dost.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T13:49:59.568004Z",
     "start_time": "2023-09-08T13:49:57.228876Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "from pathlib import Path\n",
    "from math import factorial\n",
    "import random\n",
    "import math\n",
    "from tqdm import tqdm\n",
    "from datetime import datetime\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T13:49:59.583512Z",
     "start_time": "2023-09-08T13:49:59.570966Z"
    }
   },
   "outputs": [],
   "source": [
    "sns.set(\n",
    "    font_scale=2,\n",
    "    style=\"whitegrid\",\n",
    "    rc={'figure.figsize':(20,7)}\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T13:49:59.599499Z",
     "start_time": "2023-09-08T13:49:59.586504Z"
    }
   },
   "outputs": [],
   "source": [
    "pd.set_option('display.max_rows', 20000)  \n",
    "# печать всех строх, аналогично max_columns\n",
    "\n",
    "# You can also reset an option back to its default value like this:\n",
    "# pd.reset_option('display.max_rows')\n",
    "# And reset all of them back:\n",
    "# pd.reset_option('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:00.678289Z",
     "start_time": "2023-09-08T14:04:00.390028Z"
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('qwe.csv')\n",
    "df = df[df.hours.isna() == False] \n",
    "#df = df[df.send_datetime.isna() == False]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:00.963575Z",
     "start_time": "2023-09-08T14:04:00.681249Z"
    }
   },
   "outputs": [],
   "source": [
    "df['send_datetime'] = pd.to_datetime(df['send_datetime'])\n",
    "df['send_datetime'] = df['send_datetime'] + pd.Timedelta(hours=3)\n",
    "df['to_pick_time'] = pd.to_datetime(df['to_pick_time'])\n",
    "df['to_pick_time'] = df['to_pick_time'] + pd.Timedelta(hours=3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:01.376219Z",
     "start_time": "2023-09-08T14:04:00.966567Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "''"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='hours', data=df)\n",
    "plt.title('Ящик с усами для количества часов доставки в ПВЗ')\n",
    "plt.xlabel('Часов')\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:01.407488Z",
     "start_time": "2023-09-08T14:04:01.380180Z"
    }
   },
   "outputs": [],
   "source": [
    "perc25 = df['hours'].quantile(25 / 100) \n",
    "perc75 = df['hours'].quantile(75 / 100) \n",
    "interq = 1.5 * (perc75 - perc25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:01.423007Z",
     "start_time": "2023-09-08T14:04:01.410022Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20.329382090625003"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perc75 + interq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:01.502650Z",
