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bgbg/holidays_in_tishrei.ipynb

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holidays_in_tishrei.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.334727Z",
"start_time": "2021-08-24T07:59:14.826652Z"
}
},
"outputs": [],
"source": [
"import glob\n",
"import urllib\n",
"import datetime\n",
"import pandas as pd\n",
"import numpy as np\n",
"import tqdm.auto as tqdm\n",
"import os\n",
"import pickle\n",
"from matplotlib.patches import FancyArrow "
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.339125Z",
"start_time": "2021-08-24T07:59:15.337207Z"
}
},
"outputs": [],
"source": [
"import json"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.343156Z",
"start_time": "2021-08-24T07:59:15.341372Z"
}
},
"outputs": [],
"source": [
"url_tmpl = \"http://www.hebcal.com/converter/?cfg=json&hy=YEAR&hm=MONTH&hd=DAY&h2g=1\""
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.346739Z",
"start_time": "2021-08-24T07:59:15.344496Z"
}
},
"outputs": [],
"source": [
"this_year = 5782\n",
"this_year_gregorian = 2021 #\n",
"from_year = this_year - 3\n",
"to_year = this_year + 3\n",
"the_month = \"Tishrei\""
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.353235Z",
"start_time": "2021-08-24T07:59:15.348176Z"
}
},
"outputs": [],
"source": [
"def get_data_for_hebrew_year(hy):\n",
" res = []\n",
" for hd in tqdm.tqdm(range(0, 31), desc=f'year {hy}', leave=False):\n",
" if hd == 0:\n",
" the_year = hy - 1\n",
" the_month = \"Elul\"\n",
" the_day = 29\n",
" is_holiday = True\n",
" else:\n",
" the_year = hy\n",
" the_month = \"Tishrei\"\n",
" the_day = hd\n",
" is_holiday = the_day in (1, 9, 10, 14, 15, 20, 21)\n",
" \n",
" url = url_tmpl.replace(\"YEAR\", str(the_year)).replace(\"MONTH\", the_month).replace(\"DAY\", str(the_day))\n",
" resp = urllib.request.urlopen(url).read()\n",
" jresp = json.loads(resp.decode())\n",
" g_year = int(jresp['gy'])\n",
" g_mn = int(jresp['gm'])\n",
" g_dy = int(jresp['gd'])\n",
" weekday = datetime.datetime(g_year, g_mn, g_dy, 0, 0, 0, 0).weekday()\n",
" #weekday: monday 0, sunday 6\n",
" line = [the_year, the_month, the_day, g_year, g_mn, g_dy, weekday, weekday in (5, 4), is_holiday]\n",
" res.append(line)\n",
" return res\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.358597Z",
"start_time": "2021-08-24T07:59:15.354602Z"
}
},
"outputs": [],
"source": [
"pkl_file = 'holidays_in_tishrei_data.pkl'\n",
"if os.path.exists(pkl_file):\n",
" data = pickle.load(open(pkl_file, 'rb'))\n",
"else:\n",
" lines = []\n",
" for hy in tqdm.tqdm(range(from_year, to_year)):\n",
" res = get_data_for_hebrew_year(hy)\n",
" lines.extend(res)\n",
" data = pd.DataFrame(lines, columns=['hyear', 'hmonth', 'hday', 'year', 'month', 'day', 'wday', 'isweekend', 'isholiday'])\n",
" pickle.dump(data, open(pkl_file, 'wb'))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.366851Z",
"start_time": "2021-08-24T07:59:15.361694Z"
}
},
"outputs": [],
"source": [
"data['not_working'] = data.isweekend | data.isholiday\n",
"sel_working = np.logical_not(data.not_working)\n",
"sel_holamoed = (data.hday > 15) & (data.hday < 20) & sel_working"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.374182Z",
"start_time": "2021-08-24T07:59:15.368973Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-8-7dd6acc38926>:2: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" data.not_working[sel_holamoed] = 0.5\n"
]
}
],
"source": [
"data.not_working = data.not_working.astype(np.float)\n",
"data.not_working[sel_holamoed] = 0.5"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.385317Z",
"start_time": "2021-08-24T07:59:15.375702Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"year\n",
"2018 16.5\n",
"2019 16.5\n",
"2020 15.0\n",
"2021 17.0\n",
"2022 16.5\n",
"2023 15.0\n",
"Name: not_working, dtype: float64"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"by_year = data.groupby('year')['not_working'].agg(np.sum)\n",
