFVqxZNJEYjGaOnt5/Ug3+9p66R9M5uaqLvawsrKYFRXFrKw0rCALAz5sZ1AzPSPYdMBwt+QFmxrWjz6S2eSo6z12ryk6ivA7zL0Z82G3OuboLkajtaZ3oDdPcJjiY9jyEe2kN9571LhSd6kpNMoIevNcLKbFw1/on1fiahY4o25WODHEYiKcUWit6Utk6BxI0RFPG/sBYx9PjcQmuO0WKt12VhbbSQwN0dHbz1tHwjzVFuZQOMqwnnc7baysKOH96+tZabphVlQU4yucH39IZxqtda6qaf9wkGnCDDxN9h0j2LSIkLvcdLkU4XcWzZsU20w2k7N2tPd3mPt2OiIdZv2OTlKZ0Y3xCuwFhMx4jsXBxaMER9AXJOAJ4LCdGT8PgjAdzP0ngSDMAJmsEYjaMZCic8Dcx43j4WwYMNwwQZeNRX472VSKvmicw51hXjgS5vW2XuJJ4w+rUrAw4GPVglI+3LCYFZXFrKwoobrYc9rXFMnoDLFkNC/Ooy8v8DQyqpfLcFVTn7OIBd4qfI6iXLbLfAg2TWVSdEW7cmJjrPjojHQelclS6i4l5A+xtHwpFyy9wLB8mCm1QV8Qb4H3TLN2CMKMIsJEOKVJZLJ0mRaPEQtIiu7BNHn6A7/TSrDQxvJiO8lkkt5IlMOdfezr6OWtjj768twwRYUOVlWWcP3ZSwwrSGUxy0JFuE/jGiLJTIJIrpR6fy7QdLi/S34gptHBtojighJq/QvxmYXGfE4/brtnTgMwk+mkYd3IExvt/SPH3dHuUfeiUAS8Acr95axasIryFUZAabm/nHJfOUFfUKwdgjDLiDARTgniyUzO5WJYP4zj/FRcC1BaaCNQaKW8QDE4OEh3f4xDHT1sb+/lQFeEofTI9WWeApaGinjfunqWhvwsDRWxNFREpd912v0HnNVZ4qmYKTSMUuq540Q/Q5mhUdc7rU68Dj9lrlAu08UQH0W4bHP3fIZSQznRMZ7VoyfeM+p6i7KY8RwhNtRuMEVHiHJfOSF/iDJvGXbr6Ss4BeFURISJMG+YbPyH3aIIumxUemwsKIT4wADtPRH2t4d5sqOfpp4YWTMIRCmoLfGyJOjn4mWVLA0WsTTkZ0mwiGL36ZXlML7Vw2wsl4yMclEMx3t4HT7qixbnUmyNZnI+nLa5yRQaSAyMCI9IBx397bRH2nPio2+gb9T1NouNoC9Iub+csxeebVg6/CNWj4AnIN14BeEUQ4SJMKsYwZJZwoNpugfTuX3XwLHjP+q9djKpJJF4nCPd/bzWFubXnf2jaoE4bVYWlflYW13KtRsXsSTkZ2mwiEVlPgodp8eP+bDVw+he2zfG6hFhKDM6xXbY6lFaWEa9f7EpPHz4HEa8x1y4XOKJ+CiLR3t/B+2RdjrMfWQwMup6u9VOuS9EyF/OktASyv3lOatHyBei1FMqtTsE4TTj9PjEFuYVWa2JJjN0jxEfw/tEJt/HD0UFVkoLbCwtspNMDNHTH6epu4fdbb283dlPLDGSBeEvdLA05Ofy5VUsDQ67X/zUlHhOi4JkiXSCaDKS527pm6TVY9G8sHrEErFRMR3t/e2G1cO0gESHoqOud9qcObFxVsUy87jcjPGQEumCcCYy48JEKVUHXKy1/qn5+kLgDmAN8BGt9cPHGNcIRIEMkNZaN5jnS4D/AOqARuBDWute872vAZ8yx/y11voP48w7pfGCQVZr+obGER9DxnEqz/JhUVBSYKO0wEqJw04mlSISH6CjL0JjZy/PdEdpCkdJZUb+6FYWuVgSLOKjmxbnxMeSoJ+gt/CUjf8wiooNC48IsWSEaDI66vXY2h6jrR6L8JmptXNl9YgNxUyR0X5UnEd7fzuxxOiqrMOptOX+clYsWDkSWGrGeRS5ik7Z76cgCDPDjBZYU0ptBb4IuIADwEeAAsAH/G/g0eMIkwatdfeY898BerTWtymlvgoUa61vUUqtAH4ObAYqgSeApVrn5TJOw/h8TvcCa+mspndotPAYPu4ZSpNn+MBmUYbwKLDhUFlSyST98QE6eiMc6ujlUNgQH+k8weJ22KgP+FhY5qO+1JsnQIrwFpx6AYlaa4Yyg8TyxEbUFB8x8ziVHV0Dw26x43X48JiWD2PzzonVQ2tN30CfmdXSOSq7xbB8dBBPxkeNKbAX5DJYyv3DoqM8F1x6BhYOEyaH/FAIx2TGLCZKKS9wK3AVsBx4GohrrdvN97PHHj0h7wUuNo/vN+e9xTz/kNY6ARxSSu3HEBnPT+d4pdRNwE0ANTU1J3kL84dUJkt4KJMnPFK5496hzKhuHU6rorTQRtBlY4HLQjKZpD8Wp60nwsGuPp7oinC4N5YrwQ5GAbJFAR+rKku4em2dIUQCXhYGfKec9UNrzWB6YJTQyFk7UoYYyS8oBkYfl2ELR6Wn2hQdvpwYcVqds/YMUplUXl+WjjFN4YyutMn0aItNob2QiqIKyn0h1lavzcV7DFs9fAW+U+p7KAjC/GcmXTlZwIFhHUFr3XiC4zXw30opDdyjtb7XPB/SWreZc7YppYLm+QXAC3njW8xzY5nSeHMd94JhMTnBe5ozEuksHWaWS0c8ZWwDqaPER6FNESi0U+VxUOvOGDU/onFae/p5s6uPg10RmnvjuawXAG+BnYUBH+uqA3xgw0LqTeGxMOAj4JlffUwmYriE+oib5WiLR2aMAc1pLcDr8OF3FlPlrc2zePjw2H04bbOT+aO1JpaIGZaO/nY6o5109HfkGsN19HfQEz+6MVyJu4SQL8TC4CK2LN6SS62V4mGCIMwVMyZMtNZxpdTHgW8D5UqpVcDfa60HJjnFeVrrVlM4/I9S6g2t9TMTXD/ep+eJCIepjp8XDKWzdA4YnW7zRUh+vQ+r2fNlgcdOncdKYihBbyzOkXA/+7r6OdQdoWWM+PAXOlgY8NFQG+TajV4WlhnCoz7go9Q9e//1nyyGm2WIeDJKLBUjlowSTxnH8WSMWCpKPBU7qupngbUQr8NLSUEpNb76nPDwmHuHdXaERyabIRwLj3KzdI467mQgOfpXy26150TG5oVGY7hhwRHyGTU8pHiYIAjzjRkNftVaP6qU2ovhzmkAvgx8c5JjW819p1LqEQy3yjNAh1KqwrR2VACd5pAWoDpviiqgdZyppzp+XjCYztIZT9E+MGz9MERIftdbmylAqrx2at0WBgYGaO816n083WEIkHy3S7HLycKAj811QT7SYMZ+mK6XEvf87YCrtSaZSZriIkpsWGjkCY54MkZaj3azWJQFt92D2+4h5K7AY/fgyXe12H2zUnxLa010KEpntIsuc+scIz66ol1HiSZfoY+QL0RV8QI21m7I9WcZFh/FruJ5LxgFQRDGMpMxJh6g1HwZBV4HSo4z5g2t9VlKKTdg0VpHzeN3AN8wL3sUuBG4zdz/Ju/8z5RS38MIXl0CbB/ny0x1/KwymDJcMO2m66UjbgiQ/mSeALEoQi4b1V47NS5FLD5Ae08/b7eH+Z+Ofpp6RprO2SyK+oCPs0JFvHdtHUuCfhaV+agv9c3bgmOpTPKYVo5YMkY8FT0qqFShcNvduB1eSgvLqPUtxOPw4LZ78Tg8eOxeCmehgqnWmshgJCc4uqJdowTI8JZIJ0aNs1qslJnt7tdUr8kTHCHKTWtHoaNwRtcuCIIwF8xYVo5SqhgjyyWAIVAOA9dh/NF/BCgGhoB2rfVKpVQAeE5rvUwptdC8Bgzx9DOt9bfMeUuBXwA15pzXaq17zPf+DvgkkAa+qLV+3Dz/Y+BurfXOkxl/LKYzK2cglaEjns6zgBj7SHJ0xdOQy0ax04pOp4jFB2jt6eOttjBvdvTR2jdiyndYLSwx63wsCxWxrNwot74w4MVhmz+VMFOZlGHRMLdYMpqzcsRMt0sykzhqnMvmxu3w4LEPiw2vcWzuXXb3jKfSaq3pH+wfX3BEzH2s66iAUouyUOYNEDCFR5k3QJm3zNyM1yXuEqlYKpzOiClPOCYzmi4MR9cxmeC69wALtdZ3zuiCppGTFSbRZIZXugZz4qMjniKaV3LdYVGE3Db8DgvZVIpILE5LuI+328K81TG64qnLYWNJ0M+yckOALA35WRYqorbEi806d4WpsjrLYHqQgVSMeCo+SnwMDL9Oxo6q2wFQYCvMExyGdcNt7j12Ly67e8b/aGd1lv6B/lGCo3sca0cqM9pSY7VYCXgCBH1ByjyG4Ah4ywj6TOHhKaPYXSyiQzjTEWEiHJPZqPzaB+w+3kVa68dmYS3zgv5Ehl+93YvTavR8qfHYyKRT9EfjtHT3srstzJvtozve+gqMiqdXLK/KiZBloSIWFLmxWGb3d3y0lSNuio+R1/FUjMHUAFlGx0QoFC67G7fdQ5GzmAWeatymdcNtxne47R5slpn9sRxMDhKOhQnHw4RjYbpjYcKxbrpjYbqj3XTHuuiKdh8lOmwWm2nVCHBWxVlcuPTCUdaOoDcolUoFQRCmyIwLE631pITJmcTA4ABDHc3sMV0w8cRIUGap28myUBHvW1/P0mBRToSU+2a+5sdoK8doS8fxrBwOiwOX3YPb7jYEh8M4Hg4uddk9FNoKZ/SPdiKVGFds9OReG9vYImFglEYv9ZQS8ARYUbkyT3AEc2KkyCWiQxAEYaaRXjlzgNbw1OvNLA35uW7Tkjw3TBEBz8xkv6Sz6RGrRjJfeERzAmQgFT+qzsWIlcON31lMpad6lOBwm2LEbp25tNNkOklPvGeU4AjniY3uWDc98Z6j+rCAkTIb8AQo9ZRSX1ZPQ30DAU8ppZ5SSj2B3LHb4ZYMFkEQhHnAjMeYnM7Mh5L0Rv+VodEWjmRsVExHPBUnkRk6aqzd4hgtMhweI6jU7sHtMPaFNteMWQmGBUe+6OiJj7ZudMe6j+o4C4ZbpdRTQqkpOgKm0Cj1lFLqLsmJESkQJgjzEvmlFI6JWEzmMVmdHXGhjHWv5ImPsdVIAQptLtx2D16Hn3J3pelaGb05ZsDKkdVZIoMRwrGwKTp6c+KjJxYe9XpswzcwMlZK3CUEPKVU+CtYtWBVTnSMWDpK8RX6xK0iCIJwGiLCZI5IZZJHZavkhEfScK8MpgeOcq1YlDVn5ShzhaizL8pZO4bPu+xurGp6sz4Gk4N5QiOcJzYMoRGOh+k13x9bCAyMnisl7hJKPCXUl9WxsW6j8dpdQom72BAj3gD+Qr9krAiCIJzBiDCZA9rjrfzm7V8edd5hdeasGSWFgaMsHG6HhwLr9PWeyWQz9A30jYiMeA/h2MjxsNAIx8IMpgaPGm9YN4opNgXG4uBiStwllHpK8kSHsUkxMEEQBGEyiDCZA/zOIjZXbMFt946K8Ziu8ucj1o2R+I1wzsLRk7Nw9A/0j2vdcDvdhsBwl7I0tISShWdT4imh2F1CaZ7Y8BX6xLohCIIgTCsiTOaAQpuL9aFNJzRmbOxG2LRoGEGiPaOEyNhmbmAU/ip2FVPqKaXMG2BZ+bKca2VYbJR6Sil2FeO0z8/S9IIgCMLpjwiTOWZsZspod0o450rpHeglkz06yNXlcFHqNqwZS0JLKHEb4iPfuiHBooIgCMKpggiTOWB/x37+8bFvHbP2hkJR5C6i1F1KibuE+rJ689gQHRK7IQiCIJyuiDCZAzwFHmpLa1lfs26UdWNYdBS5iiR2QxAEQTgjkQJrU2A+FFgTBEE4BZECa8IxkaADQRAEQRDmDSJMBEEQBEGYN4gwEQRBEARh3iDCRBAEQRCEeYMIE0EQBEEQ5g0iTARBEARBmDeIMBEEQRAEYd4gwkQQBEEQhHmDFFibAkqpLqBprtcxRQJA91wvYh4hz2M08jxGkGcxmqk8j26t9ZXTuRjh9EGEyRmOUmqn1rphrtcxX5DnMRp5HiPIsxiNPA9hphBXjiAIgiAI8wYRJoIgCIIgzBtEmAj3zvUC5hnyPEYjz2MEeRajkechzAgSYyIIgiAIwrxBLCaCIAiCIMwbRJgIgiAIgjBvEGFymqGUqlZKPaWUel0ptU8p9Tfm+RKl1P8opd4298Xm+SuUUi8ppV4x95ea511Kqd8qpd4w57ltLu/rZJmu5zFmzkeVUq/O9r1MB9P5PJRSDqXUvUqpt8yfk2vm6r5Ohml+Fh81z+9VSv1eKRWYq/s6WU7ieWxWSu02tz1KqffnzbXRfB77lVJ3KqXUXN2XcAqitZbtNNqACmCDeewF3gJWAAfkNfUAAAORSURBVN8Bvmqe/yrwz+bxeqDSPF4FHDGPXcAl5rED+DPwrrm+v7l6HnnzfQD4GfDqXN/bXD8P4FbgH81jCxCY6/ubi2cB2IDO4fs3x//fub6/WXgeLsCWN7Yz7/V24FxAAY+fip8dss3dNucLkG2Gv8HwG+AK4E2gwjxXAbw5zrUKCAPOcd77AfCZub6fuXwegAd41vywPiWFyTQ/j2bAPdf3MNfPArADXUCtef5u4Ka5vp9Zfh71QIcp0iqAN/Le+yhwz1zfj2ynziaunNMYpVQdxn95LwIhrXUbgLkPjjPkGmCX1joxZp4i4CrgjzO53plmGp7HN4HbgYEZX+wsMJXnYf5MAHxTKfWyUuqXSqnQLCx7RpjKs9Bap4CtwCtAK4Zw/cksLHvGmOzzUEqdrZTah3Hvn9Nap4EFQEvedC3mOUGYFCJMTlOUUh7gP4Evaq0jk7h+JfDPwGfHnLcBPwfu1FofnIm1zgZTfR5KqXXAYq31IzO60FliGn4+bEAV8JzWegPwPPAvM7TcGWUafjbsGMJkPVAJ7AW+NmMLnmFO5HlorV/UWq8ENgFfU0oVYFiNjrp0+lcqnK6IMDkNMT8o/xN4UGv9K/N0h1Kqwnx/2B88fH0V8Ajwca31gTHT3Qu8rbW+Y+ZXPjNM0/M4F9iolGrEcOcsVUo9PTt3ML1M0/MIY1iOhoXaL4ENs7D8aWWansU6AK31Aa21Bn4BbJmlW5hWTvR5DKO1fh2IY8TetGCI1mGqMCxJgjApRJicZpjR7z8BXtdafy/vrUeBG83jGzH8x8Numt8CX9NaPzdmrn8E/MAXZ3rdM8V0PQ+t9V1a60qtdR1wPvCW1vrimb+D6WUan4cG/gu42Dx1GfDajC5+mpnG35UjwAqlVJn5+grg9Zlc+0xwEs+j3rSoopSqBZYBjaa7J6qUOsec8+PDYwRhUsx1kIts07th/NHUGObk3eb2bqAUI0bkbXNfYl7/dYz/dHbnbUGM/3I0xgfs8PlPz/X9zdXzGDNnHado8Ot0Pg+MYM9nzLn+CNTM9f3N4bP4nPm7shdDsJXO9f3NwvP4GLDPvO5l4H15czUArwIHgH/FrDIum2yT2aQkvSAIgiAI8wZx5QiCIAiCMG8QYSIIgiAIwrxBhIkgCIIgCPMGESaCIAiCIMwbRJgIgiAIgjBvEGEiCP9/u3UsAAAAADDI33oaO4oiADbEBADYCHHnwjV6G+XoAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"revfig = revenue_plot(tb);"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"revfig.savefig('biden_revenue.png', dip=300, bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 360x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x216 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"report(tb, name='Biden Proposal', outdir='biden', author='Anderson Frailey');"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "taxbrain-dev",
"language": "python",
"name": "taxbrain-dev"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.7"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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