     "start_time": "2023-09-08T14:04:01.475875Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.836102194846881"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.hours > perc75 + interq].shape[0] / df.shape[0] * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.8% - Доля выбросов (выше 1.5 межквартильных размахов от 75 процентиля)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:02.122547Z",
     "start_time": "2023-09-08T14:04:02.060757Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{10: 3.1594823383611113,\n",
       " 20: 5.069302654666667,\n",
       " 30: 6.596295932583333,\n",
       " 40: 8.131690315277778,\n",
       " 50: 9.364315575694445,\n",
       " 60: 10.298966634000001,\n",
       " 70: 11.132383455694445,\n",
       " 80: 12.363303586388891,\n",
       " 90: 16.23421730761111}"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "percentiles = [10, 20, 30, 40, 50, 60, 70, 80, 90]\n",
    "result = {x: df['hours'].quantile(x / 100) for x in percentiles}\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Время доставки в часах, процентили"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:02.960652Z",
     "start_time": "2023-09-08T14:04:02.460593Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "''"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=list(result.keys()), y=list(result.values()))\n",
    "plt.title('Время доставки в часах, процентили')\n",
    "plt.xlabel('Процентиль')\n",
    "plt.ylabel('Часов')\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:02.991856Z",
     "start_time": "2023-09-08T14:04:02.964633Z"
    }
   },
   "outputs": [],
   "source": [
    "df['send_datetime_hour'] = df['send_datetime'].dt.hour\n",
    "df['send_datetime_hour'] = df['send_datetime_hour'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:03.022804Z",
     "start_time": "2023-09-08T14:04:02.993852Z"
    }
   },
   "outputs": [],
   "source": [
    "hourly_grouped = df.groupby('send_datetime_hour', as_index=False).hours.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:03.054718Z",
     "start_time": "2023-09-08T14:04:03.038761Z"
    }
   },
   "outputs": [],
   "source": [
    "#hourly_grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:03.959867Z",
     "start_time": "2023-09-08T14:04:03.212267Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "''"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=hourly_grouped.send_datetime_hour, y=hourly_grouped.hours)\n",
    "plt.title('Время доставки в зависимости от часа отправки (медиана)')\n",
    "plt.xlabel('Время')\n",
    "plt.ylabel('Часов до доставки')\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:03.975078Z",
     "start_time": "2023-09-08T14:04:03.962858Z"