"by_year"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.401845Z",
"start_time": "2021-08-24T07:59:15.386936Z"
}
},
"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>hyear</th>\n",
" <th>hmonth</th>\n",
" <th>hday</th>\n",
" <th>year</th>\n",
" <th>month</th>\n",
" <th>day</th>\n",
" <th>wday</th>\n",
" <th>isweekend</th>\n",
" <th>isholiday</th>\n",
" <th>not_working</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>5778</td>\n",
" <td>Elul</td>\n",
" <td>29</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>9</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>5779</td>\n",
" <td>Tishrei</td>\n",
" <td>1</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>10</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5779</td>\n",
" <td>Tishrei</td>\n",
" <td>2</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>5779</td>\n",
" <td>Tishrei</td>\n",
" <td>3</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>12</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5779</td>\n",
" <td>Tishrei</td>\n",
" <td>4</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>13</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>181</th>\n",
" <td>5784</td>\n",
" <td>Tishrei</td>\n",
" <td>26</td>\n",
" <td>2023</td>\n",
" <td>10</td>\n",
" <td>11</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>182</th>\n",
" <td>5784</td>\n",
" <td>Tishrei</td>\n",
" <td>27</td>\n",
" <td>2023</td>\n",
" <td>10</td>\n",
" <td>12</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>183</th>\n",
" <td>5784</td>\n",
" <td>Tishrei</td>\n",
" <td>28</td>\n",
" <td>2023</td>\n",
" <td>10</td>\n",
" <td>13</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>184</th>\n",
" <td>5784</td>\n",
" <td>Tishrei</td>\n",
" <td>29</td>\n",
" <td>2023</td>\n",
" <td>10</td>\n",
" <td>14</td>\n",
" <td>5</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>185</th>\n",
" <td>5784</td>\n",
" <td>Tishrei</td>\n",
" <td>30</td>\n",
" <td>2023</td>\n",
" <td>10</td>\n",
" <td>15</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>186 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" hyear hmonth hday year month day wday isweekend isholiday \\\n",
"0 5778 Elul 29 2018 9 9 6 False True \n",
"1 5779 Tishrei 1 2018 9 10 0 False True \n",
"2 5779 Tishrei 2 2018 9 11 1 False False \n",
"3 5779 Tishrei 3 2018 9 12 2 False False \n",
"4 5779 Tishrei 4 2018 9 13 3 False False \n",
".. ... ... ... ... ... ... ... ... ... \n",
"181 5784 Tishrei 26 2023 10 11 2 False False \n",
"182 5784 Tishrei 27 2023 10 12 3 False False \n",
"183 5784 Tishrei 28 2023 10 13 4 True False \n",
"184 5784 Tishrei 29 2023 10 14 5 True False \n",
"185 5784 Tishrei 30 2023 10 15 6 False False \n",
"\n",
" not_working \n",
"0 1.0 \n",
"1 1.0 \n",
"2 0.0 \n",
"3 0.0 \n",
"4 0.0 \n",
".. ... \n",
"181 0.0 \n",
"182 0.0 \n",
"183 1.0 \n",
"184 1.0 \n",
"185 0.0 \n",
"\n",
"[186 rows x 10 columns]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.782990Z",
"start_time": "2021-08-24T07:59:15.403374Z"
}
},
"outputs": [],
"source": [
"import seaborn as sns\n",
"sns.set_style('white')\n",
"from matplotlib import pylab as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.789413Z",
"start_time": "2021-08-24T07:59:15.784953Z"
}
},
"outputs": [],
"source": [
"palette = sns.color_palette(\"RdBu\", n_colors=7) # create a set of nice colors\n",
"red = palette[0]\n",
"pink = palette[2]\n",
"highlight = palette[4]\n",
"blue = palette[-1]\n",
"gray = sns.xkcd_rgb['bluish grey']"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.793425Z",
"start_time": "2021-08-24T07:59:15.791106Z"
}
},
"outputs": [],
"source": [
"ylabelparams = {\n",
" 'y': 1.0, 'rotation': 0,\n",
" 'ha': 'right', 'ma': 'left', 'va': 'top'\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.989307Z",
"start_time": "2021-08-24T07:59:15.795112Z"
}
},
"outputs": [
{
