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@r-darwish
Last active February 15, 2017 08:14
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{
"cells": [
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [
{
"data": {
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O6u1lObp3/lL1bxuuOROJ7YvBFW4AAACc0YLMnXrorVWK79BYyWOjVLsG6Xgx+FsDAADA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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x108472320>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gross_salaries = np.arange(5_000, 100_000, 500)\n",
"net_salaries = np.array([net_salary(salary) for salary in gross_salaries])\n",
"\n",
"plt.figure(figsize=(12, 12))\n",
"plt.tick_params(axis='x', which='both', bottom='off', top='off', labelbottom='off') \n",
"plt.legend(handles=[\n",
" plt.plot(gross_salaries, label=\"משכורת ברוטו\"[::-1])[0],\n",
" plt.plot(net_salaries, label=\"משכורת נטו\"[::-1])[0]])\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from scipy.ndimage.interpolation import shift"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"STEP_LIMITS = np.array([6_220, 8_920, 14_320, 19_990, 41_410, 53_333])\n",
"PREVIOUS = shift(STEP_LIMITS, 1, cval=0)\n",
"STEPS = STEP_LIMITS - PREVIOUS\n",
"TAX_PERCETAGE = np.matrix([0.1, 0.14, 0.2, 0.31, 0.35, 0.47, 0.5]).transpose()\n",
"TAX_POINT_VALUE = 215\n",
"\n",
"def income_tax(salary, *, points=2.25):\n",
" salary_steps = []\n",
" for step in STEPS:\n",
" salary_steps.append(max(0, min(salary, step)))\n",
" salary -= step\n",
" \n",
" salary_steps.append(max(0, salary))\n",
" salary_steps = np.matrix(salary_steps)\n",
" return (salary_steps @ TAX_PERCETAGE).item(0, 0) - points * TAX_POINT_VALUE"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"AVERAGE_SALARY = 5_804\n",
"\n",
"def health_tax(salary):\n",
" cutoff = AVERAGE_SALARY * 0.6\n",
" low, mid = min(salary, cutoff), max(salary - cutoff, 0)\n",
" return low * 0.031 + mid * 0.05\n",
"\n",
"def national_insurance(salary):\n",
" cutoff = AVERAGE_SALARY * 0.6\n",
" low, mid = min(salary, cutoff), max(salary - cutoff, 0)\n",
" return low * 0.004 + mid * 0.07"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": true,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"PENSION = 0.06\n",
"\n",
"def net_salary(salary):\n",
" return salary - income_tax(salary) - health_tax(salary) - national_insurance(salary) - salary * PENSION"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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