anal.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import csv\n",
    "import datetime\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import StrMethodFormatter\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfc = pd.read_csv('./all_comments.csv')\n",
    "dfm = pd.read_csv('./markets.csv')\n",
    "\n",
    "# take users out \n",
    "dfcu = dfc[dfc['user_type'] == 'buyer']\n",
    "dfu = dfc[dfc['user_type'] == 'buyer'].drop_duplicates(subset=['user_name'])\n",
    "dfu = dfu.set_index(dfu['user_name'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_deals = int(dfu['deals_count'].sum())\n",
    "\n",
    "deals_min = dfm['deals_min'].sum()\n",
    "deals_max = dfm['deals_max'].sum()\n",
    "comments_count_total = dfm['summary_comments'].sum()\n",
    "\n",
    "reviews_share_min = comments_count_total/deals_min\n",
    "reviews_share_max = comments_count_total/deals_max"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfu1 = dfu[dfu['deals_count'] < dfu['deals_count'].quantile(0.95)]\n",
    "\n",
    "ax = dfu1.hist(column='deals_count', bins=400, grid=True, figsize=(12,8), color='#86bf91', zorder=2, rwidth=0.9)\n",
    "\n",
    "ax = ax[0]\n",
    "for x in ax:\n",
    "\n",
    "    # Despine\n",
    "    x.spines['right'].set_visible(False)\n",
    "    x.spines['top'].set_visible(False)\n",
    "    x.spines['left'].set_visible(False)\n",
    "\n",
    "    # Switch off ticks\n",
    "    x.tick_params(\n",
    "        axis=\"both\",\n",
    "        which=\"both\",\n",
    "        bottom=\"off\",\n",
    "        top=\"off\",\n",
    "        labelbottom=\"on\",\n",
    "        left=\"off\",\n",
    "        right=\"off\",\n",
    "        labelleft=\"on\"\n",
    "    )\n",
    "\n",
    "    # Draw horizontal axis lines\n",
    "    vals = x.get_yticks(minor=True)\n",
    "    for tick in vals:\n",
    "        x.axhline(y=tick, linestyle='dashed', alpha=0.9, color='#eeeeee', zorder=1)\n",
    "\n",
    "    # Remove title\n",
    "    x.set_title(\"\")\n",
    "\n",
    "    # Set x-axis label\n",
    "    x.set_xlabel(\"Покупок на площадке\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "    # Set y-axis label\n",
    "    x.set_ylabel(\"Юзеры\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "    # Format y-axis label\n",
    "    x.yaxis.set_major_formatter(StrMethodFormatter('{x:,g}'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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59J5DXwAAwJRM8kbUDyRJVX1y+DIAADBdk6xpf1/34522XW6ttXvtdWEAAMDAJGvaD4+57DztAAAwRZOE9odMrQoAAGCsSda0v36ahQAAAKNNsqb9j8Y0tdbaQ/eoHgAAYJtJlsccyW3r14fPzW5NOwAATNEkof0Pkvyb7uf3JHlOkk/teUUAAMBJdv3hSq21b0xyYZK3JTkvyY9lEPpfOp3SAACAZILQXlU/keSrk7w6yfVJzklyRQYhHgAAmJJJlsc8Paeuaa8k5+9lQQAAwMkmCe0vjTedAgDAzE1ynvbHTbEOAABgjEnO036HJI9Jck2Sm5M8JcktSZ7dWjsxnfIAAIBJlsccS/KIJP+Q5N1JHpDBcpl7JPnBvS8NAABIJjh7TJKHJHlHkhuTfEWSpyV5X5KLplAXAADQmSS03z7J65Mc7y4/O8nVSe66xzUBAABDJgnttyb5jCQfTPKubh37HTJYLgMAAEzJJKH9vyf5QGvt51prX9pt+/Ik/3vvywIAALZMcsrHnxmx7Yv3thwAAGC7Sc4ek6r6qgzekHqX3PapqK219iN7XRgAADAwyXnavz/Jc8c0C+0AADAlk6xpf0qSf07ynu7ya5OsJXnZXhcFAADcZpLQfjjJryd5TZK01v5t9/PUPw21ql5UVbdU1TuGtt2pqq6uqvd03+841HZpVV1fVe+uqodNuz4AAJimSUL7pzM4vePfJklVPTjJHZN8xxTq2u7FSS7ctu1pSf6wtXZekj/sLqeqzk9ycZL7dNd5flUtz6BGAACYiklC+weT3CPJOzN4E+ofJ3lwko9Noa6TtNbekMF54oddlOQl3c8vSfKtQ9tf0Vr7dGvt/UmuT/LAadcIAADTMsnZY34myb9OclUGn4T6DRnMvP/wFOrajbu11m5OktbazVW19cms5ya5Zmi/m7ptOzpx4tRVPsvLy1leXk5rLWtra1Nr39zczPr6+intKysrWVpamnr7xsZGNjY2TmlfXV1NVU2t/dChQ0mS9fX1bG5untRWVVldXZ1J+9raWlprJ7UvLS1lZWVlJu3G3v4ae6OM6uMkI/vmTI6zV8ffS9vH/JZR/ZHs/r4Ze573PO8Ze/th7G31xyQmmWl/Y5Lnt9bWWmsPy2BpzJ1aa7818a1OV43YNvKvR1Udraprq+raY8eOTbksAAA4OYN2X0dPd51JZtrfn+TZ6U7v2Fr7uzOsc698pKrO6WbZz0lyS7f9pgyW8Wy5e5IPjTpAa+2KJFdsXRx3Q1W14yuis21fWlqaa/vWK8B5tW+9+p1X+9ar/3m1T3NsGXvzHXtbxj0Gpxsbuz3OXh1/L1WNmj/J2P6Y9L4Ze573zrTd856xN84sx962DLork8y0V0bPYs/LVUke2/382CSvHtp+cVXdrqrumeS8JG+aQ30AALAnJvpE1CR3784ac5LujaJTU1UvT3IkyZ2r6qYkP5nkmUleVVVPSHJjkkd2tbyzql6V5F1J1pP8QGtt9CJKAABYAJOG9m/vvoa1MzjORFprjxrT9NAx+z8jyTOmVxEAAMzOJGH7xuyw7hsAAJiOXYf21trhKdYBAACMMfGylqr63CR3ydCbUltrb9vLogAAgNvsOrRX1X2TvDLJF29rmvqadgAAOMgmCdvPSfIl0yoEAAAYbZLztH9lktcneW4Gs+t3S/JXSS6eQl0AAEBnktB+KMk7knyqu/zPSd6a5Of3uigAAOA2kyyP+WiSOyR5dwZvQn1jBp82ujaFugAAgM4kM+1vTHI4yW9kMNt+vySfkeR/7X1ZAADAlknO0/7orZ+r6v5J/m2SDyd51RTqAoAkyWXHLz9l26VHLplDJQDzc9rQXlXvO80uP5PkXntTDgAAsN1uZtoPZ3C2mBrT3vasGgAA4BS7XR5TSW5N8uIM1rYDAAAzspvQ/uAk35/k25L8cJKHJXlBkv/RWvv7KdYGAGNZ6w4cJKc9e0xr7U9aa9+Z5B5JLs3gjDH/PclN3RtSAQCAKZrklI+b3dfW+vblqVQEAACc5LShvar+n6p6aZKbkvxskk8nuSTJ57XW3jLl+gAA4MDbzZr2/53B7PonMljL/vpu+5GqwQllWmtXTaU6AABg9x+ulOSOSZ7SfQ1rEx4HAACYwG7C9o1xLnYAAJib04b21trhGdQBAACMMcnZYwAAgDkQ2gEAoOeEdgAA6DmhHQAAek5oBwCAnhPaAQCg54R2AADoOaEdAAB6TmgHAICeE9oBAKDnhHYAAOi5lXkXANBXlx2/fOT2S49cMuNKADjozLQDAEDPCe0AANBzQjsAAPSc0A4AAD0ntAMAQM85ewwA+8qos/444w+w6My0AwBAz5lpB5jQuPO3A8C0mGkHAICeE9oBAKDnFnp5TFV9UZJXDm36giQ/keQOSb43yUe77T/aWnvNjMsDAIA9sdChvbX27iQXJElVLSf5myS/meTxSX6xtfbzcywPAAD2xEKH9m0emuS9rbUPVNXEVz5x4sQp25aXl7O8vJzWWtbW1qbWvrm5mfX19VPaV1ZWsrS0NPX2jY2NbGxsnNK+urqaqppa+6FDh5Ik6+vr2dzcPKmtqrK6ujqT9rW1tbTWTmpfWlrKysrKTNqNvf6Ovb0yqo+TjOybMznOXh1/L20f81tG9Ucy+X3b3m+n2751nEUZe573PO/tdbux16+xt9Ufk9hPa9ovTvLyoctPrqq3VdWLquqOo65QVUer6tqquvbYsWOzqRIAgANtOIN2X0dPd519MdNeVYeSfEuSS7tNL0jy00la9/1ZSb5n+/Vaa1ckuWLr4g7H3/EV0dm2Ly0tzbV96xXgvNq3Xv3Oq/10s6rTbp/m2DL2zm7s7ZVxj8GkM/rjjrNXx99L4/7jOa4/Jr1vS0uj55zGbd9+nL6PPc97nvem1W7s9WPsbcugu7JfZtofnuQvW2sfSZLW2kdaaxuttc0kL0zywLlWBwAAZ2G/hPZHZWhpTFWdM9T2iCTvmHlFAACwRxZ+eUxVfWaSb0jyfUObf66qLshgycsN29oAAGChLHxob639Y5LP2bbtMXMqB1hAlx2/fN4lAMCO9svyGAAA2LeEdgAA6DmhHQAAek5oBwCAnhPaAQCg54R2AADoOaEdAAB6TmgHAICeE9oBAKDnhHYAAOg5oR0AAHpOaAcAgJ4T2gEAoOeEdgAA6DmhHQAAem5l3gUAwCxcdvzyifa/9MglU6oEYHJm2gEAoOeEdgAA6DmhHQAAek5oBwCAnhPaAQCg54R2AADoOaEdAAB6TmgHAICeE9oBAKDnhHYAAOg5oR0AAHpOaAcAgJ4T2gEAoOeEdgAA6DmhHQAAek5oBwCAnhPaAQCg54R2AADoOaEdAAB6TmgHAICeW5l3AQCzctnxy+ddAgCcETPtAADQc2baAWCEcf+ZufTIJTOuBMBMOwAA9J7QDgAAPSe0AwBAzwntAADQcwv/RtSquiHJ3yfZSLLeWntAVd0pySuTHE5yQ5LvaK19Yl41AgDA2Vj40N55SGvtY0OXn5bkD1trz6yqp3WXnzqf0gA4CJxtBpim/RLat7soyZHu55ckOZ7ThPYTJ06csm15eTnLy8tprWVtbW1q7Zubm1lfXz+lfWVlJUtLS1Nv39jYyMbGxintq6urqaqptR86dChJsr6+ns3NzZPaqiqrq6szaV9bW0tr7aT2paWlrKyszKTd2Jv92Ju1UX2cZGTfnMlx9ur4e2n7mN8yrj8mvW/bf6dPt33ccc7UJGNr+LY973ne8zfX2Etu649J7Ic17S3J71fVm6vqaLftbq21m5Ok+37XUVesqqNVdW1VXXvs2LEZlQsAwEE2nEG7r6Onu85+mGl/UGvtQ1V11yRXV9Vf7/aKrbUrklyxdXHcflW14yuis21fWlqaa/vWK8B5tW+9+p1X+9ar/3m1T3NsGXs7t8/KuMfgdGNjt8fZq+PvpaoauX1cf0x635aWRs85jdt+JrNaO5lkbI26bc97nvfm1W7s9WPsbcugu7Lwob219qHu+y1V9ZtJHpjkI1V1Tmvt5qo6J8ktcy0SgH1j3Np1gGla6OUxVfUvq+qztn5O8o1J3pHkqiSP7XZ7bJJXz6dCAAA4e4s+0363JL/Z/Rt2JcnLWmuvraq/SPKqqnpCkhuTPHKONQIAwFlZ6NDeWntfki8bsf3jSR46+4oAAGDvLfTyGAAAOAiEdgAA6DmhHQAAek5oBwCAnhPaAQCg54R2AADoOaEdAAB6TmgHAICeE9oBAKDnFvoTUQFGuez45fMuAQD2lJl2AADoOaEdAAB6TmgHAICeE9oBAKDnhHYAAOg5oR0AAHpOaAcAgJ4T2gEAoOeEdgAA6DmfiAosrFGffHrpkUvmUAkATJeZdgAA6DmhHQAAek5oBwCAnrOmHQCmzPsvgLNlph0AAHpOaAcAgJ4T2gEAoOeEdgAA6DmhHQAAek5oBwCAnhPaAQCg54R2AADoOR+uBAALwoc0wcFlph0AAHrOTDsA9IwZdWA7M+0AANBzQjsAAPSc0A4AAD0ntAMAQM8J7QAA0HPOHgP0njNpAHDQmWkHAICeW+iZ9qq6R5KXJvncJJtJrmitPaeqnp7ke5N8tNv1R1trr5lPlQAwmv8iAbu10KE9yXqSH2mt/WVVfVaSN1fV1V3bL7bWfn6OtQEAwJ5Y6NDeWrs5yc3dz39fVdclOXe+VQEAwN5a6NA+rKoOJ7l/kj9P8qAkT66q705ybQaz8Z/Y6fonTpw4Zdvy8nKWl5fTWsva2trU2jc3N7O+vn5K+8rKSpaWlqbevrGxkY2NjVPaV1dXU1VTaz906FCSZH19PZubmye1VVVWV1dn0r62tpbW2kntS0tLWVlZmUm7sTf52NnJqMdz3sbVNKpvzuQ4e3X8vbR9zG8Z15+T3rftv9On2z7PcTHpfRtnXH9uHcfz3v5+3vM3d3+Nva3+mMS+eCNqVd0+yZVJntJa+2SSFyS5V5ILMpiJf9aY6x2tqmur6tpjx47NrF4AAA6u4QzafR093XUWfqa9qlYzCOy/1lr7jSRprX1kqP2FSX5n1HVba1ckuWLr4g63seMrorNtX1pammv71ivAebVvvfqdV/vWq/95tU9zbO33sTfKmcxeTNu4mk43NnZ7nL06/l6qqpHbx/XnpPdtaWn0nNO47fMcF5Pet3HG9eeo43je27/Pe/7m7o+xty2D7spCz7TX4K/CryS5rrX2C0Pbzxna7RFJ3jHr2gAAYK8s+kz7g5I8Jsnbq+qt3bYfTfKoqrogg9nzG5J833zKAwCAs7fQob219idJRv0P1jnZAQDYNxZ6eQwAABwEQjsAAPSc0A4AAD0ntAMAQM8J7QAA0HNCOwAA9JzQDgAAPbfQ52kH9pfLjl9+yrZLj1wyh0oAoF/MtAMAQM8J7QAA0HOWxwDAghu3tGzU9p1Yjgb9ZaYdAAB6TmgHAICeE9oBAKDnhHYAAOg5oR0AAHpOaAcAgJ4T2gEAoOecpx2YuXHnlAYARjPTDgAAPWemHQBIMvq/YIn/hEEfmGkHAICeE9oBAKDnhHYAAOg5a9oBgB3t5Vp3Z4+CM2OmHQAAes5MOzA1ZtQAYG+YaQcAgJ4z0w6cFed1hoNr3O//OJ4X4MyZaQcAgJ4T2gEAoOeEdgAA6DmhHQAAek5oBwCAnnP2GACgt3zeAwyYaQcAgJ4z0w7syqTnYwaYpkln4H2mBIvOTDsAAPSc0A4AAD1neQwAMHd79YbTaR5nJ/OslYPBTDsAAPScmXbY57yBFGCx9O2/DvSDmXYAAOi5fT3TXlUXJnlOkuUkx1prz5xzSSN5Jby/jOvPvTg9mXEBsLdm8d/I/fp87jSas7VvZ9qrajnJ85I8PMn5SR5VVefPtyoAAJjcfp5pf2CS61tr70uSqnpFkouSvGuuVbGjec1GzOIsAZPc9pnMwO/XmRwABqb9/D/P90BNex3/fvgbuZ9D+7lJPjh0+aYkXzVu5xMnTpyybXl5OcvLy2mtZW1tbWrt4+pZWVnJ0tJSNjc3s76+fso+e9W+sbGRjY2NU9pXV1dTVVNrP3ToUJJkfX09m5ubIx+Hce1VldXV1T1pH9U3p7O+vp6VlZX/e/3W2o77jxpfOxn1eHik26wAAAzpSURBVO10nHHbT1fXPEx6HyZ97CbdfxbG1TTp2Jv0MTqTsb1Xxo29vRrb454zxm2f57jYq7E9rj/36vjztB+eFzY3N3f8m7vbmsb9joz7nZr0MTrd38S9sP22t//N3X5flpZGL/zYOs7S0tKOf3OH20cZ1x9bx59V3hseG1sZaBLVxz/qe6GqHpnkYa21J3aXH5Pkga21Hxza52iSo93Ff5Hkn2deaHLnJB+bw+3SD/r/4NL3B5v+P7j0/cG21f/bc+cVrbUrdrrifp5pvynJPYYu3z3Jh4Z36B6cHR+gaauqa1trD5hnDcyP/j+49P3Bpv8PLn1/sJ1N/+/bN6Im+Ysk51XVPavqUJKLk1w155oAAGBi+3amvbW2XlVPTvK6DE75+KLW2jvnXBYAAExs34b2JGmtvSbJa+Zdx2nMdXkOc6f/Dy59f7Dp/4NL3x9sZ9z/+/aNqAAAsF/s5zXtAACwLwjtM1JVF1bVu6vq+qp62oj2qqrLu/a3VdWXz6NOpmMX/f+dXb+/rar+tKq+bB51svdO1/dD+31lVW1U1b+fZX1M1276v6qOVNVbq+qdVfX6WdfIdOzief9fVdVvV9VfdX3/+HnUyd6rqhdV1S1V9Y4x7WeU+YT2Gaiq5STPS/LwJOcneVRVnb9tt4cnOa/7OprkBTMtkqnZZf+/P8nXtdbul+SnY83jvrDLvt/a72czeOM8+8Ru+r+q7pDk+Um+pbV2nySPnHmh7Lld/u7/QJJ3tda+LMmRJM/qznbH4ntxkgt3aD+jzCe0z8YDk1zfWntfa+1EklckuWjbPhcleWkbuCbJHarqnFkXylSctv9ba3/aWvtEd/GaDD5XgMW3m9/9JPnBJFcmuWWWxTF1u+n/Ryf5jdbajUnSWjMG9ofd9H1L8llVVUlun+TWJKf/KFV6r7X2hgz6c5wzynxC+2ycm+SDQ5dv6rZNug+LadK+fUKS35tqRczKafu+qs5N8ogkvzTDupiN3fzuf2GSO1bV8ap6c1V998yqY5p20/fPTfIlGXzw49uT/FBrbXM25TFnZ5T59vUpH3ukRmzbftqe3ezDYtp131bVQzII7V8z1YqYld30/bOTPLW1tjGYcGMf2U3/ryT5iiQPTfIZSf6sqq5prf2faRfHVO2m7x+W5K1Jvj7JvZJcXVVvbK19ctrFMXdnlPmE9tm4Kck9hi7fPYNX1pPuw2LaVd9W1f2SHEvy8Nbax2dUG9O1m75/QJJXdIH9zkm+qarWW2u/NZsSmaLdPvd/rLX2qSSfqqo3JPmyJEL7YttN3z8+yTPb4Nzb11fV+5N8cZI3zaZE5uiMMp/lMbPxF0nOq6p7dm8yuTjJVdv2uSrJd3fvKP7qJH/XWrt51oUyFaft/6r6/CS/keQxZtj2ldP2fWvtnq21w621w0l+Pcl/FNj3jd089786yddW1UpVfWaSr0py3YzrZO/tpu9vzOA/LKmquyX5oiTvm2mVzMsZZT4z7TPQWluvqidncGaI5SQvaq29s6qe1LX/Ugaf3PpNSa5P8o8ZvAJnH9hl//9Eks9J8vxuxnW9tfaAedXM3thl37NP7ab/W2vXVdVrk7wtyWaSY621kaeJY3Hs8nf/p5O8uKrensFyiae21j42t6LZM1X18gzOCHTnqropyU8mWU3OLvP5RFQAAOg5y2MAAKDnhHYAAOg5oR0AAHpOaAcAgJ4T2gEAoOeEdgAA6DmhHQAAek5oBwCAnhPaAQCg54R2AADoOaEdAAB6TmgHAICeE9oBAKDnhHYAAOg5oR0AAHpOaAcAgJ4T2gEAoOeEdgAA6DmhHQAAek5oBwCAnhPaAQCg54R2AADoOaEd2Leq6sVV1UZ8HZ93bQAwCaEdOAjemuQ5Sd4w70IA4EwI7cB+tvUc90ettack+c1RO1XVg6vqDVX1t1X1oar6tar6vG373DBuxr6qlqrqeVV1S1VtDrU/fcztPW7MfwBuGNrnflX12qr6WFV9tKp+u6q+aEQ9R6rqc6rqbd1tH62q7+zaXje0/8Xdtt/f4f60qnpc175aVZdW1V9X1aeq6rqq+uGqWtp2H7Yeg+/rbv+vqupzxtzvL6mq3+we43+qqrdW1b8es+9dqupYVd1YVZ+sqmuq6sKu7eljam9dXT9WVR+uqhNVdWtVXVlVd+quu/Xfl1P6Zvgx7S4fHzruiap6b1V9f9d2eKtth/7demyODB3nid22LxwaK0/fdr9e3F1+4fZxARxcQjuwn1X3fX3sDlX3S/IHSb4myWuTfCDJo5O8rqpWRxzr15Ncve0w35jkPya5XZIXJLlul/X9TQb/AbhyW03nJHl9kocluSbJW5J8c5LjVXXHbce4U5I/TPKlSX6gtXZFd7xPJHlod6wk+Zbu+8u2Xf/Kroa/2bb9GUl+JslnJXlFkjsn+YUkT91+J7og+oIk70zy0Nbax0fs87lJ3pjkW5N8OMn/zOAx3X5/0r0wuCrJE5J8LMmrk3xFkt+tqgd1j8lzkvzq0NWe0329K4O/bb+b5IokNyX5tiSP2X47E7g6yUuSHE5yeVUdOotjfX/3/Um5bUydoqrOT/L4s7gdYJ9ZmXcBAFO0Fbr/cYd9ntTt9+LW2uO7oH5TkvsmeUiS3+/2W+6+PzvJeUm+YcSx3p7kKUlemORLdlHf9a21p3Qzu98+tP0xSe6Q5Hhr7ZuTpKrekuSCJI/MIIxuOZZB8P3h1toLkqS19s9V9WtJnpzkUVV1eZKHJ/nnJL+xrYbnttaOV9UFSc7tbqsyeBGSJI9urb2+qi5K8ltJfjDJZUPXvyDJg5Ncn+TrW2sfG3NfvyvJ52SwVOkBrbXN7rZG/R16QJKvTvIPSb62tfapqvpYBo/tD7TWHp3ktVV1OF2w7f6TsuVNVfXUJPfIIMD/Q5I/33YbF1bVZye5Ocn/aq3dMKbu7d7cWjsxeIgGqurZST6VwYurkf/NGfLlVfV1SR53mv1+LreNOQChHdjXbt99v3WHfQ53369LktbaWlW9L8ldkwwv3fiX3fdPjTjG1Ul+O8m/S3LiTIsdV1PnrzMIyNuXk2zNVH/+tu3HMgjt35VBUL5Dkl9vrX1yF7d/l9x2f7dq+Ovu+znbZpr/1dB1PmOHY96z+/6mrcCeJK21Uf8FOdx9/2Brbevx3rr9kctpRnhMkvt0P785yYe2tX9V95UkP15V98l4wy/QPrztPzBJ8kNDP/9ikreNOc6HMvi7+7IM+u0tSe4/Yr8HJbl3Bi+E7r1DXcABYnkMsC91SyzO7y5ev8OuN3Tfv7i73mqSL+i2faDbdl4GoTdJPrj9AK21jSS/01388+x+ecyuaupsrWf/wLZ9L8tgSchTqurhQzX9VQZh9f5JntZt3r40ZpyP5rYXJ1s1bN3+za214RcmH+qOf4ckL6uqcbPD7+++f+XWuvhk7Ez7Dd33e1TVZ267/e33/xRVVa21+2bwIuJpGSytecq23X4qyb/IYLnTZ2fw34JxHp/BC8A/TXJRkguHG1tr1d1GMljGNM5akl9J8nndscaF+3sn+ack/2WHYwEHjNAO7DtVde8MQvTW7O63d0sYHtFdvnd3ORksNVlP8tiqenkGa8nvmsH67ONV9ZUZBKwked2Y9dp3SPJfM1iG8x1J3nSWd+F/Jvm7JA+pqquq6rUZhO+PZBAyh/1+kouTfDrJS4bWsCeD2fZkMFP8d0les5sbb621DNaoJ4MgfmzoWM/dtvt7Wms/m+TXMpghfvoO9+nj3f14U1X9clVdm8EypO2uzeDFz+2TvLGqXprBspyW5Pm7uAvXdX35i0m+t9v20W37XJDBEpUv7S7fvMPxHp3Bev6tWv9huLEGb97dWjO/03GS5JeSvDLJT59mv2dnxAtE4OAS2oH96O4ZrOHe8oQMljBszaae211Oa+2tGbyR9M+SfFMGQf8VSS7sZpTPySAsviiD8DbKT2WwPOS/ttZuPNviW2sfym3r6R+UwRrv303ykNbaKUt9WmtvT/Kfuhr+x9BM9sty23r+K1trn56gjB9L8v911390BkuM/nOSnx2z//cneW+SH906+8q2Gj+c5GszWBd/bpLvzmCpyCdG7LuZwRtnfzWDF1CPyGApybe01v5kF7W/J4M38T4hg9n0F2QQ4Idd1G3/7Az67Y93ON43JHliBmH9Z0bs+6tJjmbw4u7JOxXWWruxtXZxa+21O+z2sSTP3Ok4wMFTgwkVgP2jC41/nOSnWmtPH9F+PMnXdcsa9rWq+r0MlnM8tLX2R/OuB4Az442oAPtQVX11BmH9IRm8iXOnmWQAek5oB/aj65P8cAbn8x7luRks09jPLkzyE0neneS7mn+rAiw0y2MAAKDnvBEVAAB6TmgHAICeE9oBAKDnhHYAAOg5oR0AAHpOaAcAgJ77/wFU1Yy1ca4EegAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = dfm.hist(column='commented_share_max', bins=100, grid=False, figsize=(12,8), color='#86bf91', zorder=2, rwidth=0.9)\n",