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0y5Ytc/TRR+c73/lOefwV0bNnzwwbNixJcu211+bqq6+utn3+/Pm55ppryj/37t17hZ8DWHmNZb6ZO3duub3WWmvV2rdZs//8efDhhx+u0PMAK29NmG9WtYa6qgOoXzvustsyA/tF/v7q8HJ7vS5dkiRjPvzPickbdO1W6/5dNtyw3P7n6H+Ug/9VrWFxLVq2zIGHHpHjTjolnbt8abnGBFaPxnJ8UxdjAPWrscw3y+PTTz/NbbfdlmThdzxf//rXV2h/Gj/BPwCN0pAhQzJixIgkyRZbbFG+Wn7ixInlPl/6Uu1fDHVZ7Iulxfdb5JJLLkmTJit/15y+ffvm6aefzrBhw3L//fdnwoQJOeaYY9KlS5eMHTs2v//97/P2228nWXhvqK997Wsr/VxA/VnT55sOHTpUG7u2P2IXXyLO7UVgzbM65puVrWF11wHUr1de/Es+eG9UkmTjTTdLp/U6J0k+/mhSuc96nWtfkazTev/Zvvh+q1rD4s7+4YWr9DcZ0PDW9OOb1TkGUL+KOt/Mnj0748aNy9NPP50BAwZk8uTJqaioyMUXX1ztOx9IBP8ANEKffvppLrnkkvLPp5xySrk9derUcrtNmza1jrP4lbHTpk1bYvuqfsHUsmXL3Hzzzbn11ltz++2356WXXspLL71UrU+nTp1y/vnn59BDD12l5wLqRxHmmx133DEPPvhgkuSJJ57IaaedVmPfZ555ptyeMWPGSj8nUPdW13yzsjWszjqA+jXls89y3c+vKP985HEnlNvT/v3vcrv1WrV/zlu3bl1uV63g57y2GhYn9IdiK8LxzeoaA6hfRZ1v3nzzzRx11FHVHlt//fVz6aWXutqfpXJ0DECjMn369HznO98pX7W6++67VwvN58z5z30hW7VqVetYi29ffL+69P7772fEiBE1Bmwff/xxHn300XzwwQf18vzAyivKfHPggQeWx7/xxhurLWG3uAEDBuTdd98t/zxv3rw6rQNYeWvCfLOsGlZXHUD9mjljRi49//uZPGnhFWzb77xreh74n1uOzV3s89qyZctax2rR8j+f87lzl/9zvqwagMahKMc3q2MMoH4Veb7517/+tcRjkydPzj333JO33npruZ+fLw7BPwCNxrRp03Lqqafmb3/7W5KFZz/+6le/qnYVSNOmTcvtioqKWscrlUrldn1cSfLcc8+lX79+efLJJ9OuXbtceumleeGFF/Lmm2/m8ccfz1lnnZXmzZvnmWeeyXHHHedgDtYgRZpvOnbsmDPPPDNJUlVVleOOOy5/+MMf8tFHH2Xu3Ln5xz/+kZ/97Ge58sor07nzf5bQbd68eZ3WAaycNWG+WZ4aVkcdQP2aXjUt/+fcszPirTeTJB3X65wfX35ltc9ok8U+51nW5zwr/jlfnhqA4ivS8U19jwHUr6LPN927d8+NN96Y++67LzfccEN69+6d+fPn59lnn03//v3zwgsvLFcNfHFY6h+ARuGjjz7KaaedVr5HUseOHXPbbbelU6dO1fotvhzTrFmz0qJFixrHnD17drldW7+Vrffcc8/NrFmz0qFDh9xzzz3p2rVreXv37t3z3e9+N3vssUdOOeWUTJkyJeecc04ee+yxZV5ZA9Svos03SXLaaadl4sSJufPOOzN16tT87Gc/y89+9rNqfTbccMNcffXV6d+/f5Lq9QMNY02Yb5a3hvquA6hfn3w8ORef99188N6oJEmHddbNVdf9b9ZZt2O1fosv3z9n9uxaP79zF/ucN2++7M/58tYAFFvRjm/qcwygfjWG+WbLLbfMlltuWf55v/32S48ePfKTn/wkM2fOzA9/+MM8/fTTqaysXK7xaPycegZA4Y0cOTJHH310+QBq/fXXz4ABA7Lpppsu0Xfx+zTNnDmz1nEXX36/Xbt2dVTtQoMGDSqP/93vfrda6L+4PfbYI/369UuycGmnp59+uk7rAFZMEeebZOEZ65dcckmuv/76bLfddtXOYO/UqVO+/e1v54EHHkjbtm3Lj3fs6Et2aEhrwnyzIjXUZx1A/frgvXfz3VNOKAfuHdfrnF/ccFO6dt94ib6t1/rP53zWMj7ni88Day92jLGqNQDFVcTjm/oaA6hfjWW+WZojjzwyBxxwQJJkypQpefzxx1dpPBoXwT8AhTZkyJD07ds3EycuvP/jJptskjvvvLPGA6gNNtig3F50T6WaLL598eWv68Ibb7xRbvfs2bPWvr169Sq3Fy0JBax+RZ1vFterV6/86U9/yrBhw/LII4/khRdeyAsvvJAf/vCHqayszAcffFDuu+GGG9ZbHUDt1oT5ZkVrqK86gPo17K9D84MzTs7HH01KkmzUrXt+9X9vrTFw79ylS7k9+aOJtY69+PZ1O61XZzUAxVTU45v6GAOoX41lvqnN/vvvX24vOrEAEsE/AAV2//3358wzzyyfabnzzjvnrrvuqnaw9nmbb755uT1mzJhaxx87dmy5vdlmm61itdUtfnbo2muvXWvfddddt9yeNm1andYBLJ8izzdL07Zt22y66aZZb731ql39//rrr5fbW2+9db3XASxpTZhvVqaG+qgDqF9PPvxgLj3/vMz8f5/1bbbfMb+68fZ07vKlGvfpvsl/Pq8Txo+rdfwJ4/6zvdsmS/+Se2VqAIqnyMc3dT0GUL+KPN9MmzYtb7/9dh5//PGUSqVa+7Zv377cnjt3bq19+WIR/ANQSAMHDsyPf/zjzJs3L0ly0EEH5fe//321g56l2XHHHcsh1/Dhw2vtO2zYsCRJly5d6vzK1w4dOpTbyzqgnDRpUrm9+EkAwOpR9Plm7Nix+c1vfpOLL7641lVDSqVS+XYiXbt2zUYbbVSndQDLtibMNytbQ13XAdSvJx4enGuvuDTz5y/8rH+tZ69c/T//N22XsWTtl7f9zy2D3nz9tVr7vvH/tnfqvH7WX0qQv7I1AMVS9OObuhwDqF9Fn28uv/zy9OnTJ9/97nczcuTIWvsu/n3y+uuvv8yx+eIQ/ANQOK+88kouuuii8pmP/fv3z69//eu0aNFimft26dIlO+64Y5Lk8ccfT1VV1VL7DR8+PKNHj06S8j2T6tLuu+9ebj/wwAO19n3wwQfL7d12263OawFq1hjmm7lz5+a3v/1t7r333gwaNKjGfo888kjGjx+fJDn88MPrvA6gdmvCfLMqNdRlHUD9evP1V/Prq35a/qwfetQ385OfXr1cn/X1Oq+fL2+zXZLkhWefzvTpS/+cv/X31zNuzIdJkq9+fclbm61KDUBxNIbjm7oaA6hfjWG+Wfx73z/96U819luwYEG17T169Fiu8fliEPwDUChVVVX50Y9+lPnz5ydJjjzyyFx88cXVlqpeluOPPz5JMmXKlFxyySVZsGBBte1Tp07NJZdckiRp3rx5+vfvX0fV/8fBBx+cddZZJ0ny+9//Ps8+++xS+z344IP585//nGThvaD22muvOq8FWLrGMt9ssskm2WKLLZIsPPP8vffeW6LPqFGjctlllyVZuLJIfdQB1GxNmG/qooa6qAOoXzOmT8/PL7s4C/7fZ/2AQw7LWT+4YIU+64cf0zdJMu3fU/M/v7hqic/5tH//O9f9/IokCz/nhx19bJ3XAKz5GsvxTV0dIwH1p7HMN7179y6vEnvPPffkxRdfXKJPqVTKlVdembfffjtJstdee2W77bZb7ueg8WvW0AUAwIr44x//mAkTJiRJOnXqlGOOOSYjRoxY5n5dunQpL6l08MEHZ+DAgRk6dGgeeuihTJw4MSeccEI6d+6cUaNG5cYbbyxf9XrOOefUy3LXlZWVueKKK3LWWWdl/vz5+c53vpODDz44Bx10UNZbb7189NFHefTRR/Pwww+nVCqlVatWufrqq9Osmf91