    }
   },
   "outputs": [],
   "source": [
    "hourly_grouped_num = df.value_counts('send_datetime_hour', normalize=True) *100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:03.991014Z",
     "start_time": "2023-09-08T14:04:03.978049Z"
    }
   },
   "outputs": [],
   "source": [
    "#hourly_grouped_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-09-08T14:04:04.733929Z",
     "start_time": "2023-09-08T14:04:03.994030Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "''"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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66adnzpw5ueuuu3LwwQcvsJ9k/o2WE044odZjmjFjRr1CnSFDhiRJDj300PTv3z8rrLBCcd3w4cPzv//7v5kwYUJGjhyZq6++eoGh0T788MOcffbZqaysTHl5ec4666x8//vfrxFonXXWWbn77rvzq1/9KpWVlfnVr36VLbbYYqFDjH3xxRdJ5g9FVNsT8f/5z3/qDHXmzp2bfv36FcOTAw44IOeff/4CT+a+/vrrOeWUU/Lpp5/m3nvvzXbbbZeDDz641v1utdVWdZ7zkSNH1hrqLK2alrZhw4bVuIlYm8b+HNRl4sSJufbaa5PMD0L+/Oc/Z7fddiuu//GPf5zevXtn2LBh+eKLL3LbbbflJz/5SXH96NGjc8MNNxS3v/baaxfam+ftt9/OD37wg0ycODEzZ87MAw88kB/+8If1qvHjjz8uhjVHH330Qoc9evnll4ttOnbsmJtvvjkbbbTRAu3+85//5KSTTsrMmTMzYcKEPPXUU/nud79bXH/11VcXA52ePXvmqquuqvH0ePUhDW+77baceuqpxVCosrIyP/rRj4qBzlZbbZXLL798gRBs0KBBOe200zJ58uS8+eab+c1vflNr4JwkO+2000IDu7lz56Zv377597//nUKhkJtuuil/+MMfat1PfdT2XlWeeeaZWm8uv/vuu/nFL35RDHSOOOKInHPOOTXO31lnnZVbbrklF154YebOnZtbb701W265ZY1/g8ase3HO0aRJkzJp0qR069YtV199dY3v0k9/+tOcffbZefTRR4vft4EDBy7Qy+YXv/hFMdDZcccdc8kllyww3ODo0aNzyimnZNSoUXnxxRfzt7/9Laecckqtx7b55pvn9ddfz7hx4zJixIiFfq6T+T1vkvlB0syZM2vd31tvvVUMuNu0aZPf/va3NebBS5Jzzjkn1157bS6//PJUVlbmjDPOyMMPP5yVV1651v0ubVdccUUmTpzYKPu6++67i9fili1b5rzzzssRRxxRozfnOeeck1//+te59957M3fu3Pz85z9P9+7ds84662SDDTZYaEBT/ftx2GGH1To84Zc15HtX3aBBg1JeXp5f/vKXNYKU008/PQ888EB+/vOfZ86cObnvvvtywAEHLBDUVX/oYNddd82f/vSnGn/HJPNDmYsuuqg4xOh9992Xs846a4F2Vbp27Vrr7/qHHnooZ5xxRpLkjjvuSL9+/erV66dQKOT6669PkmyyySb529/+tshtvmzGjBm5+OKLF3s7AFhWLXqAdwCAWnzwwQfp06dPpk+fnmT+U+4HHnhgcX3V3CXJ/Jtftc2p8J3vfCc77bRT8fWXb+5PnTo1d955Z5L5w7tdeeWVCx1GaY899shJJ51UfH3HHXcswVEtnl69euW3v/3tAjc4unfvnr/+9a/FJ7JvuOGGTJ48uUaba665pnhD+LTTTstxxx230CFSvve97xXHjZ89e3axl8SXTZs2LUkWe2iU6h599NHi8Ga9evXKxRdfvND9bbHFFvnzn/9cvCn2l7/8JXPnzl3i9y21mhalUCjkggsuyLx589K+ffs6h99r7M9BXd59991ssskm6dy5c3r37l0j0Enm3/St/h0ePnx4jfUPPfRQsUfYMcccU+vwbN/85jdz/PHHF1/X1Qvry2655ZbMmTMn5eXlOfbYYxfapvq15dRTT631xnePHj1qBHtfrmP69OlZb7310rFjx1x88cULDAe03377ZaWVVkqSVFRU5L333iuuu+eee4o3XldfffVcd911CwQ6yfw5l66++uricJD33HNPMQhYHC1atMgPfvCD4uv69tJYWq688spiz7K99torF1xwwQLnr6ysLMcee2zxRm6SXH755Utt+KPFPUdt27bN9ddfv0A4uuKKK+ayyy7LxhtvnGR+T8EvB7RvvPFGHn/88STJhhtumL/97W8LnT9qnXXWyVVXXVX8HXHDDTcUr9ULs8ceexS//1X7/7JCoVAMNeuayySZP1Ri1b/Tr3/96wUCnWT+eevbt28OP/zwJMlnn32WW265pc79Lk0jR47MrbfemmT+d6shKisrc+WVVxZfn3322TnyyCMXGJ5zxRVXzIUXXphdd901yfz5zapvt6yqCuK/7MADD6zxvas+91Iy//geeeSRJMkKK6yw0L9jkvkh2JlnnlnshTRjxowlun4l8x/IqLpGVlRULDDsYW2ee+654rV3SeZGTJK//e1vxTkYG/qZAoBlgVAHAFjARx99lOuvv36h/1111VW58MILc+yxx2afffbJf//73yTzbwpdfPHFNW4KHHnkkTn11FNzxBFHZJdddqnzPasmYE6ywA2vZ599tnhTauedd84WW2xR636OOOKIrLfeetl1112z/vrrL/axL65zzjmn1rlbNt988+LEwhUVFXn22WeL6yoqKvLAAw8kmX9jsfoN8IU5/vjji8O3/etf/0pFRcUCbaZOnZok+drXvrbYx1Gl+tj8ffv2rXUc/mR+z4Sqm/rjxo0rDvfS2JbFmhbl/vvvL/ZSq96748uWxuegLj169Mjtt9+eF154Ib/4xS8W2mbcuHHF5S8PJ9SzZ8+cccYZOfLII4s3gGtT13e6NtOnTy+GsTvssEOtT77vs88+6devX773ve/lgAMOWOI6fve732XgwIEZNGhQVllllQW2nTRpUo1eENXPR/X5TE455ZRa/42TFCcaT+YPS1k9lFoc1XtOLGw+o6/KrFmzioFDWVnZQoemqu64444r3kgdP358Xn755aVW2+Kco6OOOiprrbXWQte1bNkyJ598cvH1Y489VmN99ZDnhBNOqLXnQjJ/SKqq3klffPFFnnzyyVrbdu7cOVtuuWWS2kOdV199tTgkVl2f/08++STPPffcAjXUpvrxVl2XmkLVvCcrrrhiTjvttAbt65VXXsmHH36YZH6P4aOPPrrO9tV/pz/yyCN1zuvV1L7xjW/U2QP2mGOOKX4f3nrrreJ5SOZ/N37xi1+kT58+OeWUUxYaSFZp3bp11l133eLr+l7PF6b6+9T3GlbVS6dDhw7ZZ599Fvs933///dx4441J5g/dtrjDtgHAssjwawDAAsaOHbtYw1R06dIll1xyyQJP7S/sieCFmTp1aj755JPi6y8/xV19KLSqp2hrs8oqq9QYDm5p2nDDDRcZHO22227FG3jPP/98DjrooCTJf//73+LNoqo5hurSunXrbLrpphk0aFBmz56dt956K1tvvXWNNlXnsK6bM3WZM2dOjUmpN9lkk0Vus/XWW+fFF19MMv/mWWNPsL0s1rQo06dPL84FscEGG+SYY47JzTffvNC2S+NzsCTmzJmTyZMn54EHHshtt92WZP7N+sMOO6xGu+22265eN8S+/BR2fXtm/PWvfy32Wqrriexdd911kdeCZP5T5dVDqvrUUSgUMmvWrLzzzjs1JtXebrvtsvbaayeZH2q89tprSeafpz333HOR+913333z4IMPJskSz+vw1FNPFZdrm6/jqzB06NBioLjxxhunW7dudbYvLy/PXnvtVbyxOnjw4IXOUdMYFuccfec736lz/c4775xWrVqlsrIyQ4YMyaxZs4rf0er/hvW9LlUFQa+88krxd8HC7LXXXnn11Vfz9ttvZ+zYsQuc36pA8Wtf+1qdc99UzWGSpNjrqC6rrLJKVl999YwfPz7jxo3LJ598stCwc2kaOHBgcR6qH/7wh7X28K2v6gHinnvuWedDAcn8+cw23njj/Pe//01lZWWGDh3a5PML1Wbvvfcu9gBcmFatWmWnnXYqBnQvvPBC8ZreoUOHRQbzVcaNG1cj3FrSnnZjx44t9p5r1apV8Xpal2effbb4b3jYYYct8nfkwvz2t79NZWVlVlhhhfz85z8viR5YALAoQh0AYLG0bt067du3T5cuXbLJJptkhx12yN57773AXAMLM3Xq1IwePTpjxozJmDFjMnr06IwYMSLvvvtu8cZTkhrLSYpDZiT5Snrf1FddEx1XqX5TsfpTsqNGjSouv/XWWzV6E9THhx9+uMDN/IYOLfLhhx/WuHGzsCHuFrV9Y1uaNQ0cOLDOYcGqh0mL44orrijO/3PeeefVedNtaXwOFteBBx6YESNG1PhZmzZtct5556Vnz551bjt79uwa3+n3338/77zzToYPH16jF9GXv9NfdtNNN2Xs2LF55plnksy/Wbmo3n3VTZ8+Pe+//37GjBmTsWPH5r333svbb7+dkSNH1rgBuag6nnjiiRq9Fapss802ufzyy4uvP/nkk+JT5mussUZxiLa6dO/evbhcPWhalMrKykyaNCkPPfRQ/vKXvySZHyQdddRR9d5HY6tef21D331Z9Xb1mS9kcSzJOWrVqtUiv2+tW7dOt27d8t5772XOnDn59NNPs+aaa2bOnDk1Qsv6PsBQZVHXyj322KM4sf3jjz9eY0i5OXPmFIfN2nfffdOqVata91P9+vLoo48u0fVlYaHO9OnTi70nalM1LOvimDlzZn7/+98nSdZee+0cd9xxS3wdrrKkn9WqXsiN/VltTPUJE6v/zVTVu6s2n3zySfE6OmbMmIwaNSrDhw/PRx99VKPdoq6j1c2bNy/Tp0/P66+/nt/85jfF6+b+++9f57CkTz/9dIYMGVIcZnCttdaqMbxufT355JP597//nSTp06fPIgNoACgVQh0AYAHbbbddcVLchqqoqMiAAQNy11131Tm/QYsWLWqd/6RqIvMkdd4E+KrVZxLp6sM1VT+OqqHSltTCtq8a576+kzV/WdWEyUuqoce0MEuzpgEDBjRo3wszatSo4lwU3/nOd9KjR4862y+Nz0FjmDdvXp1Duz355JO5+eabM2TIkFqf2q7rO/1l1Xsy9e3btzh30KJqrOpZ9NZbb2XevHkNrqM2c+fOrTFUUPXPZX2vSZ06dVro9l92zjnn5Jxzzql1fXl5ec4888xFBm5LU/X5wep7/NWHhWzo57YxzlGHDh3qDFyrVD++iRMnZs0118znn3++WDe2v2xRx9+tW7d07949w4cPXyDUeeGFF/LZZ58lqXvotfq8z6JU9Zpb2H6XxqTz1ec9Offcc+v1sMiiVP+uVf8O1qV6u6V1jW0M9fkbpPrnt/rfINV/dt111+Whhx4qPoywMPW9jg4aNGiR4eF2221X6/CfVaoPd7jrrrvmd7/73WL//Td79uxceOGFSeb/XfS///u/i7U9ACzLhDoAwFIzYcKEnHjiiQv0AigvL8/qq6+eDTbYIJtttll69OiR559/Pn/9618Xup+lNal2Q9XnhmD1G83Vn6iufnNkm222WWDC+kWpmnOhyqefflq8ebWkwzJVr+kb3/hGjjvuuMXavra5KRpiWaypLtXngjjrrLMW2b6xPwdL4vjjj8+nn36aL774Im+99Vaef/75VFRU5Pzzz0+nTp2Kc8Ek87+LZ599dh566KEF9tOlS5est9562WSTTbLtttumvLw8ffr0Wex67rnnnnzrW9/KzjvvXGubL774IqecckpxmL0qZWVlWXXVVbP++utn0003zXbbbZdx48blvPPOq9d7b7DBBjnzzDNTUVGRTz/9NI8//ngmTJiQoUOHpm/fvrnzzjvTunXrGjf0a5tT68uq/1svagioupSVleXdd9/NjBkzivMrNaUlOf76brOk6nOO6nP9TmrWXXUNr/47qU2bNos970t9hsjcc889M3z48Lz22muZOHFiOnfunOT/hl5bY401FtlLr3rtu+++e771rW8tVp31GR6rsXzwwQfF4fn23HPP7LTTTo2y3yX5rlb/vb20P6sNUVcvrSoL+/xWeeWVV/KjH/1ogZC5devWWXvttbPhhhtmyy23zI477pj+/fsv8bCRX/bFF19k9OjR2XzzzevV/sUXX8zdd9+92L9Prr322mJPq5///Od1znsFAKVGqAMALDVnnHFGMdDp3Llzjj/++PTs2TMbbLDBAv9zXdfE0dV7u9T25HBTqM/wMtVvlnTp0qW4XP2YVl111TonO66Pqvk9kprDPC2O6jUVCoUG19QYlmZNN998c509aa644oriUE71MXDgwOLY/yeffHK95qJo7M/Bkvjy3B633XZbzj///CTJ5Zdfnn333bd4Y/Pqq68uBjqtW7dO7969s9tuu2XjjTeucSzJ/LkQ6uuBBx7IyJEjc8EFF2TChAnp27dv/va3v9U6BNtvf/vbYqDTvn37/M///E969eqVb37zm2nXrl2Ntrfeemu961hrrbVq/BucfvrpOeqoo/Luu+9m+PDhGThwYA466KAaT4xX77VSl+rtvnyuqttvv/1qDO04b968zJo1K+PHj8+TTz6Zzz//PHfddVfGjx9fvAn+VVuax18fjXGO6jvZe/WeGt/4xjeS1Dz+2bNn59hjj22UXiXV7bXXXvnzn/+cefPm5cknn8wRRxyRWbNm5YknnkhSvyHfqp/n9ddfv9GuL6uvvnqNuYsWZrfddlvkcF/V/fa3v01FRUXatGlTZy+sxVW9101TfFaXpvp8hqt/fqv/DTJ58uSceuqpxb9RNt544xxzzDHZaqutstZaa6VFixY19jNz5sx61dStW7f07t27+LpQKKSysjKTJ0/OSy+9lHfeeSf//e9/c/zxx+eOO+6odUjd888/P+utt14uuOCCvPPOO7n00kszffr0/OQnP6lXHePHj8+1116bJNlll12y++6712s7ACgVQh0AYKl4/fXXize4V1xxxdxxxx11DgtW182Wbt265fXXX0+SvPfee4t8OvmSSy7J7Nmz061btxx66KFp3779EhzBor377ruLbFN9yLnqY7lXX37jjTfq9X5Tp07NSiuttNCn/Ksmlu7UqVPWXXfdeu3vy1ZbbbW0bNkyc+bMyYQJE/Lxxx9n1VVXrXOb6dOnp3Xr1ou8obmkTzsvzZoa08yZM4vDEa277rr5n//5n3pt19ifg/qaO3fuAjftqhx11FEZMGBA3n777XzwwQcZN25cunXrloqKivz9738vtrv44ouz77771voeVUNEJYueg6F9+/Y54IADir2x5s6dm5/+9Kf55z//ucC/9yeffJL7778/yfzP1Q033JAtttii1n1Xv7bUVkdt56NTp0758Y9/XBwO7sUXX8xBBx2U1VZbLa1atUplZWXGjx+fadOmLXJeneo9Fuu6Fu6000455JBDFrruo48+ymGHHZYJEybkxRdfzDPPPJNvf/vbdb7v0rDmmmsWl99+++16bTN8+PDickPntWiMczRjxoxFXk9mzpxZfNJ/xRVXLPawWWGFFdKlS5dMmDAhhUIhb7zxRrbZZps6a666Kd62bdv6HGI22GCDrLPOOhk9enQef/zxHHHEEXnqqaeKc4wtaui1ZMmuL1OmTEnHjh2/0h4qTz31VDEEPumkk5Z4XriFqf5Z/XKv4do05md1aVrcv0Gqn4u77rqrOBzbJptskgEDBtT5O7O+1/OuXbvWGh4WCoWcddZZeeCBBzJ9+vT8+c9/zp///OeFtm3dunW23Xbb3HjjjTnooIMyYcKEXH311dlyyy3r1aP1oosuyqxZs9K6detFDvUGAKVoyf9PEACgDtV7juy444513sQsFAo1hvX48twY1UOc5557rs73nT17dm677bb84x//yGWXXbZUb+wPHTp0kb11qvdAqv6k6FZbbVUc/mfMmDGLvOFWUVGRfffdN5tvvnn22muvGjenCoVC8X169eq1xDfj2rZtW2Pi5YUNsfVlZ555ZjbffPPsvPPOufvuu2usq/7vuKQBRGPXtLRcddVVxcmkzzvvvHoNi5M07uegPn73u9/lkEMOyc4771znnDnVh12aOHFikvmBalVPuY4dO9YZ6CT/FzQm9Z9Yu0ePHjnmmGOSzH8KvX///gu0efPNN4tDCnXv3r3OQKeuOgYPHpwf/vCH2WGHHXLTTTfVun31c1F1E3SFFVYo9hQpFAo15n+oTdXk9kkWGUzXpmvXrjn88MOLrxtrOKTFtcUWWxQ/48OGDcuYMWPqbD9v3rxiD5NkyY+/PhbnHFVNoF6bp59+ungd22WXXWoM2bbtttsWl6uGRKvLZZddVhzK6sorr1xk+2T+MGRJ8vLLL2fatGnF61/37t1r7eFQXfWgaciQIfnkk0/qbD9p0qT06tUrW2yxRfbdd98aN/KXloqKiuK8J2uuuWZOPPHERt1/9XPw2GOP1Tr3VpXRo0cXg8oWLVos8vrSlBb1+Z09e3ZeeOGFJPOHXqs+pGXVgzLJ/N6adf2tNG7cuBq9rhZ1DmtTVlZWY760wYMHL3Kbzp0751e/+lXx9S9/+ctF/t314osvFq/JJ5xwwlc+DCsAfBWEOgDAUlH9hvGihjz5xz/+kXHjxhVff3kOnb333rt4w+HJJ5/MyJEja93X/fffX3ySeZdddlmqoc6sWbNy3XXX1bp+yJAhef7555PMnyR8++23L65r165d8YZdklx44YV1TkJ84403ZtKkSamsrMyMGTNq3NB74YUXioHCXnvttcTHk9Qciuu6666r8ybgq6++mqeeeiqFQiGffvrpAuPj1zWWf1PVtDR8+OGHueGGG5LM/6zusMMO9d62MT8H9fHaa6/lv//9byZOnJgHHnhgoW3mzZtXIyyqGr6o+nd6xowZmT17dq3v89Zbb9W40V1ZWVnvGk8//fTi/CHPPPNMnnnmmRrrq9fx5bkgvuzJJ5+scVO/+rVl5syZeeqppzJp0qTccccdtQ4vNGzYsOJy9aGcDj744OLylVdeWeeNxjfeeKNGqFOfobNqUz20rbrWfdVWXHHF7L333knmh1p/+MMf6mx/8803F69RK6+8co1r4dJQ33N0/fXXZ9asWQtdV1FRkb/97W/F19XnlkpqXpfuueeeOgPWsWPH5s4770wyPyStPnRcXaquDZWVlXnwwQeLDzXUp5dOkqy33nrFa2BlZWUuuuiiOtv/6U9/SmVlZWbPnp127dpl5ZVXrtf7NMRNN91UDAV/8YtfNPrv7B49eqRr165J5g/JtajhGKt6XCbz/4ZYWj19G8PQoUPz0ksv1br+xhtvLA6/1qtXrxq9CRfnb7Qvf24aMs/hkly/9thjj+IcSxMmTFhkKPrrX/86yfyevieddNISVgoAyzahDgCwVGy00UbF5VdeeSWPP/74Am0qKipy1VVXLXDD4Ms3Vzt37pwjjjgiyfwbUz/84Q8zatSoBfY3aNCg4r7Kysq+kvlJrrnmmtx+++0L/Py1117LqaeeWuwZ8LOf/WyBm1U//OEPiz979dVXc9ppp9UY/77K/fffnyuuuKLGdtWfGK8aN75z587ZddddG3Q8hxxySHGIlilTpuS4445b6BAvb775Zk4//fTi8e29997ZcMMNa7SZMGFCcbkhN8Yas6alYdy4camoqEjbtm2XaC6Ixvoc1MeBBx5YXP71r3+9wLw38+bNy6WXXpoPPvggyfx5fqp6qqy77rrFcK6ysjJ//OMfF9oD54knnsgJJ5xQI8ip7cb5wrRv3z79+vUrvr7wwgtr7Kv6teXDDz9caC+befPm5a677lpg/oXq15btt9++OEfK+++/n379+i0wZ9cHH3xQI7Do2bNncfmggw4qfi7Hjx+fE088MR9//PECtQwZMiR9+/Yt3gg95JBDsvHGG9dxBmo3derUGmHZks6f1RhOOumk4uf20UcfzS9/+csFrt2FQiG33357jRvlZ5111lIN2xfnHL3//vs57bTTFvh3nzZtWk477bTi0FXbbbddjfA1mX/Df6uttkoy/3fZiSeemFdffXWh79G3b9/id2DzzTevda6oL9t8882LgcRll12WysrKlJeX5zvf+U69tk+S0047rXgjfeDAgenfv/8C38e5c+fm2muvzR133FH8WfUeFUvTe++9lyTZddddl8pQgi1btszJJ59cfH3RRRdlwIABC1y7Zs6cmXPPPbc4V1Dbtm1zxhlnNHo9ja1fv34L/dzdeeedxaHNWrVqlZ/97Gc11le/jt5+++3Fa351kydPzo9//OMF/n6r7/w6C1M9VFuc69fPf/7z4u+ff/zjH3n//fdrbVv1mTrnnHPqPdwhAJQac+oAAEvFDjvskA022CAjR45MoVDIKaeckl69emXjjTfOCiuskPHjx+fpp58uPiFaNT9FsvCn73/2s5/l1VdfzX//+9+MHTs2Bx10UHbZZZfiTYGhQ4fmhRdeKN6o6dOnz1IfNqWq5l/96le56667stNOO6VVq1Z566238uyzzxaHKNlzzz1z6KGHLrD9N7/5zfzyl7/Meeedl0KhkCeeeCKDBg3K7rvvnrXWWiuTJ0/O4MGDa/QU2HXXXXPUUUclmX/T5r333ivOXbTWWmvlH//4R501Vx8maeTIkbn++uuz1VZbFYdDatOmTf70pz/lmGOOyRdffJH33nsv3/3ud7Pzzjtnk002SUVFRYYNG5bnn3++eK5XX3314jBZ//73vzNy5MhMmjSp+GR6UnMs/8XV0Jq+Kj/84Q+LN2AXR0M/B4vjsMMOy+23356RI0dm9uzZ6dOnT3r06JGtttoqFRUVeeGFF2rMkXLqqacWbwi3b98+hxxySPHG74033pgXXngh22+/fb72ta/l008/zUsvvZTRo0cnmX8zde7cuSkUCovsUfNlhx56aO6444688cYbef/993PzzTcXQ9p11103vXr1KvaC+93vfpd//etf2WqrrdK+fft88skn+fe//13sGVLbtaXqRmfVzc6nn346e+21V/bYY4+suuqq+eCDD/LII48Un2hfa621aoRiK6ywQv785z/n6KOPzhdffJGhQ4dmn332ya677pr1118/c+bMydChQ/Pyyy8XP5ff/OY3c95559V57M8999wC8wDNmDEjY8eOzfPPP18cEqtTp07ZZ599Fuu8NqYNN9ywxuf2jjvuyFNPPZXddtstq622WqZOnZrnnnuuRs/KQw89tEYPlyXVWOeoVatWefbZZ7PXXntl7733TteuXfPRRx/l0UcfLe7/61//ei644IKFDmv5xz/+sTh/z4QJE3LUUUelZ8+e2XLLLVNWVpZRo0blqaeeKgZ6HTt2zCWXXLJYx7rHHnvkH//4R7En2LbbbrvIecWq22mnndK3b99ir6MBAwbkySefzG677ZauXbtmwoQJeeGFF2rcJD/mmGPqHTw1hhVWWGGpznty2GGHZfDgwXnggQcyZ86c9O/fP7fcckt22mmndOzYMR9++GGeeuqp4oMI5eXl6d+/f9Zbb72lVlNjaNWqVSZPnpyjjz46u+yySzbbbLNUVFTk+eefz1tvvVVsd8YZZyxwLIcffnhuuummzJ49O5MnT87++++fvfbaK+uss04qKiry3nvv5dlnny1e/xb1N1qVjz76KNdff32Nn1VWVmbixInFv+GqHHnkkfU+1nXXXTfHHntsbrjhhlRWVubCCy/M1VdfXWv7Xr16NbjnMgAsy4Q6AMBS0aJFi1xxxRX5wQ9+kA8//DBJ8vzzzxdvxFa3zTbbpF+/fjn66KOTpMb/9FdZYYUVcvPNN+eMM87I008/ncrKyjzxxBM15mlI5t+M6du3b04//fSlcFQ1bbXVVtlyyy1zzTXX5L///e9C6z722GPr7L1x2GGHZaWVVkr//v0zZcqUfP7557nvvvsW2vbQQw/Nr371q+LNxauuuqrGOPevvPJKXnnllXrX/9Zbb+Wtt97KKaecUmOOi4033jgDBgzIj3/847z77ruZM2dOnnrqqeITzF8+B5dffnlxmJ6BAwcuUP/666+fHj161LuuhWlITV+FtddeO8cff/wSb9+Qz8HiaN26da699tr06dOn2AvhP//5T415Z5L5Pd1+9KMf5Xvf+16Nn59zzjn54IMPikHiO++8U2Mi7iqrrbZafv/73+fnP/95xo4dm0mTJi1yUvovv/+5556bI444IoVCIX/9619z4IEHFodlu/jii3P88ccXA6ihQ4dm6NChC+xnww03zEUXXZQjjjgilZWVGTlyZCoqKoo9Rb773e9mwoQJueyyyzJnzpxMnjw5d9111wL7WXvttXP11Vcv0MOke/fuNT6XM2fOzMCBAxd6TAcffHB++ctfZsUVV6zz2AcOHFjrPqq0b98+l19+eTp27Fhnu6XtsMMOS/v27fOrX/0qU6ZMyYQJE2r09qjSqlWrnHHGGTnuuOMa5X0b6xxdeOGF+c1vfpPJkydnwIABC6zfcMMN87e//a3WOeG6du2au+++Oz/+8Y8zdOjQFAqFvPTSSwsdEmu99dbL5ZdfXmOOpvrYa6+9aoT19R16rbof//jH+frXv55LL700M2fOrPXfqUWLFjnxxBNr9JT7Kvzv//5vunXrtlTf46KLLkrXrl1z3XXXZc6cORk5cuRCh3Lt0qVLLrnkkqU+RGBjOPbYYzNixIi8+OKLefrpp/P000/XWL/CCivkN7/5Tb773e8usG23bt1y6aWX5owzzsisWbNSUVGx0LmhysrKcvjhh2eTTTbJL3/5yyQL/xutytixY2v0zKvNMcccs9gB78knn5yHHnooEyZMyDPPPJN///vfNeYJqtKqVaulGhICwLJAqAMALDXrrLNOHnjggdxyyy156qmnMnr06MycOTNt27ZN165d07179+y333759re/nbKysqy77rp57733MmbMmLz++usL9LRp3759rrrqqrz00ku5//7788orr2TixIkpFApZddVV07Nnzxx99NFfyZBbVX76059mp512yk033ZShQ4fm888/T5cuXbLddtvlqKOOqldvoX322Se9evXKXXfdVezpMmXKlLRq1Spdu3bNt771rRx22GFfyfwwVTbccMM89NBD+de//pXHHnssb731ViZNmpR58+alc+fO2WyzzbL//vtnjz32SHn5/43oW1ZWVgwbOnfunJ49e+ZnP/vZYg8T1pg1fRUaYy6Ir+pz0LVr19xzzz154IEH8sgjj2TEiBGZOnVqWrZsmVVWWSXbbLNNevfuvdB5P9q2bZsbb7wx999/fx566KEMHz48n3/+eVZYYYWsvPLK2XDDDbPLLrvkoIMOSps2bbLjjjsWb5Y/+OCD6dOnT73r3GKLLXLwwQfn3nvvzfTp03PZZZfld7/7XZL5vSfuuuuu3