    "\n",
    "ax = ax[0]\n",
    "for x in ax:\n",
    "\n",
    "    # Despine\n",
    "    x.spines['right'].set_visible(False)\n",
    "    x.spines['top'].set_visible(False)\n",
    "    x.spines['left'].set_visible(False)\n",
    "\n",
    "    # Switch off ticks\n",
    "    x.tick_params(axis=\"both\", which=\"both\", bottom=\"off\", top=\"off\", labelbottom=\"on\", left=\"off\", right=\"off\", labelleft=\"on\")\n",
    "\n",
    "    # Draw horizontal axis lines\n",
    "    vals = x.get_yticks()\n",
    "    for tick in vals:\n",
    "        x.axhline(y=tick, linestyle='dashed', alpha=0.4, color='#eeeeee', zorder=1)\n",
    "\n",
    "    # Remove title\n",
    "    x.set_title(\"\")\n",
    "\n",
    "    # Set x-axis label\n",
    "    x.set_xlabel(\"Доля покупок с отзывыми\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "    # Set y-axis label\n",
    "    x.set_ylabel(\"Магазины\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "    # Format y-axis label\n",
    "    x.yaxis.set_major_formatter(StrMethodFormatter('{x:,g}'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [],
   "source": [
    "low_border = (500,\n",
    " 750,\n",
    " 1000,\n",
    " 1500,\n",
    " 2000,\n",
    " 2500,\n",
    " 3000,\n",
    " 3500,\n",
    " 4000,\n",
    " 4500,\n",
    " 5000,\n",
    " 6000,\n",
    " 7000,\n",
    " 8000,\n",
    " 9000,\n",
    " 10000,\n",
    " 15000,\n",
    " 20000,\n",
    " 25000,\n",
    " 30000,\n",
    " 40000,\n",
    " 50000,\n",
    " 75000,\n",
    " 100000,\n",
    " 150000,\n",
    " 200000,\n",
    " 250000,\n",
    " 300000)\n",
    "top_border = []\n",
    "for i, num in enumerate(low_border):\n",
    "    if i < 1:\n",
    "        continue\n",
    "    top_border.append(num-1)\n",
    "top_border.append(350000-1)\n",
    "top_border = tuple(top_border)\n",
    "borders = dict(zip(low_border, top_border))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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NVWuoaz3AGV/POZ1Lyb2IiIiIyAihcIi3j73LgqL5zCusTPjrnRe9WHf78V3ndB4l9yIiIiIiI+xtqafH38eWmvNm5PWKcgpZUb6UHSf34A8Fpn0eJfciIiIiIsNYa3nz2DtU5JWxpGThjL3uBdWb8AUH2HNq/7TPoeReRERERGSYxo7DtPd3ctGCzRgz7mKwcTe/cC5VBZW83bwDa+20zqHkXkRERERkmDeOvUNhVgGrypfP6OsaY7igeiOd3i4OdjZN6xxK7kVEREREopq7T9LcfYILazbhdDhn/PVXli+jwJM37UWtlNyLiIiIiES9cXQ72a5sNlStScrrOx1Ozpu/gabTx2jtbZ/y8UruRURERESA9r5ODnQc4rz56/E43UmLY+O8tbgcrmmN3iu5FxEREREB3jz2Di6Hi/Pnr09qHDnubNbNXcXelnr6/P1TOlbJvYiIiIjMej0DvexpqWP93NXkenKTHQ4XVG8kZEO8e2L3lI5Tci8iIiIis95g+ckLazYlOxQASnOLWVqyiHeO7yYYDsZ8nJJ7EREREZnVfIEB3j2xm5UVyynOmZPscIZcUL2RvkA/+1oaYj5Gyb2IiIiIzEr9AS8HO5p49sDL+EMBttRsTnZIZ1lUXEN5XumUFrVyJTgmEREREZGkC4SCtPS2ceLMKU72tHDiTAtdvu6h9g1zVzO3oCKJEY42uKjV1voXONrVzMLimkmPUXIvIiIiIhklbMN09J3mRM8pTp5p4URPC219HYRtGICCrHzmFVSycd4a5hVUMreggixXVpKjHtvqihW8dOjPvNW8Q8m9iIiIiMweO07sYW9LPSd7WgmEAwBkOT1UFVaypWYzVYWVVBVUUpCVn+RIY+d2utg8bz1/PvIWnf1dlOQWTbi/knsRERERSXu9A338Z8OLlOYWs75qFVUFlcwrnEtJThHGmGSHd042z1vH60e3se34Dq5ZfvmE+yq5FxEREZG0V99+EIBb1lxPWV5JkqOJr/ysPFZX1LLr5H4uW3Qx2e7xpxCpWo6IiIiIpL36tkbKcksyLrEfdGH1JgLhADtP7p1wPyX3IiIiIpLW+vz9HO06zoryZckOJWEqC8pZUDSfbcd3TrifknsRERERSWsN7YewWFZmcHIPkUWtzgz0TLiPknsRERERSWt1bQcoySmiPK802aEk1LLSxZTmFk+4j5J7EREREUlb/QEvR043s7J8WdpXxZmMwzj4/Pm3T7zPDMUiIiIiIhJ3B6JTcjJ5vv1wLsfExS6V3IuIiIhI2qpra6Qou5DK/PJkh5ISlNyLiIiISFryBnw0nT7GyvLlGT8lJ1ZK7kVEREQkLTV2HCZsw7NmSk4stEJtnPj9/lHbnE4nTqcTay2BQCBh7eFwmGAwOKrd5XLhcDgS3h4KhQiFQqPa3W43xpiEtXs8HgCCwSDhcPisNmMMbrd7RtoDgQDW2rPaHQ4HLpdrRtrV99T3hlPfU9+biXb1PfW94ZLZ9/a1NFCYlU9VQcWY7ZCZfW/w5zEWjdyLiIiISNoZCPo50nWM5aVLNSVnGDPy24lMmz5IERERkRmyt6WeJ/c/y2c23Ub1nKpkhzPTxv02o5F7EREREUk7dW2N5HvymF84N9mhpBQl9yIiIiKSVvxBP4c6m1gxCxaumiol9yIiIiKSVg52NhEMh1ipKjmjKLkXERERkbRS19ZInjt3Ns61n5SSexEREREZV0PbQV49/Ab+4OgykMkQCAU42NFEbflSHEap7Eiqcy8iIgnjDwVwGgdOhzPZoYjINFhr+WPjn+gZ6GXXqf18qPZylpUuTmpMhzqPEAgHNSVnHPq6IyIiCfPrdx/lxYN/TnYYIjJNR7qa6RnoZUvNeXicbh7Z/Qf+Y+9Wegf6khZTXVsjOe5sFsyZn7QYUplG7kVEJGE6vadVyUIkje05VUeW08P7F13EZYu38Maxd/hz01sc7jzKFUsvYWPV2hn9Nx4MBWnsOMzqilocDo1Rj0WfioiIJEQoHMIfCtDR3zlqOXcRSX3+UIC6tkZWVizH7XThdDi5ZOEF/M0Fn2JuQQXPNLzEv7/7e9r6OmYspsOnj+IPBVihKTnjUnIvIiIJ4Q34gEiC0OtP3p/wRWR6GtoOEggHWFe58qztJblF3L7ho1y/8mo6+k9z/7bf8qfDrxMMBRMeU11bI9muLBYWVSf8tdKVpuWIiEhCeIO+ocftfZ0UZOUnMRoRmardLfspyi6kes68UW3GGNbPXcWykoW8cPA1/nLkbfa3HuDDtVewsLgmIfEEw0EOtB9iRfkyXaQ/AY3ci4hIQgyO3AO093cmMRIRmaozvh6aTh9jTeXKCefU53pyuWHVNfzV+pux1vKbnf/BU3XP0R/wxj2mptPNDIT8mpIzCSX3IiKSEMOT+47+00mMRESmam9rPQBrR0zJGc/ikgX8zQWf4uIF57O3pZ6fvfUr9pyqi+v1NvVtjWQ5PSwq1pSciSi5FxGRhPBGR+4KsvJpn8EL7kTk3Fhr2XOqjvmFVZTkFsV8nNvp4vIl7+Nz5/0VxTlF/KHujzy06wkG4rD4VSgcoqH9IMvLluByaFb5RJTci4hIQgzOua+ZM08j9yJp5FRvG+39naybG9uo/UgV+WXcsek2rl72AZpOH+OxvU8TDJ/bxbZHuprxBQe0cFUMlNyLiEhC+AIDOI2DqoIK+gNe+v3xn4MrIvG359R+nMbByvLl0z6HMYbzqzdw3coP0nT6GE/tf46wDU/7fPVtjXicbhYXL5j2OWYLJfciIpIQ3oCXHHcOpbklAHToolqRlBcKh9jbWs/ysiXkuLPP+Xzr567iyqXvZ3/bAf544E/TmoMfDoepbz/IstLFuJyakjMZJfciIpIQ3qCPHHc2ZXmR5L5dU3NEUt6hziN4A76YL6SNxUU1m9lScx7vntjNa01vTvn4o93H8QZ8mpITI339ERGRhPAGfOS4sinMKsDtcNHep5F7kVS3p6WOXHcOS0oWxvW8ly95H/0BL68deYscdw7nV2+I+di6tkbcDlfcY8pUSu5FRCQhvAEfpbnFGGMozS3RtByRFOcN+DjQfohN89bHfZEoYwwfrr0Sb8DHc41/IsedzZrKFZMeF7ZhGtoOsrR0EW6nO64xZSpNyxERkYTwBnxDc3ZL84qV3IukuLq2A4RseNpVcibjcDi4afW11MyZx1N1z3Go88ikxzR3n6Qv0K8pOVOg5F5EROLOWos36CPbFUnuy3JLODPQG5d61yKSGLtP7acst4TK/PKEvYbb6eLWdTdQllvCY3ue5viZUxPuX9fWiMvhZGnJooTFlGmU3IuISNz5Q37CNjw0cl82VDFHF9WKpKLO/i6OnznFurmrMMYk9LWyXVl8Yv1N5HnyeHjXk+Mucmetpb6tkSUli/C4PAmNKZMouRcRkbjzBgYAhk3LUTlMkVS2p6UOIKZ58PGQn5XHX224GafDwe92PUG3r2fUPsfPnKLX36cpOVOk5F5EROJucHXaweS+OHsODuNQxRyRFGStZU9LHYuKayjIyp+x1y3OmcMn1t+EP+jndzsfH7XQXV3bAZzGwbLSRTMWUyZQci8iInHnDUT+k85x5QCRC+lKcoo0ci+Sgo51n6Dbd4Z1latm/LUr88u5bd0NnBk4w8O7nxy6LmdwSs7ikoVkubJmPK50puReRETizhs4e+QeoCyvRAtZiaSgPaf243a4qS1fmpTXrymaz82rP8ypnlYe2/s0wXCQkz0tnBno1ZScaVByLyIicTdWcl+aW0KXt5tgKJissERkhEAoyP62A6wsX4YniXXkl5ct4boVV9F0+hh/2P9H9rcewGEcLCtdnLSY0pUWsRIRkbgbmnPvGjZyn1uCxdLp7aIivyxZoYnIMAfaD+EPBViboNr2U7G+ajXegI8XD72GwbC4ZMFZAwQSG43ci4hI3HkDPrKcHhyO9/6bKc0rBlQxRySV7G7ZT2FWPguLqpMdCgAXLdjMRTWbsVhWlS9PdjhpSSP3IiISd8NXpx1UkhNJ7lUxRyQ19A70cbjzKBcvOC/hte2n4ooll7CyfDlVBRXJDiUtKbkXEZG48wV9ZI9I7t1OF0XZc7SQlUiK2Ndaj8WytjL5U3KGM8Ywr7Ay2WGkLU3LERGRuPMGfGfNtx9UlldMu6bliKSE3afqqCqoHFpkTjKDknsREYk7b8BLjjtn1PbS3BI6+08TDoeTEJWIDGrpbaO1r511KXAhrcRXWiT3xpj7jTGtxpg9w7bdbYw5bozZEb1dN86xdxpjDkRvdw7bvtgY82Z0+0PGGE90uzHG/NAY02iM2WWM2Zz4dygiklnGmnMPkYo5IRumy3cmCVGJyKA9p+pwGAerymuTHYrEWVok98ADwLVjbP+BtXZj9LZ1ZKMxpgT4DnARcCHwHWNMcbT5+9HjlwOngb+Obv8wsDx6uwv4cTzfiIhIpguHwwyE/GMm94N//lfFHJHkCYfD7G2pZ1npInI9o//CJuktLS6otda+YoxZNI1DPwQ8Z63tBDDGPAdca4z5HXAl8Mnofg8CdxNJ5G8CfmmttcAbxpgiY0yVtfbkRC/k9/tHbXM6nTidTqy1BAKBhLWHw2GCwdGLwrhcLhwOR8LbQ6EQoVBoVLvb7cYYk7B2j8cDQDAYHPUnfmMMbrd7RtoDgQCR7vIeh8OBy+WakXb1PfW94VKh7/lCAwB4jHvUPsVZhQC09XWwsHB06T31PfW9WNr1e+/c+lZj+2H6Av2sLF0+9Fmq76VX3xv8eYwlXUbux/OV6NSZ+4eNyA83Hzg27HlzdFsp0GWtDY7YPtExoxhj7jLGbDPGbLvvvvvO5X2IiGSMwdVps11Zo9qyXFkUePJUMUckifa2NZDtymJx8YJkhyLTNDwHjd7uGmxLi5H7cfwY+C5go/f/E/j8iH3GKtpqJ9g+0TGjN1r7M+BnE+0DkW+cE33DOtd2h8OR1PbBb5TJah/8Np2s9sHRhGS1J7Jvqe+p701kvJ/NYHJfkJM/5j6leSV09J9W31Pfm3a7fu9Nv+8EbJCDnYdZP3c1udmjp+So76VH3xuRg56937hnSHHW2hZrbchaGwZ+TmRO/UjNQM2w59XACaAdKDLGuEZsn+gYERGJgTfoBRizFCZEKuZ09HeO+tO3iCRefVsjwXCItXNXJTsUSZC0Te6NMVXDnn4U2BPdPt8Y80J0+7PANcaY4ui0nWuAZ6Pz6V8Cbo3udyfwRPTxk8Ad0ao5W4Duyebbi4jIe3yByJz7sS6ohUjFHH8oQM9A70yGJSLA7lP7KckpYl6BFonKVGkxLccY81vgcqDMGNNMpALO5caYjUSmwzQBX4juXgUEAay1ncaY7wJvR9vuGby4FvgG8DtjzPeAd4FfRLdvBa4DGoF+4HOJe2ciIplncFrOuMl9XuQSqfb+TgqzC2YsLpHZrsvbzbHuE3xg8cUYM9YsZMkEaZHcW2tvH2PzL8bYBrAF+Jdhx94P3D/GOQ8xxlSe6Kj+l6cXqYiIeINeHMaBxzn23NHS3Eg5zPa+TpaULJzJ0ERmtT0tdQCsqdTCVZksLZL7qbDW/ijZMYiIzGbegI8cV/a4I4O57hxyXNmqmCMyQ6y1NLQfYvvxXSwsqmaO/mKW0TIuuRcRkeQab3XaQcaYaMUcLWQlkmhHu47z0qE/c+LMKUpzi7ly6fuTHZIkmJJ7ERGJq8mSe4Cy3GLq2w7OUEQis09bbwcvH/4zjR1NFHjyuG7FVayrXIXDkba1VCRGSu5FRCSuvEEfRdlzJtynNLcEb3Av/f5+cj25MxSZSObr9vXwatMb7D61nyynhyuWXMJ58zfgdirlmy30kxYRkbjyBnxUTVJmrywvelFt/2kWKLkXOWfegI/Xj25jW/NOAC6q2czFC86f9K9oknmU3IuISNxYa2OaljO8Ys6CovkzEZpIRgqEgmw7voM3jm7HFxxg3dxVXLpoiy6ancWU3IuISNwEwkFCNjRpcl+YlY/H6dZFtSLTFA6H2d2yn1cPv0GPv49lpYv4wOL3UZFfluzQJMmU3IuISNwMLWDlmji5N8ZQkltMu5J7kSk70H6Ilw/9hfb+TuYVzuXG1dfqL2AyRMm9iIjEjTfgBSDHnY8w5hMAACAASURBVDPpvmW5JRw5fSzRIYlklLeOvcsLB1+lJKeIW9ZcR23ZUq02K2dRci8iInEzNHIfw0V8Zbkl7GmpYyA4QJYrK9GhiaS9PS11vHDwVVaULeWm1dfidDiTHZKkIBU7FRGRuPEGY0/uS/OKAbRSrUgMDnY08XTd8ywoms+Nqz6kxF7GpeReRETiJtY59wBluaVApGKOiIzvePdJ/mPvVsrzSrl17UdwqWa9TEDJvYiIxM1UpuUUZRfiNA6N3ItMoL2vg4d3/4E8Tx6fWH+TprDJpJTci4hI3PiCPjxOd0xTBhwOR7RiTscMRCaSfs74evjdridwOhz81YabydOCbxIDJfciIhI33oAvpik5g8pyS2jv08i9yEj9AS+/2/U4/qCfT6y/ieKcOckOSdKEknsREYmbWFanHa40t5hu3xkCoWACoxJJL/5QgEd2PUmX9wy3rruByvzyZIckaUTJvYiIxI034CV7Ksl9XgkWS6dXo/ciAKFwiMf2PM3JnlZu1uJUMg1K7kVEJG68QV9MC1gNKsstAaBDU3NEsNbyVN3zHD59lA+vuJLa8qXJDknSkJJ7ERGJm6nOuS/JLcJgaO9XOUyZ3ay1PN/4Kvta6/nA4ovZULUm2SFJmlJyLyIicRG2YXzBgSnNuXc5XBTlFNKh5F5mudePbmPb8R1cUL2Rixecn+xwJI0puRcRkbjwBQaA2GrcDxepmKPkXmavHSf28KfDr7OmYgVXLb0UY0yyQ5I0puReRETiwhuMfXXa4UpzS+j0dhEOhxMRlkhKa2g7yDMNL7GkZCHXr/ygEns5Z0ruRUQkLqayOu1wpXklhG2Y077uRIQlkrKOdjXz+L5nqCqo4KNrrotp8TeRybiSHYCIiGSG6Sb371XM6aQ0tzjucYnESzgcpsffS7fvDN2+nqF7X/SvVmAYHHcfPgI/tNUMPorcN3YcpiinkNvW34jH6Z6x9yGZTcm9iIjExdC0nKmO3EcT+vb+TmpR6T9JnnA4zJmBweT9zHtJ/EDk/oyvB4s965h8T95Qn7c20jZ8n8imwS02+jzyuDyvlJtWX0vuFMrHikxGyb2IiMSFL+AFIMc1tUQly+WhICtf5TAlaTr7u3iq7o+cONMyKnkv8OQxJ7uQ6sIq5lTUMie7cOhWmJWPy6lUSlKLeqSIiMSFN+DDYMhyeaZ8bFluiRaykqRoaD/IU/ufwxjDxQvOoyhnTjRxL6AwOx+XQ6mSpJeYeqwxZsF4bdbao/ELR0RE0pU34CPHnT2tah+luSXsPLkXa62qhciMCIfDvNL0Oq8f3c7c/MgFrUU5hckOS+Scxfp19PA42+0UziEiIhnMG/RNeb79oLK8YgLhAGcGepiTrQRLEqvP388T+57hSFczG6vWcvWyyzS9RjJGrD15vGEUDa+IiAgQGbnPnmKN+0GDFXPa+zqV3EtCNXef5D/2bsUX9HH9ig+yvmp1skMSiauY6txbax2DNyAfuARYEn0uIiIyNC1nOkoHy2H2a969JIa1lrebd/DrHY/icji5Y9PHldhLRprS36CMMeXA20ANEDbG/Fdr7U8SEpmIiKQVb9BHpbt8WsfmenLIcWerYo4khD/oZ2vDi+xvbWBZ6WJuWHkN2e6sZIclkhBTnWB2O7AAeB1YDHwdUHIvIiKRkftpTsuBwYo5Su4lvjr6Onls71Y6+k/zgcUXc/GC83XRtmS0qSb3NUQuov0g8HngB3GPKE35/f5R25xOJ06nE2stgUAgYe3hcJhgMDiq3eVy4XA4Et4eCoUIhUKj2t1uN8aYhLV7PJFye8FgkHA4fFabMQa32z0j7YFAYGjhkkEOhwOXyzUj7ep76nvDJavvBUJBguEg2a7IaOh0+lZxdhENHQeHXlN9T31vvPZYf+/Vtx/k2caXcTmcfHztDSwpW4S19px+b6rvqe+NlIz/cwd/HmOJtRTmHdGH66P3twIbAWcsx4uISGbzRVenne4FtQClOUX4ggP0B7xasVPOSSgc4tUjb7L95C6q8iu5YcXVFOXOSXZYIjPCjPx2MuZOxoRhaMk2E31sAGutVYIfMfkHKSKSoVp627h/22/56JrrWFm+bFrnONx5lN/tepxPbriFhcXVcY5QZouegV4e3/cMzd0nOG/+Bq5a+n6cDqUqknHGnVsW67ScV1DyKiIi4/AGIiP35zLnvjS3GICO/k4l9zItx7tP8uiep/GH/Ny46kOsqVyR7JBEZlxMyb219vIExyEiImlsKLmfZilMgIKsfDxOtyrmyLTsa2ngqbrnKMjK5/aNH6U8rzTZIYkkRcwX1Bpj1gKfAaqBY8CvrbW7ExWYiIikj8E59+eS3BtjKM0toaNPte4ldtZaXjvyFq81vUnNnHncsuZ6cj26ZkNmr1gvqP0k8Esi83sG5/j8nTHmDmvtbxIVnIiIpId4TMuBSDnMw6ePxiMkmQWCoSBP1z/PvtYG1lWu4toVV+ByTLUQoEhmiXWF2e9G930CuBd4PPr8uwmKS0RE0og34MPtcOFynltiVZpXTK+/D19wIE6RSabq8/fzm52Psa+1gcsXv4/rV35Qib0IsU/LKQN+b639+OAGY8wjROrdi4jILOcN+M5pSs6gstwSILLw0Pw5Ved8PslMbb0dPLLnD/T5+8+pQpNIJop15P4BYL4xxgFgjHEC84CfJyguERFJI96gNy7Jfelgct+vefcytoMdTfzy3YcJhoN8auPHlNiLjBDryP0m4CLguDHmILCUyGh+wBjzYnQfa629KgExiohIivMGfOS4zv0ixqKcQpzGqYo5MqZtzTt5vvEVKvJLuXXtDRRmFyQ7JJGUE2ty//7ofWX0NuiyYY9VB19EZJbyBnwU5p97ouUwDkpzi2nvU3Iv7wmHwzx/8BW2H9/FstLF3LTqQ3hcnmSHJZKSYk3uP5fQKEREJK15Az6y4zAtByKLWZ3saYnLuST9+YIDPLHvGQ51HuHC6k1csfQSHCbWWcUis0+si1g9OPjYGJNrre1PXEgiIpJOrLX4ggPnXAZzUFleCfvbDhAIBXGfY/UdSW9d3jM8svtJOr1dfLj2SjbOW5vskERSXkxffY0xDmPM3xtjTgBnjDELjTEvGmNuT3B8IiKS4nzBASw2LhfUwnsX1XbqotpZrbn7JA++8xC9/j4+sf4mJfYiMYr171rfAP4fYC5grLVHiMy9/0KiAhMRkfQwtIBVnJL7wXKYuqh29trbUs9vdjyGx+nhjk23sai4JtkhiaSNqcy5rwO2A5+MbtsOXJuIoEREJH14g/FN7otz52AwSu5nIWstrzW9yWtH3qJmzjxuWXs9ue5zr8IkMpvEmtxXAY8A3cO2hYD4/CYXEZG0NTRyH6c59y6Hi+KcOXSoYs6sEggFebr+efa3NrB+7mqurb0Cp8OZ7LBE0k6syf1B4ErgLQBjzPXAR4HGBMUlIiJpwhvwApATxxHW0twSWvs64nY+SW29A308uucpTvS0cMWSS7ioZjPGmGSHJZKWYp1z/0NgAfCx6PMngULgfyciKBERSR/xnnMPsLC4mtPeLtqV4Ge81t52HnznYdr6OrhlzfVsWXCeEnuRcxBTcm+tvR/4IpF5915gP/Ala+2/JTA2ERFJA4Nz7rNdWXE756ry5RgM+1oPxO2cknoaOw7zq3cfIWzDfHrTrawoX5rskETSXswFhK21PwV+msBYREQkDXkDPrJd2XEdbc3PymNhUTX7Wuu5dNFFGsnNMNZa3m7ewYsHX6Myv4xb191AQVZ+ssMSyQix1rlfaIz5n8aYG40x640xvzfG/KsxpjjRAYqISGrzBXxxnZIzaHVlLae93ZzqaY37uSV5QuEQzzS8xAsHX6W2bAmf2nSrEnuROIp15P4+4CrgS8ARoBawQD5wR2JCExGRdOANJia5ry1byjMNL7GvtYGqwsq4n19mnjfg4/G9/0lT1zEuXnA+H1h8sf4qIxJnsV5Qez7wOrADWA58CtgFfDBBcYmISJrwBnxxK4M5XI47myUlC9nf2oC1Nu7nl5nV2d/FL995hKPdx7l+5dVcvuR9SuxFEiDW5D4H2Ea0FCbwMPAXoCQRQYmISPrwJmhaDsDqilp6/H0c6z6RkPPLzDja1cyD7zyMN+Dlkxs+yvq5q5IdkkjGijW5byVS+nI3sNVaGwIqga5EBSYiIukhkcn98rIluB0u9rU2JOT8kni7Tu7jtzsfJ8+Tw53nfZyaovnJDkkko8U65/7bgNtaex+R+fcApcCjCYlKRETSQjAcJBAOxHUBq+E8TjfLypZQ13qAq5ddphVL04S1lmPdx3n3xB72tTawqLiGj66+jmx3/MqlisjYYkrurbUPDD42xpRaazustVckLCoREUkLQwtYJWDO/aA1FbXsb22g6fQxlpYuStjryLk74+thd0sdu07uo8vXTZbTw5aa87hs8RZ9MROZITEl98YYJ/A94MtAnjGmD/gX4O+ttcEExiciIinsvdVpEzciu7hkAdmuLPa1Nii5T0HBcJAD7YfZdWofhzuPYrEsLKrm0kUXsaJ8KW6nO9khiswqsU7L+Ub0Nigf+DrQC/xDvIMSEZH04AsOJveJmZYD4HK4qC1bSl3bAQKhIG5nzOsvSgK19Lax6+Q+9rTU4wv6KMjK530LL2Dd3FUU58xJdngis1asvyHvAI4TKYFZB6wEfh3druReRGSWmolpORCpmrPr1D4OdjaxsnxZQl9LxucN+NjXWs+uk/s41duG0zioLVvK+qrVLCquwWFirdMhIokSa3K/APi1tfaV6PNWY8wzwO2JCUtERNLBe9NyEpvcLyyuJs+dy76WeiX3SXC8+yRvH99JQ9tBQjZEZX45Vy/7AGsqVyT8Zy8iUxNrcn8KuMEYcy3vjdzfABxNVGAiIpL6Ziq5dxgHKyuWs+PEHgaCA2S5VHVlpjR3n+DXOx7D43Szcd5a1s9dxdyCimSHJSLjiDW5fxT478DTw7YZ4P+Ne0QiIpI2vEEfLodzRi6aXF1Ry/bjO2loP8Q6LYI0I7p9Z3h0z9PMyS7kzs0f1yi9SBqIdXLcd4jMsQ8QSeqbga8B/ztBcYmISBrwBnwJn28/aH7hXOZkFWhBqxniD/r5/e6nCIVD3LbuBiX2Imki1uS+DPi/iCT4FrgUeASoSVBcIiKSBrwBb0Ir5QxnjGFVRS1Np4/R7/fOyGvOVtZa/lD3R9r6Orh5zYcpzS1OdkgiEqNYk/vD0dtnRzw/lICYRjHG3G+MaTXG7Bm2rcQY85wx5kD0fszfPMaYO6P7HDDG3Dls+2JjzJvR7Q8ZYzzR7cYY80NjTKMxZpcxZnPi36GISHryBnwzOqK7urKWsA1T19Y4Y685G73S9AYN7Ye4atmlLClZmOxwRGQKYk3uzTi3map59QBw7Yht3wResNYuB16IPj+LMaaEyJSii4ALge8M+xLwfeAH0eNPA38d3f5hYHn0dhfw47i+ExGRDOIN+siewYtbK/LKKM0tZl9r/Yy95myzt6Wevxx5mw1Vazh//oZkhyMiUxTTBbXW2qQWrrXWvmKMWTRi803A5dHHDwIvc/ZCWwAfAp6z1nYCGGOeA641xvwOuBL45LDj7yaSyN8E/NJaa4E3jDFFxpgqa+3JiWL0+/2jtjmdTpxOJ9ZaAoFAwtrD4TDB4OiFgl0uFw6HI+HtoVCIUCg0qt3tdmOMSVi7x+MBIBgMEg6Hz2ozxuB2u2ekPRAIEOku73E4HLhcrhlpV99T3xtupvueN+Ajy+kZ6ocz0fdWV9TyatObdPR0UpCVf1a7+t659a02bydb65+nurCKKxa+76yfQar1vZH0ey+9+146/d4bKRl9b/DnMZZ0Xm2icjDhjt6PVZdrPnBs2PPm6LZSoMtaGxyxfaJjRjHG3GWM2WaM2XbfffdN+42IiKQjay2+4ADZM3RB7aDVFSsAqO84OKOvm+l6B/p4dM9T5HnyuGnVtTgdzmSHJCLjGJ6DRm93DbZl+hreZoxtdoLtEx0zeqO1PwN+NtE+EPnGOdE3rHNtdzgcSW0f/EaZrPbBb9PJah8cTUhWeyL7lvqe+t5ErBPCNkx+dt6on1Mi+15JbhFz8yuo7zjI+xZdMOY+6ntTaw+EgjxR/yz+kJ/PrL+NwpyCCY9Pdt/T773M6XtTbVffi7SPyEHP3m/cM6S+FmNMFUD0vnWMfZo5u6JPNXACaAeKjDGuEdsnOkZERIYZWsBqhkfuIXJh7ameVjr7u2b8tTONtZat9c9zsqeFG1d9iIr8smSHJCLnIJ2T+yeBweo3dwJPABhj5htjXohufxa4xhhTHL2Q9hrg2eh8+peAW0ceHz3vHdGqOVuA7snm24uIzEYztTrtWFaVLwdQzfs4eP3oNva1NnD54vexvGxJssMRkXM0peTeGFNrjLkuUcFM8Lq/BV4HVhhjmo0xfw3cC1xtjDkAXB19DlAFBAGiF9J+F3g7ertn8OJaIhff/jdjTCOROfi/iG7fSqTEZyPwc+BLCX57IiJpyRuI1JqfqTr3wxVmF1AzZx77WutHXfwmsatvO8ifDr/OmooVbFlwXrLDEZE4iGnOfbSk5MPAFYA1xiwjkvz+o7X27xMYHwDW2tvHabpqjG1bgH8Zduz9wP1jnPMQkfKYI7db4MvTi1REZPbwBpM3cg+wuqKWZw+8TFtfh6aSTENrbzt/2P9Hqgoq+fCKqzBmrEvORCTdxDpy/z+IlI70A8Za2wS8AXwkQXFNm7X2R9baJ5Mdh4hIpntvzv3M1bkfbmX5MgxGNe+noc/fz+93/4Fsl4db134EtzPT62uIzB6xJvfXEqkj/5Nh2/YBmpwnIjJL+aLJ/UyXwhyU68llcckC9rUemFVTc6y1tPd1DH25mqpgOMhje7fSF/DysXU3kJ+VF+cIRSSZYv2qngOMvKi0jMhIvoiIzEKDq9M6HMmrzbC6opan6p7j+JlTVM+pSlocM8Vay382vMjOk3uByBerktwiSnKKKMktjtznFFGcW4THObqkn7WWZxteprn7BDetvpaqgrGWiBGRdBZrcr+LyBScvQDGmP8B3AD8KUFxiYhIivMGfEkbtR9UW7YEp3Gyr7VhViT3bze/y86Te9k0bx0lOXPo7O+i09vFkdPH2NNSd9a+BZ68oYS/OPoFoKW3nV2n9nHJwgtZXVGbpHchIokUa3L/fwPPE7lYFeC/AwHg7gTEJCIiacAb8CXtYtpBWa4slpUuoq71AB9cdikOk84Vnid2oP0QLxx8jZXly/jQ8stHXQDrDwU47e0aSvhP93fR6T1NXVvj0MXPACvKlnLpootmOnwRmSExJffW2teMMecDXwQWAk3Az6y1uxIYm4iIpDBvwEeuZ+bLYI60uqKW+vaDHO06zqLimskPSEMtvW08se9Z5hZU8JGVV49Z2cbjdFOZX05lfvmoNm/AR6e3i36/l8XFNaqMI5LBYr483lq7B5WIFBGRKG/QR2lecbLDYGnpYjxON/ta6jMyue8d6BuqbHPb2htwjzGXfjI57mzmu+cmIDoRSTWx1rl/cZwma60dq9a8iIhkOG/AS44r+SP3bqeL2rKl1Lcf5Jrw5bgcmVPWMRAK8uiep/AGfHx6062qbCMik4r1N+Dl42yfPbXHRERkSCgcwh8KJH3O/aBVFbXsaanjcOdRlpdlRpVmay1P1z/PiZ4WPrbmeuaqso2IxCDW5P5zCY1CRETSii84AECOOzkLWI20uLiGHFc2e1sbMia5f+3IW+xvbeDyJe+jtnxpssMRkTQR6wW1DwIYYxxEVqu9nkjd+68kLjQREUlV3oAXICWm5QA4HU5Wli9jT0sd/lBgzBrv6WRfSwOvNb3Jurmr2FJzXrLDEZE0MtWaYR8F/haoBT4A/DjuEYmISMobXB01VablAKyurCUQDtLYfjjZoZyT42dO8VTdc9TMmceHa69UZRsRmZKpJvebiMyzPw/4X9HnIiIyy6Ricl8zZz75njz2tdYnO5Rp6/b18OjupyjIyuOWNdfjdDiTHZKIpJmplhTIA7DWvmuMWQ/kxj8kERFJdYOLIqVScm+MYVXFcrY17+SX7zxMQVY+hVkFkfvs6H1WPnme3JRc7Gog6Of3u/9AMBzkkxtvSYk1BEQk/cRaCjM00XMREZldhkbuXamT3ANcUL2JgaCfbt8ZWnrbaew4TDB89n9ZDuOgwJNHQVY+BdkFFA59CcjD7XTjNA6cDicO48TpcOA8696JI9ruNA4cxhGXaTNhG+bJ/c/S1tfBx9ffSFleyTmfU0Rmp1hH7sf7zaVSmCIis5A34MNpHNNaUCmR5mQXcP3KDw49t9biDfjoGejlzEAPZwZ6hx73DPRy8kwLDQMHCdnpj1k5jYOS3GIWFlWzsLiaBXOqyZ5iFaGXD/2Fxo7DXLP8AywpWTjtWEREYk3uFyc0ChERSSvegJccd07KX+xpjCHXk0OuJ4fKgvIx94l8AfDSM9BHIBwkbEOEwmFCZ92HCNswoXCI0Mj7cIiW3jZ2nNzLtuM7MRgqC8pZVFTDwuJqqufMm7B6z86Te3nz2DucN389583fkKiPQkRmiVhLYR4xxristUFjjBO4Fui11v4pseGJiEgq8gZ9ZLtSo8b9uYp8Acgl13Nul5EFw0FOnmmhqauZI6eP8Vbzu7xxbDsO42Be4dzIyH5RNfML5+JyRv77PXK6mWcaXmJx8QI+uPSyeLwdEZnljLWTz6wxxvwfRKrjbAdOATdFm/7BWvvtxIWXVjRFSURmjX9/9/cAfHrTrUmOJHUFQgGau09ypOsYTaebOdXTisXicjipLpxHddE8tjXvJN+Ty2c235YxX5ZEZEaM+2fTWJP7RmDRsJO9DqwFeqy1NXEIMBMouReRWePnb/07JbnFfGzt9ckOJW34ggMc6zrOka5mjpxuprWvnRx3Nndu/gTFOXOSHZ6IpJdxk/tY59zXAL+InuivgauB/w/4/DmHJiIiaccb9KVUGcx0kO3KYnnZEpaXLQGg398PcM7TgUREhos1uXcDwy/fv5XISH7qFQoWEZGEGqxAk2plMNONknoRSYSpLGJ1dfTeAA9E7zUVRURklvGHAoRtWCP3IiIpKNbk/hWUyIuICMMWsFJyLyKScmIthXl5guMQEZE04Q0quRcRSVUxT8sxxiwmcjHtQqAJuN9aezhBcYmISIryBrwA5LhykhyJiIiMFFNyb4y5EHgByOW90jt/a4y50lr7VqKCExGR1OMLDACQ41ZddhGRVBNrtZt7gTzgiejjx4kk+v+YoLhERCRFeYPRkXu3Ru5FRFJNrNNyNgKPWmtvG9xgjHkEuCohUYmISMoavKBWK6qKiKSeWEfufUDZiG1l0e0iIjKLeAM+spwenA5nskMREZERYh25/zNwizHmAFAP1AJLgUcTFZiIiKQmb0Cr04qIpKpYk/u/A84jktAvjW5rAr6egJhERCSFeYM+spXci4ikpFjr3B8xxqwFPsJ7pTCfttb2JzA2ERFJQd6AjxyXknsRkVQUc537aCL/cAJjSWt+v3/UNqfTidPpxFpLIBBIWHs4HCYYDI5qd7lcOByOhLeHQiFCodCodrfbjTEmYe0ejweAYDBIOBw+q80Yg9vtnpH2QCCAtWcv4OxwOHC5XDPSrr6nvjfcTPQ9b8BLcU6R+p763lnt+r2nvjcT7ep7kb4x+PMYy4TJvTGmc6J2wFprSyfZR0REMogvOKAa9yIiKcqM/HZyVqMx4XEbI6y1VuUSIsb/IEVEMkQ4HOb7r/yI9y+8kEsXb0l2OCIis5UZr2GyaTlXDHv8FeAW4Mp4RCQiIunHF4xUQNYCViIiqWnC5N5a+6fBx8aYm0duExGR2WVwASuVwhQRSU2xLmIlIiKCN6jkXkQklU12Qe2Nw54ujW67gWHzfKy1TyYmNBERSTVDI/cqhSkikpImm3P/OKMvFH182GMbwzlERCRDaFqOiEhqmywxP4qqwIiISJSSexGR1DbZBbWLZigOERFJA96gF4dx4HGOv4CKiIgkjy6oFRGRmHkDA2S7sjBm3BLLIiKSREruRUQkZt6AV1NyRERSmJJ7ERGJmTfo0wJWIiIpTMm9iIjEzBvwqQymiEgKU3IvIiIx8wZ8mpYjIpLClNyLiEhMrLVK7kVEUpySexERiUkgHCRkQ0ruRURSmJJ7ERGJydACVppzLyKSspTci4hITHxanVZEJOUpuRcRkZh4g0ruRURSnZJ7ERGJiTfgBSDHpTr3IiKpSsm9iIjExKtpOSIiKU/JvYiIxETJvYhI6lNyLyIiMfEGfXicbpwOZ7JDERGRcSi5FxGRmHgDPpXBFBFJcUruRUQkJlqdVkQk9Sm5FxGRmHiDPrKV3IuIpDQl9yIiEhNNyxERSX1K7kVEJCaaliMikvqU3IuIyKTCNowv6CPHrQWsRERSmZJ7ERGZlC84AKjGvYhIqlNyLyIikxpawEpz7kVEUpqSexERmZRWpxURSQ9K7kVEZFJK7kVE0oOSexERmZQ3qOReRCQdKLkXEZFJ+aIj99macy8iktKU3IuIyKS8AR8GQ7YrK9mhiIjIBNI+uTfGNBljdhtjdhhjto3RnmWMecgY02iMedMYs2hY253GmAPR253Dti+O7nsgeqxnZt6NiEhq8gZ9ZLuzMMYkOxQREZlA2if3UVdYazdaa88fo+2vgdPW2mXAD4DvAxhjSoDvABcBFwLfMcYUR4/5PvADa+1y4HT0HCIis5Y34CXHpQWsRERSnSvZAcyAm4C7o49/D/zIRIaePgQ8Z63tBDDGPAdca/7/9u48ys67vu/4+3uXWbWONluyLNlGXuQFZINZHHygBDt1COQATaEN4UBaTuiBky6np/SkyaGBtA1N00LdNuVAwtISkjRlCXEgBMxS1wYs2xWSLXmRja0FSSNZy8xo5m6//nGfGV2NZrTO3DvzgwCY2QAAG31JREFUzPt1znPuc5/fc5/7u898dfW5z/09z434IvC3gL+XPeaz2eP/29mepFKpnLGsWCxSLBZJKVGtVmetvdFoUKvVzmgvlUoUCoVZb6/X69Tr9TPay+UyETFr7V1dzS9UarUajUbjtLaIoFwut6W9Wq2SUjqtvVAoUCqV2tJu7Vl7rWar9kYqJ+kpdVGr1aw9a8/3PWvvtDZrr/21N/73mEoejtwn4K8jYmtEvG+K9nXACwAppRpwDFjRujyzJ1u2Ajiardu6/AwR8b6IeDgiHv7Upz41Iy9Gkuaik9VRT6aVpDmiNYNm00QGjsmfTuabiFibUtoXEauBbwIfTCl9r6V9B3B3SmlPdv8ZmsNw3gt0p5Q+mi3/TWAE+BzwYDaMh4hYD9yXUrr5HF2Z3ztSks7i3gf/kI3L1/Om69/Y6a5IkmDaE6Dm/ZH7lNK+7PYg8CWawb3VHmA9QESUgKXAkdblmSuAfcAgsCxbt3W5JC1YJ6uj9HrkXpLmvHkd7iOiPyIWj88DdwHbI+IDEfGBbLWvAuNXwnk78O3U/LriG8BdEbE8O5H2LuAbWdv92bpkj/1Ke16RJM091XqNWqPmD1hJ0jww30+oXQN8Kbs0Wwn4Qkrp6xFxL/BAts6ngc9HxNM0j9i/AyCldCQiPgL8KFvvt8dPrgX+BfDFiPgo8Gi2DUnKvZQSQ5VhDg4Ncmj4MAeHBzk4NAhAX9mr5UjSXDfvx9xPJSK+Brw1pXTmKc2zJ387UlKuVetVDg0f4VAW4A8OD3Jo6DAna6MT6yzuXsTq/pWsWbSS29ff6tF7SZobph1zn8tw3yHuSElz2nBlhMf2befA0CEODh/mxZNHJ9rKhTKr+gdYvWglq/pXZrcrDPOSNDcZ7tvAHSlpztpzbD9f3nEfJyrDLO9dxur+FaxatJLV/StZvWgFy3qW+uuzkjR/GO7bwB0pac5JKbF17za+9cz3WdK9iLfe+POsWbyq092SJF2aacP9fD+hVpI0jUq9ytd3fZsdB3fxkhUbedP1dznMRpJyznAvSTl0eORFvrTjPg4NH+bOja/iNRte4bAbSVoAHJYzc9yRkuaEXYee4S93fpNCFHjz5ru5emBDp7skSZpZDsuRpLxrNBp899kHeeiFrVy2eDVvvfEelvYs6XS3JEltZLiXpBwYrozwlce/zk+O7mHL5Tfxs5vupFTwLV6SFhqH5cwcd6Skjhi/zOXJ2ih3b3o9t1y+udNdkiTNLi+F2QbuSElt5WUuJWnBcsy9JOVJ62UurxnYyC/c4GUuJUmGe0maV1JK7D9xkPt2/Y2XuZQkncFhOTPHHSlp1hwbPc6OA7vYfmAnh0depKfUw1u8zKUkLVSOuW8Dd6SkGTVaHWPnoafYcWAXzx/bC8AVS9dy05rruH7VJofhSNLCZbhvA3ekNI+dGBvigZ/8iFKhSHepm55Sd3bb1TLfvO0uds3aMJh6o84zR55jx4FdPDX4LPVUZ6B3GTetuZ4b11zHst6ls/K8kqR5xRNqJelsHnz+YR7bt51ysUSlXj3n+t3F00N/f1cfi7sXZVM/i7sXsairOV8sFM+6rZQSe4//lO0HdvLEwacYrY3SV+5ly9qbuHHN9Vy+eLVj6iVJ58VwL2nBG6tV+PFPn2Dzmmt58w1302g0GKtXGK2NMVYbm+L2VNtYbYyTtTH2nzjIU4d3U2vUz9h+X7mXxd39Wdg/Ff77u/rZd/yn7Diwk6OjxykVSly78mpuXHM9Vy1ff84PBZIkTWa4l7Tg7Tiwk0q9ym1rbwGgUCjQW+i54DHtKSVGa2OcGBvixNgQQ5XhbH44uz/E/hMHGKmePO1xG5ev546Nr+S6lVfTXeqesdclSVp4DPeSFrSUEo/s+zGXLVrF2iWXXdK2IoLecvNDwepFK6ddr9aoMTQ2wlBlmKU9i1ncveiSnleSpHGGe0kL2gvH9nFo+DD3XPeGto1rLxVKLOtdwrLeJW15PknSwlHodAckqZMe2buNnlI3m1df2+muSJJ0yQz3khasobFhdg0+wy2XbaZcLHe6O5IkXTLDvaQF67H922mkBlvW3tzprkiSNCMM95IWpHqjzqP7tnPV8isZ6FvW6e5IkjQjDPeSFqSnBnczVBnmtnW3dLorkiTNGMO9pAVp675tLO1ezDUrNna6K5IkzRjDvaQFZ3D4MM8f3cuWtTdTCN8GJUn54f9qkhacrXt/TDEKvPTyzZ3uiiRJM8pwL2lBGatV2H7gCW5YfS19XX2d7o4kSTPKcC9pQdlxYCeVepVbPZFWkpRDhntJC0ZKia17t3HZolWsXbym092RJGnGGe4lLRgvHNvL4MgRbl13CxHR6e5IkjTjDPeSFoyte7fRU+pm8+prO90VSZJmRanTHciLSqVyxrJisUixWCSlRLVanbX2RqNBrVY7o71UKlEoFGa9vV6vU6/Xz2gvl8tExKy1d3V1AVCr1Wg0Gqe1RQTlcrkt7dVqlZTSae2FQoFSqdSWdmvv/GpnqDLMk4O72XL5zZQKzX1n7Vl7F9vu+561N5m1Z+21s/bG/x5T8ci9pAVh24EnaKQGL13j5S8lSfkVkz+d6KK5I6U5qt6o818f+gyrF63k797ylk53R5KkSzXtiWMeuZeUe08N7maoMsyta738pSQp3wz3knJv675tLO1ZwjUrNnS6K5IkzSrDvaRcOzR8mOeP7mXL2psohG95kqR88386Sbn2yN5tFKPISy+7sdNdkSRp1hnuJeXWWK3C9gM7uWH1Jvq6ejvdHUmSZp3hXlJubT+wk0q9ym3rPJFWkrQwGO4l5VJKiUf2buOyRau5fPGaTndHkqS2MNxLyqUXju1lcOQIt627hYhpLwcsSVKuGO4l5dLWvdvoKfVww+prO90VSZLaxnAvKXdOjA3x5OBuXnr5ZsrFUqe7I0lS2xjuJeXOY/u200gNtqy9qdNdkSSprQz3knKl3qjz2P4dXD2wgeW9yzrdHUmS2spwLylXdhx8kqHKsJe/lCQtSA5GlZQLR0aO8t1n/y87Dz3Nyr4Brh7Y0OkuSZLUdoZ7SfPa0NgwD/zkhzy2fwfFKHLHhtt55fotFMIvJiVJC4/hXtK8NFYb4wcvPMoPX3iUeqrzsstv5I4Nt7Oou7/TXZMkqWMM95LmlXqjzqP7tvPAT37ISPUkN6zaxJ1XvZqBPk+elSTJcC9pXkgp8fjBJ/nesw9ydPQ4G5ZdweuuvoO1S9Z0umuSJM0ZkVLqdB/ywh0pzZJnjzzP/bsf4MDQIVb3r+T119zBVcuvJCI63TVJkjph2v8ADfczxx0pzbCfnjjI/bsf4LkXX2Bp92LuvOrV3LjmOkO9JGmhM9y3gTtSmqTeqHN09DijtTFq9SqVeo1qo0qtXqNSr1JrTLrN2qv1GqO1MfYe309vqYfXbHgFt667mVLBkYSSJGG4bwt3pBasSr3K4ZEXOTx8hMGRIxweOcLg8Iu8ePIo6Tz+aZQKJcrFEuVC+bTb9cvW8cr1t9JT6m7Dq5Akad4w3LeBO1K5N1I9yeHhF5vhfeQIh0deZHD4CMfHTkysU4gCy3uXsqJvgJV9yxnoW05vuZeuYolSoXz6bbFMuVBymI0kSRfGcN8G7kjNOSkljo+dYDA7oj44fIShyjCN1CCldNptg0RK6dRyEo2USNk6lXqVk7XRiW2XCiVW9C2fCPEr+wdY0TfA8t6lFAvFDr5qSZJyz3DfBu5IdUxKiaOjxxkcHh8ScyrMVxvVifX6y30s6VlMIYKIAgWCiOZUiEJzOdntpHXKhRLL+5ZlYX6ApT2LPeIuSVJnGO7bwB2pWZVSYrQ2xrHR4xwdPc6RbEjM+PCYWqM2se6irn5W9jdD+Mr+FazsG2BF/3L6yr0dfAWSJGmGGO7bwB2pSzZaG+PYyeMTAf7YxHSCo6PHqNSrp62/pHtxS4gfmDiq3lP2BFRJknLMcN8G7khNK6XEyeooQ5Vhhisjp90eGz3BsdFjHBs9wWht7LTHdRXLLO1ZMjEtm5hfzPLeZXSXujr0iiRJUgcZ7tvAHbnAjJ9kOlI9yUhlhKHKCMOV4Zbb8fnm1EiNM7ZRLpRZ2rN4IrAv61l66n7vEnpLPY5rlyRJkxnu28AdOc+llKg1aoxUTzJcOTkR2keqJ7Nl2XzlJCPV5nytUZ9yW/3lPhZ199Hf1U9/Vx+LWm4XdTWXL+rqo8sj75Ik6cIZ7tvAHTlDGqlBtd78ldLmr5nWqTZq1Manem3ifrXesrxRo1qvT8zXG3XqqU6tUafeOHXbumzy/el+cKlUKNJX7qOvq5e+ci/9LfN9XX30lXtZlIX3vnIvhUKhzXtNkiQtIIb7NnBHTpJSYv+Jgzx/dA9jtTEq9SrVepVKo0a1XqFar00sq9arzflGddqj4edSiALlQolSoUSpUKTYMpWiZb5QpFgonbksipSLJfqzsD4e3PvLvZSLZYfHSJKkucJw3wbuSJqBfu/xn7Lr0NPsPPT0xC+XBkFXsUxXsUw5mybmCyW6il2Ui6dum8vLlIvjYb3UMl+kXCw3lxWKE+0eLZckSQuE4b4NFuyObKQGe47tZ+ehp9l16GmGKsMUo8BVA1dy3apNvGTFRk8MlSRJmjnThqpSO3sxn0TEzwEfB4rAp1JK/67DXZpTGo0Gzx/by85DT/PkoWcYro5QKhS5emAj1626hpesuIqektdalyRJaieP3E8hIorAk8AbgT3Aj4B3ppQeP8vDcr8j6406Pzm6pxnoB5/hZHWUcqHENSs2cv2ql3DNwEav/iJJkjT7PHJ/gW4Hnk4p7QaIiC8CbwGmDfdPHnxmYj6y/V0oFCgWi81LLNZqZwxLKRQKFAsFUoJavXZaW0qJYqFAFApAolY780ouhUKBQqFAaiTq9VMnoY6vVywWiQgaKdHI2hMpuxpNjRSJeqpTqVWp1CrUGvWJE1prjdrEVWRq2YmvR0ePMVobo6tY5urlG7hh9SauWbGRAoXm8zegUqlM9KNcbp6EWq/XT+vfTLV3dTU/SNRqNRqN068hHxGUy+W2tFerVSZ/SC4UCpRKpba0t+7zccVicaL2qtXqrLU3Gg1qtdoZ7aVS8xyI2W6frdqy9qw9a8/am67d2rP2JutE7Y3/PaZiuJ/aOuCFlvt7gFdOXiki3ge8D+Df3P/x9vRsFk2+2ky5WKZULFGKEt2lLq4Z2MimgavYsOyK5jotbzSSJElqj9YMmvlkSumT4LCcKUXE3wHuTin9g+z+u4DbU0ofnO4xe47tSwCn7840xdyk5QlOP6AfZ5+bZt0zXsMZC04tKY6H+OzqM+PzhfBqM5IkSfOAw3Iu0B5gfcv9K4B9Z3vAFUvXzmqHJEmSpHPxUO3UfgRsioirIqILeAfw1Q73SZIkSTorj9xPIaVUi4gPAN+geSnMP0wp7ehwtyRJkqSzcsz9zHFHSpIkqR2mHXPvsBxJkiQpJwz3kiRJUk4Y7iVJkqScMNxLkiRJOWG4lyRJknLCcC9JkiTlhOFekiRJygnDvSRJkpQThntJkiQpJwz3kiRJUk4Y7iVJkqScMNxLkiRJOWG4lyRJknLCcC9JkiTlhOFekiRJygnDvSRJkpQThntJkiQpJwz3kiRJUk4Y7iVJkqScMNxLkiRJOWG4lyRJknLCcC9JkiTlhOFekiRJygnDvSRJkpQThntJkiQpJwz3kiRJUk4Y7iVJkqScMNxLkiRJOWG4lyRJknLCcC9JkiTlhOFekiRJygnDvSRJkpQThntJkiQpJ0qd7kBeVCqVM5YVi0WKxSIpJarV6qy1NxoNarXaGe2lUolCoTDr7fV6nXq9fkZ7uVwmImatvaurC4BarUaj0TitLSIol8ttaa9Wq6SUTmsvFAqUSqW2tFt71l4ra8/aa0e7tWfttbL22l9743+PqXjkXpIkScqJmPzpRBfNHSlJkqR2iOkaPHIvSZIk5YThXpIkScoJw70kSZKUE4Z7SZIkKScM95IkSVJOGO4lSZKknDDcS5IkSTlhuJckSZJywnAvSZIk5YThXpIkScoJw70kSZKUE4Z7SZIkKScM95IkSVJOGO4lSZKknDDcS5IkSTlhuJckSZJywnAvSZIk5YThXpIkScqJSCl1ug+5EBHbgdFO90Pz0kpgsNOd0Lxj3ehiWTu6GNbN3DKYUvq5qRpK7e5Jjo2mlF7e6U5o/omIh60dXSjrRhfL2tHFsG7mD4flSJIkSTlhuJckSZJywnA/cz7Z6Q5o3rJ2dDGsG10sa0cXw7qZJzyhVpIkScoJj9xLkiRJOZHbcB8R6yPi/oh4IiJ2RMSvZ8sHIuKbEfFUdrs8W74iW38oIu6dtK3vRMSuiHgsm1ZP85y3RcSPI+LpiPhERES2/Mps249GxLaIuGeax3dHxJ9kj/9BRGxsaft6RByNiK/NzB7SVGa4broi4pMR8WRE7IyIt03znFPWTdb2SxHxeNaXL0zzeOtmDpip2omIxS3vNY9FxGBE/KdpnnPa2sna3x4RKSKmvMKFtdN5M/ye886sHrZlf7+V0zzndP9X/dPs/WZbRHwrIjZM83jrZg7oUO38TkS8EBFDk5ZbO3NJSimXE3A5cGs2vxh4EtgMfAz4ULb8Q8DvZvP9wM8AvwbcO2lb3wFefh7P+UPg1UAAfwX87Wz5J4H3Z/Obgeemefw/Av4gm38H8CctbW8AfgH4Wqf3bZ6nGa6bfw18NJsvACsvsG42AY8Cy7P7q62buTvNZO1M2u5W4M4LqZ2WPnwPeGi69y9rp/PTTNUNzUtbHxx/n8ke/+ELqRvg9UBfNv/+1nqwbube1KHaeVX2vEOTlls7c2jK7ZH7lNL+lNIj2fwJ4AlgHfAW4LPZap8FfjFbZzil9H+4yB+iiojLgSUppQdTs0o/N75tIAFLsvmlwL5pNtPat/8FvGH8iEpK6VvAiYvpm87fDNfNe4F/m63XSCmd8eMf56ibfwj8l5TSi9k2Dk7TbetmDpiN95yI2ASsBr4/RdvZagfgIzT/kz7be5q102EzWDeRTf3Z33AJU/xfc7a6SSndn1IayVZ9CLhimm5bN3NAu2sn28ZDKaX9Uyy3duaQ3Ib7VtnXPluAHwBrxgszu51yiM0U/ij7ivw3J3/1nVkH7Gm5vydbBvBh4JcjYg9wH/DBaZ5jHfBC1rcacAxYcZ790wy7lLqJiGXZ7Eci4pGI+LOIWDPFqmerm2uBayPigYh4KCKm/CU6rJs5Z4becwDeSfPI1lRXPpi2diJiC7A+pXSur7etnTnkUuompVSlecT0xzSD2Wbg01Oserb3nFa/SvOo/lSsmzmmTbVzvqydDst9uI+IRcCfA/84pXT8Ijfz91NKNwOvzaZ3TfVUUywb/w/5ncBnUkpXAPcAn4+Iqfb92bahNpqBuinRPHLxQErpVuBB4Pemeqoplo3/zUs0h+a8jmYNfarlQ8P5bkNtNkPvOePeAfzxdE81xbKUvbf8R+Cfncf2rZ054lLrJiLKNAPaFmAtsA34l1OtOsWy0/7mEfHLwMuBfz/d051rG2qfNtbO+WzL2pkDch3us4L9c+B/ppT+d7b4QPa15PjXk9MNdZiQUtqb3Z4AvgDcHhHFOHXC22/TPPrR+jXUFZz6WutXgT/NtvEg0AOszE5MeSwiHsvW2wOsz/pWojmE58jFvXpdrBmqm8PACPCl7P6fAbdeYN3sAb6SUqqmlJ4FdgGbrJu5a6bec7J1XwqUUkpbs/vnWzuLgZuA70TEczTHyH41Il5u7cxNM1Q3LwNIKT2TfdPzp8BrLvA9h4j4WeA3gDenlMayZdbNHNXm2jlXX6ydOSK34T4bOvNp4ImU0u+3NH0VeHc2/27gK+fYTimys8azf0RvAranlOoppZdl029lX32diIhXZc/9Ky3bfp7miSJExA00w/2hlNJvjG9jir69Hfj2NF/Ha5bMVN1kf7e/oHnUHZp//8cvsG6+TPMkJbIavBbYbd3MTTNVOy3eSctR+/OtnZTSsZTSypTSxpTSRprjX9+cUnrY2pl7ZrBu9gKbI2JVdv+N2TbP+z0nG87132nWy0QgtG7mpnbXzjn6Yu3MJWkOnNU7GxPNM8ITza+XHsume2iO7foW8FR2O9DymOdofoIcovnpcjPNs8u3ZtvZAXwcKE7znC8HtgPPAPdy6kfCNgMPAP8v68dd0zy+h+YR3qdpXs3g6pa27wOHgJNZ3+7u9D7O4zRTdZMt30DzaiXbssdceYF1E8DvA4/THAv5Dutm7k4zWTtZ227g+nM855S1M2md7zD91XKsnRzVDc2roDyRbesvgBUXUjfA3wAHWvrxVetm7k4dqp2PZY9rZLcftnbm3uQv1EqSJEk5kdthOZIkSdJCY7iXJEmScsJwL0mSJOWE4V6SJEnKCcO9JEmSlBOGe0mSJCknDPeSJElSThjuJUmSpJww3EuSJEk5YbiXJEmScsJwL0mSJOWE4V6SJEnKCcO9JEmSlBOGe0mSJCknDPeSJElSThjuJUmSpJww3EuSJEk5YbiXJEmScsJwL0mSJOWE4V6SJEnKCcO9JEmSlBOGe0mSJCknDPeSJElSThjuJUnnJSKei4iUTXe0LH9ty/LnOthFSVrwDPeSpIvx/pb5X+tYLyRJpzHcS5Iu1IvA2yNiZUSsAt6WLZsQEVdGxBcjYm9EHI2Iv46Im1raByLiExHxTESMRsTuiHhT1vYzEfFIRJxs+UYgtTx2fNnG7P74Nwqvm/2XLklzm+FeknShPgt0A+/Npm7gM+ONEdEHfBv4JWAb8E3gdcD92QeCAvBl4IPZY/8HsBu4OtvE7wFbgIeAP5r1VyNJOVLqdAckSfPOd4G7gPcBATwOfA/4J1n7zwPXAHuBXdmy57NlbwceBl4LjAKvSCntB4iI8qTn+RjwBPCe2XohkpQ3hntJ0sX4A+AT2fwHJ7VtzG7XAb8+qe0lwOFs/vnxYA+QUqpmsx8C/hK4b6Y6K0kLhcNyJEkX43PACDAMfH5S23PZ7VagkFKKlFIAy4HfAZ7N2q+MiMvGHxQR4wecHgQOAPUpti1JOguP3EuSLlhK6VhE3Nky39p8H80x9LcBD0TENuBKmuPu76E5hOf7NIfm/Cgivk7zKP9fAf8Z+OfAVcC9wH8A3jVNN34rIo4DA9n9D0TESErphzP1OiVpvvHIvSTpoqSUtqaUtk6xfBh4A/DHNEP9u4HraJ44uyul1AB+kWaQrwK/AlwPPBcRV9AclnMQ+Ffn6MJ7aA77WZzdfxuw+RJfliTNa5FSOvdakiTNYdllMZ8F3pNS+kxHOyNJHeSRe0lSHhyhebUeh+RIWtA8ci9JkiTlhEfuJUmSpJww3EuSJEk5YbiXJEmScsJwL0mSJOWE4V6SJEnKCcO9JEmSlBP/H2YGWrdQ7eZKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "registrations = pd.read_csv('./new_users_by_month.csv')\n",
    "registrations = registrations.set_index(registrations['date'])\n",
    "registrations.drop('date', axis=1, inplace=True)\n",
    "\n",
    "ax = registrations.plot(grid=False, figsize=(12,8), color='#86bf91', zorder=2)\n",
    "\n",
    "# ax = ax[0]\n",
    "# for x in ax:\n",
    "x = ax\n",
    "    # Despine\n",
    "x.spines['right'].set_visible(False)\n",
    "x.spines['top'].set_visible(False)\n",
    "x.spines['left'].set_visible(False)\n",
    "\n",
    "# Switch off ticks\n",
    "x.tick_params(axis=\"both\", which=\"both\", bottom=\"off\", top=\"off\", labelbottom=\"on\", left=\"off\", right=\"off\", labelleft=\"on\")\n",
    "\n",
    "# Draw horizontal axis lines\n",
    "vals = x.get_yticks()\n",
    "for tick in vals:\n",
    "    x.axhline(y=tick, linestyle='dashed', alpha=0.4, color='#eeeeee', zorder=1)\n",
    "\n",
    "# Remove title\n",
    "x.set_title(\"\")\n",
    "\n",
    "# Set x-axis label\n",
    "x.set_xlabel(\"Месяц\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "# Set y-axis label\n",
    "x.set_ylabel(\"Новые юзеры\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "# Format y-axis label\n",
    "x.yaxis.set_major_formatter(StrMethodFormatter('{x:,g}'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "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>Unnamed: 0</th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>10</th>\n",
       "      <th>8</th>\n",
       "      <th>6</th>\n",
       "      <th>4</th>\n",
       "      <th>2</th>\n",
       "      <th>0</th>\n",
       "      <th>shop_header</th>\n",
       "      <th>deals_min</th>\n",
       "      <th>summary_comments</th>\n",
       "      <th>commented_share</th>\n",
       "      <th>deals_max</th>\n",
       "      <th>commented_share_min</th>\n",
       "      <th>commented_share_max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>522</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>King of Buzz</td>\n",
       "      <td>1000</td>\n",
       "      <td>535</td>\n",
       "      <td>53.500000</td>\n",
       "      <td>1499</td>\n",
       "      <td>0.535000</td>\n",
       "      <td>0.356905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>253</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>БУКЕТ ЧУВАШИИ Premium</td>\n",
       "      <td>500</td>\n",
       "      <td>266</td>\n",
       "      <td>53.200000</td>\n",
       "      <td>749</td>\n",
       "      <td>0.532000</td>\n",
       "      <td>0.355140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3717</td>\n",
       "      <td>85</td>\n",
       "      <td>44</td>\n",
       "      <td>9</td>\n",
       "      <td>16</td>\n",
       "      <td>21</td>\n",
       "      <td>spbShop</td>\n",
       "      <td>6000</td>\n",
       "      <td>3892</td>\n",
       "      <td>64.866667</td>\n",
       "      <td>6999</td>\n",
       "      <td>0.648667</td>\n",
       "      <td>0.556079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>9530</td>\n",
       "      <td>233</td>\n",
       "      <td>50</td>\n",
       "      <td>17</td>\n",
       "      <td>22</td>\n",
       "      <td>26</td>\n",