w+rSWOabJPnBD36Q008/PbNnz07//v3z7W9/OzvssEPmzZuXoUOH5o477sjMmTPTtGnTXHXVVWlniV1YrdaE+aYuaqiLOoD69cB9d2fypIlJknU6dsxBhx2RD94dtcz9OnVev7wE/z69DsgTDw/Oqy+/mGefeDSTP5qYw485Lh07dcro99/L3QNuz6QJ/0qS9D/l9Kz/per3s62LGoA1X2M5vqmrYySg/jSW+aaysjKXXXZZvv/972fu3Lk5+eSTc/TRR2fvvfdOx44dM3r06Nx99915/fXXkyxc4v/KK69crteIL46K0qI1JwCgAPbZZ5/yQdSKuOqqq9KnT5/yz1VVVTnjjDPyyiuv1LjPSSedlAsvvHCFzsx8+eWXc8IJJyRJzjjjjJx77rm19n/yySdz4YUX1riEVLLwYPHXv/61Zf5hNWts883vf//7/PznPy+fff55a6+9dq6++urst99+y10DUDfWhPmmrmpY1TqgyEqlUv752YzMmjs/s+YtSLtWzda493j/w3uXQ/cV8YOLLs3+Bx9a/nn69Kpc8sPv582/vVbjPn2O7ZfTvnveEq9BXdVQk7+/Njznn3VakqTvSafkpNPPWuHnWp1KpVKmzpqXVs2apFXzpunWYa017n0DK6OxHN/U5TESUD8ay3yzyEMPPZSLL744M2bMqHG/bbfdNtddd1023HDDFX5OGjeXDQJQGJ9++ulKHUAtTWVlZQYMGJBBgwZl8ODBGTlyZKZNm5YOHTpkp512Sr9+/bLnnnvWyXPVplevXtlll11y11135fnnn8/o0aMzffr0rL322tl8882z77775phjjkmbNm3qvRbgPxrjfHPiiSdm1113zYABAzJs2LBMnjw5zZs3T/fu3bPPPvukf//+WXfddeu9DqC6NWG+qcsaVqUOoH5NnfLZSgXuS9OmTWV+ccNNeerRh/L0Y49k9PvvpmpaVdq1b5+ttts+hx71zey4y5InLtdlDcCaq7Ec39T1MRJQ9xrLfLO4Qw45JLvttlvuuOOOPP/88xkzZkzmzJmTDh06ZPvtt8/BBx+cAw88ME2auJs7S3LFPwAAAACsoiJc8c+axxX/AADUFaeDAAAAAAA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\n",
"text/plain": [
"<Figure size 2200x880 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(dpi=220, figsize=(10, 4))\n",
"ax.plot(by_year.index, 31 - by_year, 'ok')\n",
"ax.set_ylim(0, 30)\n",
"ax.set_xlim(this_year_gregorian-3.5, this_year_gregorian + 2.5)\n",
"ax.set_ylabel('Working days\\nduring the month\\nof Tishrei', **ylabelparams)\n",
"ax.set_xlabel('Gregorian year')\n",
"ax.set_ylim(0, 31)\n",
"STEP = 1\n",
"ax.set_xticks(range(int(by_year.index.min()), int(by_year.index.max() + STEP ), STEP))\n",
"ax.grid(False)\n",
"fig.set_facecolor('white')\n",
"# DELTA = 0.17\n",
"# ax.axvspan(this_year_gregorian-DELTA, 35+DELTA, zorder=-1, color=highlight, alpha=0.5)\n",
"p = FancyArrow(this_year_gregorian, -2.5, 0, 32.5, width=0.5, \n",
" length_includes_head=True, \n",
" head_width=0, head_length=0, \n",
" shape='full', overhang=0, \n",
" head_starts_at_zero=False, \n",
" transform=ax.transData, \n",
" zorder=-1, color=highlight, alpha=0.5,\n",
" clip_on=False)\n",
"ax.add_patch(p) \n",
"\n",
"sns.despine(left=True, ax=ax)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:15.996829Z",
"start_time": "2021-08-24T07:59:15.991413Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"14.5 0.500000\n",
"16.0 0.333333\n",
"14.0 0.166667\n",
"Name: not_working, dtype: float64"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(31-by_year).value_counts(normalize=True)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:16.009731Z",
"start_time": "2021-08-24T07:59:15.998413Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-16-2a2a87a0df07>:2: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" data['day_number'][data.hmonth == 'Elul'] = 0\n",
"<ipython-input-16-2a2a87a0df07>:5: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" data['day_type'][data.not_working == 1] = 'Not working'\n",
"<ipython-input-16-2a2a87a0df07>:6: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" data['day_type'][data.not_working == 0.5] = 'Half working'\n"
]
}
],
"source": [
"data['day_number'] = data.hday\n",
"data['day_number'][data.hmonth == 'Elul'] = 0\n",
"data.day_number = data.day_number - 1\n",
"data['day_type'] = 'Trying to work'\n",
"data['day_type'][data.not_working == 1] = 'Not working'\n",
"data['day_type'][data.not_working == 0.5] = 'Half working'"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:16.020955Z",
"start_time": "2021-08-24T07:59:16.011640Z"
}
},
"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>hyear</th>\n",
" <th>hmonth</th>\n",
" <th>hday</th>\n",
" <th>year</th>\n",
" <th>month</th>\n",
" <th>day</th>\n",
" <th>wday</th>\n",
" <th>isweekend</th>\n",
" <th>isholiday</th>\n",
" <th>not_working</th>\n",
" <th>day_number</th>\n",
" <th>day_type</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>5778</td>\n",