HHHHXnkkUcyatSoTJ8+PW3atEmXLl2y0UYbZY899si+++6bli1bpmfPnnnuuecyc+bMPPHEEzXmRznhhBOy88475/bbb8+gQYMyfvz4VFRUZKWVVsqGG26YPffcM9/73vdqHcan6nP58MMP5/HHH8+bb76Zzz77LIVCIauvvnq22267HHrooQ3qOdiiRYu0b98+a6+9dnbcccccddRR6dKlyxLvrzHtu+++6dWrV+688848++yzeffddzN16tS0bt06a6+9dnbaaaccccQRWW211ZZqHUtyjrbaaqs8/PDDuf766/Pkk0/mo48+Sps2bdK9e/cccMABOeiggxY5H9iqq66aAQMG5Omnn86//vWvDB06NBMnTkxlZWW+9rWvZeONN87ee++d/ffff4muEdtss01WXnnlfPbZZ2ndunVxLqPFdeyxx2bffffNHXfcUeyZM3Xq1Kywwgrp1q1bevTokSOOOOIr752y+uqr53//93+X+vuUl5enX79+xV6AL730UsaPH59p06ZlpZVWKl4zDjnkkLRr126p19MYVlxxxdxwww259957c/fddxd7YK655prZZZddcuyxx9bZe3TPPffMgw8+mJtuuikvvfRSPvzww8ydOzft2rXLmmuumS222CKHHnpounfvnk8++STl5eWZN29ennjiiZx77rmLNbRZ27Zts8oqq2TLLbfM9773vWy77baLfbzt27fPT3/605x99tlJ5oey22+//QLf0eOOOy7rrrvuYu8fAEpJWWFhA2EDALBQ48aNy+67755k/jwLixrubGnabbfdMn78+JxyyilLNP9BQ7cHKDXHHntsBg0alCR58skna+2FA8uie++9t9j71+9uAFh+fbWPMAIAAAAAALBEhDoAAAAAAAAlQKgDAAAAAABQAho+Yy0AAE3i8MMPz9SpU7PVVls1yfYAAADAV0uoAwBQovr27duk2wMAAABfLcOvAQAAAAAAlICyQqFQaOoiljdDhw5NoVBIq1atmroUAAAAAACgiVVWVqasrGyRQ6Qbfq0JFAqFyNIAAAAAAIAk9c4MhDpNoKqHzmabbdbElQAAAAAAAE3tzTffrFc7c+oAAAAAAACUAKEOAAAAAABACRDqAAAAAAAAlAChDgAAAAAAQAkQ6gAAAAAAAJQAoQ4AAAAAAEAJEOoAAAAAAACUAKEOAAAAAABACRDqAAAAAAAAlAChDgAAAAAAQAkQ6gAAAAAAAJQAoQ4AAAAAAEAJEOoAAAAAAACUAKEOAAAAAABACRDqAAAAAAAAlICWTV1AY5o4cWJuv/32PP/88xk9enRmzJiR9u3bZ4MNNsjuu++eww8/PCuuuGKt28+bNy/33Xdf7r///rz99tuZMWNGunTpkq233jpHHnlktt1226/waAAAAAAAAP5PWaFQKDR1EY3hiSeeyNlnn51p06bV2mb11VfPlVdeme7duy+wbtq0afnRj36UQYMGLXTbsrKyHHfccTn77LMbXOubb76ZJNlss80avC8AAAAAAKC01Tc3aBY9dQYNGpQf//jHqaysTKtWrXL44Yfn29/+djp16pSPPvoo9913X55++umMHz8+P/jBD3Lvvfema9euxe0LhUJ+/OMfFwOdXr16pXfv3uncuXOGDx+ea6+9NuPHj8+NN96YlVdeOX369GmqQwUAAAAAAJZTJd9Tp1AoZP/998+oUaPSqlWrXH/99enRo8cC7a688sr8+c9/TpLsv//+ufTSS4vrHnzwwfzsZz9LkhxyyCG58MILa2w7ZcqUHH300Rk1alRWWGGFPPbYY1l11VWXuGY9dQAAAAAAgCr1zQ3Kv4pilqbXXnsto0aNSpIceeSRCw1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AAAAAAAAAwAKY1AEAAAAAAAAAALAAJnUAAAAAAAAAAAAswOFyuVxmFwEAAAAAAAAAAICCcaYOAAAAAAAAAACABTCpAwAAAAAAAAAAYAFM6gAAAAAAAAAAAFgAkzoAAAAAAAAAAAAWwKQOAAAAAAAAAACABTCpAwAAAAAAAAAAYAFM6gAAAAAAAAAAAFgAkzoAAAAAAAAAAAAWwKQOAAAAAAAAAACABfx/0HHlvrqFpzAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 2000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=hourly_grouped_num.index, y=hourly_grouped_num)\n",
    "plt.title('Распределение заказов по времени отправки')\n",
    "plt.xlabel('Время')\n",
    "plt.ylabel('Доля в % ')\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.8.16"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "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": true,
   "toc_window_display": false
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 },
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