" <td>Elul</td>\n",
" <td>29</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>9</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>-1</td>\n",
" <td>Not working</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>5779</td>\n",
" <td>Tishrei</td>\n",
" <td>1</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>10</td>\n",
" <td>0</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>1.0</td>\n",
" <td>0</td>\n",
" <td>Not working</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5779</td>\n",
" <td>Tishrei</td>\n",
" <td>2</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.0</td>\n",
" <td>1</td>\n",
" <td>Trying to work</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>5779</td>\n",
" <td>Tishrei</td>\n",
" <td>3</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>12</td>\n",
" <td>2</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.0</td>\n",
" <td>2</td>\n",
" <td>Trying to work</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5779</td>\n",
" <td>Tishrei</td>\n",
" <td>4</td>\n",
" <td>2018</td>\n",
" <td>9</td>\n",
" <td>13</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>0.0</td>\n",
" <td>3</td>\n",
" <td>Trying to work</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" hyear hmonth hday year month day wday isweekend isholiday \\\n",
"0 5778 Elul 29 2018 9 9 6 False True \n",
"1 5779 Tishrei 1 2018 9 10 0 False True \n",
"2 5779 Tishrei 2 2018 9 11 1 False False \n",
"3 5779 Tishrei 3 2018 9 12 2 False False \n",
"4 5779 Tishrei 4 2018 9 13 3 False False \n",
"\n",
" not_working day_number day_type \n",
"0 1.0 -1 Not working \n",
"1 1.0 0 Not working \n",
"2 0.0 1 Trying to work \n",
"3 0.0 2 Trying to work \n",
"4 0.0 3 Trying to work "
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:16.025772Z",
"start_time": "2021-08-24T07:59:16.022313Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"year\n",
"2018 16.5\n",
"2019 16.5\n",
"2020 15.0\n",
"2021 17.0\n",
"2022 16.5\n",
"2023 15.0\n",
"Name: not_working, dtype: float64"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"by_year.tail(10)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:16.030362Z",
"start_time": "2021-08-24T07:59:16.027594Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"17.0"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"by_year.loc[this_year_gregorian]"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:16.440930Z",
"start_time": "2021-08-24T07:59:16.031961Z"
}
},
"outputs": [
{
"data": {
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+37/44gu1adPG4v0mxb4nZs6cabjX3LhxI9GWzlOnTjVUiyxcuLCWLl2qzp07Wzw32bJl08CBA/Xbb78ZKleePHlSP/zwg9XxrXFzc9PSpUvVq1cvi3O4u7vryy+/VLt27QzrN2zYYPP4AAAAAAAAySH8BwAAgExj3bp1hsoZn3766VNvbVmzZk3DD4RJhef27dtn/nEze/bshuOSav0bP5Di5uammjVrGrb//fffhspNhQoV0jfffKMsWbIkOfcePXqoZ8+ehnXW2hAmZsKECRZhLmdn5xRV/VuxYoU+++wzcws3Ozs7jRkzRv369bN5jJQaOHBgkq3zJOnNN980/GB7+fJl3bt3z2K/vXv36sSJE+blIkWKaNKkSUm2BixVqlSSFcye1J9//qkHDx6Yl+vUqWMRZkxowIABFhX4EvPo0SP5+PiYl3PmzKlhw4Yle5yTk5NFKOTy5ctW901YYSlhFUNrjh07Zqhc2K5dO4sgcPwKmt7e3slWq6tQoYIaN25sXo6OjjZUvMsI7dq1swgNJNS9e3dDNbhHjx7J19c3vadmsx49eiRZIVWSunXrZgjJPnr0KNHXS8IqlP3790+2SleJEiUsqiEmHOdpCggI0KhRowzrypcvb/V9GRwcbFhOaZvc7NmzG5bjf148iZRcQ2bh4uKi//3vf8qRI0ei+2TLls0i5HTy5Emr+86dO1chISHm5YoVK2rcuHFWQ07xjRgxQk2aNDEvR0VFafbs2clfwBP67bffDKGsTp06Jfv5Y62CYWIuX76ss2fPmpdLlCihXr16JXucq6urunbtajGWNQmr2dlyP9m2bZsh6J1YRbyUiH//yZMnT6LB8ziFChWy+BxL2LJeiq0kF7+SsyR9+eWXyf4NWrdurTfeeMO8HBISYq7qnFDCYNpHH31k0z+0SVid8tq1axZtgyXjcyPJcN+1xs3NzeL7xNGjRy328/PzM/y9HR0d9d1336lw4cJJjl+pUiWL1toLFizQw4cPkzwuzsiRIy3+AUhCb7/9tmE5qX8EBAAAAAAAkFKE/wAAAJAp3LhxQ59//rl5+cUXX7T4IfhpcHR0NLQ09Pf316VLl6zuG7/lb82aNQ3BucQqljx+/NiwrXHjxhY/uP7999+G5WHDhtkcBnn//fcN1XUOHjxoUzWhAgUK6MUXX7TpHIlZu3atRo0apZiYGEmxwb/x48erd+/eTzRucnr06JHsPq6uripTpoxhXfzKMXESVvJ588035eLikuz4DRo0SLTiz5NKGGywtQ32iBEjbNrv/v376tSpk+rWratChQqpdevWiVZoSihh5aT4IZj46tevb6hmduzYMV27di3JsZNr+SvJUP3uypUrNlXxGzZsmH766SetXbtWx44dS7e/m60SBnatsbe3V5UqVQzrEqvo9LTZ2dnpzTffTHY/R0dHVa9e3bAufuWpOEePHjVUVHV1ddXQoUNtmkuDBg0MVcEOHz6cISHJoKAgDRo0yPAZ4+TkpPHjxxuqs8ZJWMUxuaB3Qk5OToZxn7QqpJTya8gs2rVrl2xQSIqtRhdfwtbMcRLer0eOHGlzteJRo0YZnsu1a9faHEZKDZPJZBH6suW95eDgoHfeecemczx69EhdunRRrVq1lD9/fnXq1Mnm14ut95OXXnpJTk5O5uV//vkn2ZbE8e8njo6Oat++vU1zSkpcG3Mp9v0S11I6KX369NGMGTO0cuVKHTlyRF26dLHY588//1R4eLh5uVatWhZVqRPz+uuvGz4/li5dapinFFvJsnLlymratKlKlSolLy8vVa1a1abx8+fPr5w5c5qXTSaT1ec+4TlPnz6d7NgvvfSSvvnmG/311186ePCgRZhOiq0oGPcdU5Lat2+fbOgyTuvWrQ33oJCQEK1atSrZ47Jly6YOHToku1/x4sUNVVjDwsLS9f0MAAAAAAD+Wwj/AQAA4JkXHR2tkSNHmqsV5c2bV+PHj8+w+ST8kTV+yC+x9XXr1jX8eHrmzBmr1Zf27t1r+FG3RYsWhu2hoaGGynMuLi5q06aNzXN3dXVVq1atDOsSCyLGV7169ScKdGzcuFEffvihuaKQvb29Jk2apO7du6d6TFsUKFDAUBEtKfnz5zcsW/vBOn6lRwcHhxQ998lVJkuNkJAQQ8Upd3f3ZKscxvH29tYLL7yQ7H5FihTR+PHjNW/ePG3bti1F772EodSEP/jHcXR01EsvvWRYt27dukTHjY6ONrQG9vLyUvny5S32i18ZNDg4WG+//bZu3ryZ5JzLlCmjZs2aqXTp0ikOWaU1Jycni2qbiUn4+g0LC0uPKaVY0aJFLeaWmISt460FI/bu3WtYbt68uaGqanISfv7Z0vo8LQUFBal///46d+6cYf2HH36YaEglYVgvNa3u4x9jrRJXSqTmGjILWz8/E95XrN3PL126pFu3bpmXCxUqZPP4Umy70/iVfyMjI9O1Wtj58+cNYc7y5cvbXNm3YcOGhtBXYsqXL69JkyZp/vz52rFjh03B4Di23k9y5cplqCQXFhambdu2JTpuUFCQdu3aZV5u2LChRavs1Ij/3EVHR2vo0KHy8/NL9piWLVuqTJkyiYbsE34GpqRKoZubmyHQfv/+fYsAtL29vT755BP9/PPPWrdunUXQPjm2/J0Svq4++OADHTt2LMlx8+TJo7Zt26pChQqJfuYn/D7bqVMnW6ZslvAfFdny/bhcuXLKmjWrTePb8j0TAAAAAAAgNQj/AQAA4Jn3008/6d9//5UUW0Vq8uTJyp07d4bNp1GjRoYgRfyWqHGuXbumq1evmpfr1KljqMwVExOjAwcOWBwXv+Wvs7OzGjRoYNh+7Ngxww+p5cqVs6nyXHwJq2sdPnw42WMqVqyYonPEt3XrVr3//vuGwMnrr7+uzp07p3pMWyXXhi2+hD/exm99KMVWdoofjChVqlSK2m/aWjknJU6dOmWoclOuXLlk20nGF78KWloKCQmRj4+PZs2aZVgf1+7ZmoQBhjVr1iS67549e3T37t1Ej42TMFC4e/dutWjRQgMHDtT8+fMTbRv5rChUqJChHXVSknv9ZpSUtGZPGHaxVqEu4edVSsJUkizClNZaR6aXgIAA9e7dW2fOnDGs79u3r1599dVEj0v4nk7qfZSY+J8TSbUpT05qryGzKFasmE37JWylbO21mjCol5oQfWru16mVsHVxSoKcTk5OKleuXFpPSZIUGBiorVu3WrSoTav7yYYNGwzfq9Ki5a9kef85ffq02rVrpz59+mjWrFmpqjoaHR1tEZJLWIUyOQm/z6XFZ2BkZKSOHz+un376SYGBgYZt1v5OCZ8bf39/de/eXV26dNH06dN17Ngxw2eWLSIiIgz/OMbR0dGiIm5yatSoYVi25f2Wlt8zAQAAAAAAUivl/1wcAAAAeIqOHj2qn376ybz86quvqn79+hk4o9jKKdWrVzdXBNm/f7+ioqIMgcD4Vf/c3d3l7e2twoULy8HBwfxj3759+ywq++3YscP8uE6dOhbhsoStaG2p3JZQwtZ5trQH9fT0TPF5JOnevXt69913LSq/rFy5UoMGDVKOHDlSNa6tUhLOSxiISfjD85UrVwzLtoZE4hQtWlROTk6JVitKjYStcYsXL56i41Pz+onv5s2bunTpkq5du6Zr167p8uXLOnfunK5evWr1h/ukwhrly5fXCy+8oPPnz0uSzp07p/Pnz1udY/wgh4ODQ6ItGnv27Km//vrLEPKLjIyUj4+PObRbuHBhNWzYUE2aNFGdOnVsruDzNKTk/ZHc6zej2FINLDHWXi/xQ9VSbOgo4XszKQnDV8lV4korvr6+GjRokKESnCR169ZNn376aZLHJgyAprRyn8lkMoRMbA2UJvQk15BZPMnrNaG0uF97eXkZltOznfeT3k9Kly5tUZXOVjExMfL399eVK1d09epVXbt2TZcuXdK5c+estv+Wkr6fNGnSRLly5VJQUJCk2H+kERwcbPXvG/9+4ubmpubNm6fqGhJq1aqVqlatqiNHjpjXxcTE6ODBgzp48KCmTZsmT09PNWzYUI0aNVLDhg2T/c5y9+5dQ/t6e3t7RUZGpugzMOE/GEnJZ2BQUJAuXbpk/htduXJFFy5c0IULFxJtJ27t71SlShW1adPGUMFXig2gnjx5UjNmzFCuXLlUr149NW7cWI0aNZK7u3uScwsMDDR8NhYtWjTF1XuLFi2qrFmz6vHjx5Jiv8PGxMQk+Y8q0vJ7JgAAAAAAQGoR/gMAAMAzKyQkxFAxzsvLSx988EEGzypWs2bNzOG/R48e6ejRo4aKIfFbSdapU0d2dnZydXVVxYoVzVVWErYT8/X1VUBAgHk5YTBQkvmH7Di5cuVK8dwTtktLOKYtx9gq7gfUhG7duqVJkybpyy+/TNW4tkppVcSkJKxmk5IffCWZXwMJx3kSCf92KZ1TSl8/kZGR2rhxo9asWaNDhw5ZbXX5JDp06KBp06aZl9esWaMRI0YY9nn8+LE2b95sXq5bt67y5ctndbwcOXLo559/1pAhQ3Tp0iWr+1y/fl2LFi3SokWLlC1bNjVp0kSdOnVSo0aN0uCKnkxavn4zipOTU5qOl/A1/+GHHz7ReGn9GrZmy5YtGjlypEWLxz59+mj06NHJVoNLWGUufvjHFgnPm5rX1ZNeQ2aRmpbKiUmL+3XCsJot9+vUSjh2SsP5Kb2+0NBQrVmzRmvXrtXx48fTtAWqs7OzWrdurcWLF0uKvXdt2rRJ3bp1M+wXEBBgriwtSW3atEl1ODYhR0dH/fDDDxoyZEiiLW3v3Lmj5cuXa/ny5XJyclKDBg3UsWNHvfjii1YrdAYHBxuWY2Ji1KZNmyeaZ3KfgQcOHNDff/+tPXv26ObNm090rvi+/PJLhYWFGSpexxcUFKR169Zp3bp1sre3V82aNdWhQwe1b9/eaqgv4Xer1AZ53dzczN9dY2JiFBwcnGS18efhPg0AAAAAADI/2v4CAADgmTV27Fhdv35dUuwPuVOnTk2zH2WfVMLKMPFb/8bExBiCfXXr1rX6+Pz587p//755OX7VPzs7OzVt2tTivAlDH6mpUpbwmPDw8GSPedLn3dHRUW+88YYhILJ8+XLt2rXricZ9mhJW20pJe904af36Tfi3S+nrIWGoKCn//vuv2rdvr/fff1///PNPsoGBEiVKqEePHimaT8eOHQ3P67p16yz22bZtm+F98PLLLyc7j5UrV2r48OHKnz9/kvuGhoZq3bp1euONN9S3b1+LSljIeCEhIWk6XsIwTVqbOXOmhg0bZhFsevvtt/XZZ5/ZFJpLGDx5+PBhiuaQcP88efKk6Pi0uIb/orS4XycMOdlyv06thGOntGpaSsLnW7ZsUatWrfTZZ59p3759SQb/7OzsVK5cuWQ/6xNKuL+11r+rV682VKZL6TmSkydPHi1atEhjxoxRiRIlktw3MjJS//zzj4YPH64uXbro9OnTFvuk9L1vi8Q+A2/evKkBAwaob9++Wr58ebLBPw8PD73yyis2h0BdXFw0c+ZMTZs2TeXLl09y37jv1Z9++qleeuklqxUmE77fUhvKS/g+TayiIQAAAAAAwLOEyn8AAAB4Zq1evdr8OCIiQh06dEjxGDNmzNCMGTPMy7Vq1dL8+fOfeG5FihRR6dKldeHCBUmxlf6GDx8uSTp16pShgk7C8F9cG2OTyaT9+/ebq7bEr35SqVIl5c2b1+K82bJlMyyHhYWleO5pEUhICScnJ3399dd68cUX9ejRIy1cuNC87bPPPtOaNWtSXLEuIySsgpSaKkVpHVxKGM5IrNJiYmxtQbx9+3a9/fbbVn8Et7e3V8GCBVWqVCmVLl1aFSpUUNWqVVWgQAFdv37dXHnJFvny5VPt2rXNP+xfvXpVx48fV6VKlcz7xP9ccHV1VcuWLZMdN0uWLBoyZIgGDx6sQ4cOaevWrdq1a5e5xbA1Bw4cUL9+/bRo0aJEKwvi6cuSJUuK294mJb2CHRERERo1apTh9SrFfh6OHTtWXbt2tXmsAgUKGJbv3r2borkkbBVraxv3tLyG/6LMdr9+WveTJUuW6PPPP7faDtbR0VGFCxdWqVKl9MILL6hixYqqVq2a3N3dtX//fq1YscLm+VStWlXFihUzt8Q9cOCA7ty5Y3j9xw8EFitWTNWqVbN5fFs5ODiod+/e6t27t06fPq0tW7Zox44dOn36dKJtX8+cOaP+/fvrjz/+MLSLTo+/v7XPwOvXr6t3796JBv48PDxUsmRJlS5dWuXKlVOlSpXk5eUlOzs7+fj4pKhCZbt27dSuXTtdvHjR/NwcO3Ys0dfTtWvXNGjQIM2ePVt16tQxr0/4jxlS836Tnv53ZAAAAAAAgLRA+A8AAABIpWbNmpnDfydPnlRwcLBy5sxpqEhSqFAhFSlSxLxctWpVubi4mH+U3Ldvn9q0aaOgoCBDW7iElQXjJGxjlpqqVQl/lE1tS19bODk5acaMGWrSpIkk6f3339e2bdvMPygHBARo8uTJmjhxYrrNIa0krL6V0gDO48eP07StoWQ5p5S+HmxpH3rnzh199NFHhoCAq6ur+vTpo8aNG6tcuXKJ/jhuaxgkvpdfftnwHlq7dq05/BccHGyoFtmqVasU/TBvZ2enGjVqqEaNGvroo490+/Zt7d27Vz4+Ptq5c6fFe8Pf31/fffedJk2alOLrQPrImTOn4XX777//prg9aXoLDg7W0KFDDe1EpdgA8ffff6969eqlaLyiRYsalq9evZqi4+Mq6MZJrgKZlPbX8F+U8N6amvt1wmPS8379pPcTW8Lt586d08SJEw3BPw8PD/Xr10/16tWTl5dXohVyU3M/6dChg6ZPny4ptnrc+vXr9eqrr0qKrb589uxZ874dO3ZM8fgpVa5cOZUrV07vvPOOgoKCtG/fPu3evVvbt2+3COkGBwdr4sSJ+u2338zrEv79y5Ytm6JApC1MJpNGjhxpCP7Z29urY8eOatOmjSpVqpRkG9zUBqpLliypQYMGadCgQXr06JEOHjwoHx8f7dixw+IzLyIiQp9//rnWr19vrhacFu+3mJgYQ1VjBweHFFVIBgAAAAAAyCi0/QUAAABSqVmzZubHMTEx2rNnj6TYQF+c+FX/pNi2r9WrVzcvx+27c+dORUdHm9e3aNHC6jkTVoA6d+5ciuft6+trWC5cuHCKx7BV3rx5zcE/KTY09vnnnxv2WbZsmXbv3p1uc0grXl5ecnBwMC/HDw3Y4uzZs1YrHT2JYsWKGZbjwqi2iquIlJSFCxcaQnH58uXTypUrNWLECFWrVi3J8F3CH99tuf6WLVsaKmZt3LjRfNz27dsNAZBOnTolO15S8ubNq44dO+qrr77S7t279eOPP6p48eKGfVatWpXiClhIPwmrMD5rrZnv3bunPn36WITmChcurMWLF6cqNJc7d24VLFjQvHz16tUUtX9N+Fnl7e2d5P7pcQ3/RfH/ZtKzf79+0vuJLaHUX375xRAO8/Ly0tq1azVo0CBVqFAh0eCflLowV8eOHQ1tqTds2GB+vHnzZvNjOzu7pxL+iy9Xrlxq3bq1JkyYoJ07d+q3334zVLmVYr8jxv+M8/T0lKPj//077uvXr6f594p9+/bp8OHD5mVHR0f9/PPPmjx5sho3bpxk8E+SITwn2XbfTyh79uxq0qSJRo8erc2bN+vPP/9UgwYNDPtcvnxZ+/fvNy97eHjIycnJvHz16tUU37svXrxo+I6RP39+w/MNAAAAAADwrCL8BwAAgGfWpk2bUvzfBx98YBijb9++hu1Tp05Ns/lVrlxZefLkMS/7+PgoMjJSR44cMa9LGP6TZGhTdvnyZd26dcvQ8rd48eIqVaqU1XNWqlTJ8EPkmTNnUlxNLv6PulLyQZC01qxZM3Or4zijR49O85a4aS1btmwqU6aMefnBgwc6efKkzcfHhUPTUvny5Q0/dp86dSpFoSBb5r9lyxbD8ttvv21zAOXixYuGZVtCANmzZzeEXwMCAnTixAlJ0o4dO8zrCxUqpBo1aiQ5Vnh4uHx9fbVu3TrdunUryX0dHR3VvHlzzZ8/Xy4uLub1kZGR8vf3T3beeDqqVq1qWD5w4ECKjo+Ojk63MGdQUJD69etnEfKqXLmyli1bptKlS6d67PjtSBPeZ5KTMMRXq1atRPdNz2v4r0n4Wj18+HCKg1BP835dpUoVw3JKXmNS6u4no0aNUq5cuWwaP+H9JLGWufEVKVLE8N45cuSI7ty5I8l4P6lZs2aaBysjIyPl5+enTZs2Wcw9ITs7O9WpU0e//fab8ufPb9h26dIl8+OsWbMavoc8fPhQZ86cSdG8wsPDk2ydnvBv1LZtWzVu3Nimsa9fv27xHcTaaz46OlpXrlzRtm3bzPf3pFSsWFGzZs1ShQoVDOsvX75sfuzs7GzYHhUVpaNHj9o07ziHDh0yLHt5eaXoeAAAAAAAgIxC+A8AAADPrGLFiqX4v/hhPCm2RWT87QmrRj0Je3t7ww+iu3fv1smTJw1hvPhBvzgJqybt2rVLPj4+5uX4FQUTcnFxMfy4GRYWpvXr19s85wcPHhiq3UjWA4rpbfTo0YYWxjdu3NCUKVOe+jxSqm3btoblpUuX2nRcZGSk/vrrrzSfj4uLiyHIExoaavHDfWJu375tU3AqYcvQhIGWpCScS1KBg/gSVmDavHmzoqOjDe+ThBWdEpo1a5aqVKmijh07asSIEYaAbVLy5s1rETBIWMkIGad27dqG5VWrVqXo+NWrV6ty5cqqX7++unfvrq+//jpN5hUdHa233npL58+fN6xv2rSpfv/9d7m7uz/R+PErqErGCmZJuXXrliHEVbx4cYsKb3HS+xr+a0qUKCFPT0/zsr+/v6FSWXL8/PwMfzsHB4ckg5tPqlixYobKp1euXLE5PHX8+PFkK//dv3/fotV8wsBhYkwmk7Zu3WpYl5r7SUxMjLZu3ar79+/r+PHjVvdJC6tXr1aVKlXUtm1bvf322za35s2WLZvF98aE95+Er4GVK1emaG7jxo1TpUqV1KxZM/Xt21dr1qwxbE94z7f1byRZ3vMly7/Tv//+qypVqujFF1/UkCFDNG/ePJvGdnBwsAghJnxuatasaVj++++/bRo7zvLlyw3LGfH9GAAAAAAAIDUI/wEAAABPoHnz5ubHAQEBWrx4sXnZy8tLHh4eFseULVvWUOlm9uzZhnZ2ibX8jfPKK68YlmfMmGFz1bxp06YZqrKUKVPGUEXmafHw8NCHH35oWLd06VLt3bv3qc8lJTp37qwsWbKYl//880+bqiP9+OOP6daetGvXrobl77//3qbqfz///LOh1XRiEgbsbA3C/fPPPxZhjfjtHpNSr1495c2b17zs4+Ojw4cPG94nL7/8cpJjeHt7GypDpSQEEFcZKk7C9p3/NfHbXUupa+OYVho2bKhChQqZl0+dOqXVq1fbdGxERIR+/PFHSdLdu3d17NixJNuMpsT3339vUWGvXbt2+uGHH5JsjW2rFi1ayNXV1by8YsUK3bhxI9njEr7Pu3Tpkui+6X0N/0UJ79dfffWVTZ+7kjR58mTDcpMmTWyukpdaCV8f06ZNs+n9Hve+Soq9veX/BGnr/WTBggUWFe7it2dNSps2bQzvcx8fH+3cudN8f3BxcVHr1q1tGstWZcuWNYTe1qxZY/N8k7v/dO/e3XBfXrJkia5cuWLT2H5+flq1apWio6Pl7++vAwcOWPyjmIT3/IcPH9o09s2bN/XDDz9YrE943y9Tpozh3rxt2zabWzrb8tzEf52tWbPG5grN69atM4RdnZyc1K5dO5uOBQAAAAAAyGiE/wAAAIAnUL9+fUMYLH4IxVrVPyn2B/D41avity1zd3dPtrJau3btVKBAAfPyjRs39N577yUb+FqyZImWLFliWDd06NAkj0lPXbt2NVRVMZlM+vTTTy0qAz1L3N3dNXjwYPNydHS0Bg8ebBGYiWMymTR79mybghGp1apVK0O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"text/plain": [
"<Figure size 2200x880 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set_style('whitegrid')\n",
"fig, ax = plt.subplots(1, 1, figsize=(10, 4), dpi=220)\n",
"\n",
"p = FancyArrow(-5, this_year_gregorian, 38, 0.0, width=1, \n",
" length_includes_head=True, \n",
" head_width=0, head_length=0, \n",
" shape='full', overhang=0, \n",
" head_starts_at_zero=False, \n",
" transform=ax.transData, \n",
" zorder=-1, color=highlight, alpha=0.5,\n",
" clip_on=False)\n",
"\n",
"\n",
"label = 'Not working'\n",
"sel = data.day_type == label\n",
"tmp = data.loc[sel]\n",
"clr = red; mrkr = 's'; s = 80; alpha=1.0\n",
"ax.scatter(x=tmp.day_number, y=tmp.year, s=s, color=clr, marker=mrkr, label=label, alpha=alpha)\n",
"\n",
"label = 'Half working'\n",
"sel = data.day_type == label\n",
"tmp = data.loc[sel]\n",
"clr = pink; mrkr = 's'; s = 40; alpha=1.0\n",
"ax.scatter(x=tmp.day_number, y=tmp.year, s=s, color=clr, marker=mrkr, label=label, alpha=alpha)\n",
"\n",
"label = 'Trying to work'\n",
"sel = data.day_type == label\n",
"tmp = data.loc[sel]\n",
"clr = blue; mrkr = 's'; s = 4; alpha=1\n",
"ax.scatter(x=tmp.day_number, y=tmp.year, s=s, color=clr, marker=mrkr, label=label, alpha=alpha)\n",
"\n",
"x = 31; ha='left'\n",
"for year, non_working_days in by_year.items():\n",
" workign_days = (31 - non_working_days)\n",
" ax.text(\n",
" x, year, workign_days, ha=ha, va='center', fontsize='xx-small', color=gray\n",
" )\n",
"ax.text(x, by_year.index.max() + 0.5, \"Working\\ndays\", ha=ha, ma='left', fontsize='xx-small', color=gray)\n",
"ax.set_xlim(data.day_number.min() - 0.5, data.day_number.max() + 0.5)\n",
"ax.set_ylim(data.year.min() - 0.5, data.year.max() + 0.5)\n",
"sns.despine(left=True, bottom=True)\n",
"ax.legend(bbox_to_anchor=(1.15, 1), loc=2, frameon=True)\n",
"ax.set_xlabel('Days since Tishrei 1$^{st}$')\n",
"ax.set_xticks([0, 10, 20, 30])\n",
"ax.xaxis.grid(False)\n",
"\n",
"ax.add_patch(p) \n",
"ax.set_ylabel('Gregorian\\nyear', **ylabelparams)\n",
"fig.suptitle(\n",
" f\"{31-by_year.loc[this_year_gregorian]:.0f} working days in the {this_year_gregorian} holiday season\", \n",
" y=1.0, fontsize='x-large'\n",
")\n",
"fig.set_facecolor('white')"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"ExecuteTime": {
"end_time": "2021-08-24T07:59:38.288096Z",
"start_time": "2021-08-24T07:59:38.024646Z"
}
},
"outputs": [],
"source": [
"! atom holidays_in_tishrei.ipynb"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"_draft": {
"nbviewer_url": "https://gist.github.com/1c91ff0eed54518157f5e74afab06603"
},
"gist": {
"data": {
"description": "2018 holidays_in_tishrei.ipynb",
"public": true
},
"id": "1c91ff0eed54518157f5e74afab06603"
},
"hide_input": false,
"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": "3.8.0"
},
"toc": {
"base_numbering": 1,
"nav_menu": {
"height": "11px",
"width": "252px"
},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": "block",
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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