       "      <td>masterclad shop</td>\n",
       "      <td>20000</td>\n",
       "      <td>9878</td>\n",
       "      <td>49.390000</td>\n",
       "      <td>24999</td>\n",
       "      <td>0.493900</td>\n",
       "      <td>0.395136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1076</td>\n",
       "      <td>19</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Johnson &amp; Johnson</td>\n",
       "      <td>1500</td>\n",
       "      <td>1107</td>\n",
       "      <td>73.800000</td>\n",
       "      <td>1999</td>\n",
       "      <td>0.738000</td>\n",
       "      <td>0.553777</td>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3371</td>\n",
       "      <td>3371</td>\n",
       "      <td>3404</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Marussia Shop</td>\n",
       "      <td>63</td>\n",
       "      <td>33</td>\n",
       "      <td>52.380952</td>\n",
       "      <td>63</td>\n",
       "      <td>0.523810</td>\n",
       "      <td>0.523810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3372</td>\n",
       "      <td>3372</td>\n",
       "      <td>3405</td>\n",
       "      <td>334</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Drug's tvoego druga</td>\n",
       "      <td>500</td>\n",
       "      <td>348</td>\n",
       "      <td>69.600000</td>\n",
       "      <td>749</td>\n",
       "      <td>0.696000</td>\n",
       "      <td>0.464619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3373</td>\n",
       "      <td>3373</td>\n",
       "      <td>3406</td>\n",
       "      <td>2406</td>\n",
       "      <td>20</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>★LIRIKA_SHOP★ (Ищем Курьеров на ЛИРИКУ)</td>\n",
       "      <td>4000</td>\n",
       "      <td>2454</td>\n",
       "      <td>61.350000</td>\n",
       "      <td>4499</td>\n",
       "      <td>0.613500</td>\n",
       "      <td>0.545455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3374</td>\n",
       "      <td>3374</td>\n",
       "      <td>3407</td>\n",
       "      <td>100</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>BLACK WARRIOR</td>\n",
       "      <td>254</td>\n",
       "      <td>110</td>\n",
       "      <td>43.307087</td>\n",
       "      <td>254</td>\n",
       "      <td>0.433071</td>\n",
       "      <td>0.433071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3375</td>\n",
       "      <td>3375</td>\n",
       "      <td>3408</td>\n",
       "      <td>5478</td>\n",
       "      <td>81</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "      <td>17</td>\n",
       "      <td>НАША МАРКА(Нужны курьеры)</td>\n",
       "      <td>10000</td>\n",
       "      <td>5622</td>\n",
       "      <td>56.220000</td>\n",
       "      <td>14999</td>\n",
       "      <td>0.562200</td>\n",
       "      <td>0.374825</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3376 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0  Unnamed: 0.1    10    8   6   4   2   0  \\\n",
       "0              0             0   522    6   3   1   1   2   \n",
       "1              1             1   253    8   1   1   1   2   \n",
       "2              2             2  3717   85  44   9  16  21   \n",
       "3              3             3  9530  233  50  17  22  26   \n",
       "4              4             4  1076   19   6   1   1   4   \n",
       "...          ...           ...   ...  ...  ..  ..  ..  ..   \n",
       "3371        3371          3404    33    0   0   0   0   0   \n",
       "3372        3372          3405   334    5   3   1   4   1   \n",
       "3373        3373          3406  2406   20   4   6   4  14   \n",
       "3374        3374          3407   100    4   2   0   0   4   \n",
       "3375        3375          3408  5478   81  26   6  14  17   \n",
       "\n",
       "                                  shop_header  deals_min  summary_comments  \\\n",
       "0                                King of Buzz       1000               535   \n",
       "1                       БУКЕТ ЧУВАШИИ Premium        500               266   \n",
       "2                                     spbShop       6000              3892   \n",
       "3                             masterclad shop      20000              9878   \n",
       "4                           Johnson & Johnson       1500              1107   \n",
       "...                                       ...        ...               ...   \n",
       "3371                            Marussia Shop         63                33   \n",
       "3372                      Drug's tvoego druga        500               348   \n",
       "3373  ★LIRIKA_SHOP★ (Ищем Курьеров на ЛИРИКУ)       4000              2454   \n",
       "3374                            BLACK WARRIOR        254               110   \n",
       "3375                НАША МАРКА(Нужны курьеры)      10000              5622   \n",
       "\n",
       "      commented_share  deals_max  commented_share_min  commented_share_max  \n",
       "0           53.500000       1499             0.535000             0.356905  \n",
       "1           53.200000        749             0.532000             0.355140  \n",
       "2           64.866667       6999             0.648667             0.556079  \n",
       "3           49.390000      24999             0.493900             0.395136  \n",
       "4           73.800000       1999             0.738000             0.553777  \n",
       "...               ...        ...                  ...                  ...  \n",
       "3371        52.380952         63             0.523810             0.523810  \n",
       "3372        69.600000        749             0.696000             0.464619  \n",
       "3373        61.350000       4499             0.613500             0.545455  \n",
       "3374        43.307087        254             0.433071             0.433071  \n",
       "3375        56.220000      14999             0.562200             0.374825  \n",
       "\n",
       "[3376 rows x 15 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfm1 = dfm[dfm['deals_max'] < dfm['deals_max'].quantile(0.99)]\n",
    "\n",
    "ax = dfm1.hist(column='deals_max', bins=25, grid=False, figsize=(12,8), color='#86bf91', zorder=2, rwidth=0.9)\n",
    "\n",
    "ax = ax[0]\n",
    "for x in ax:\n",
    "\n",
    "    # Despine\n",
    "    x.spines['right'].set_visible(False)\n",
    "    x.spines['top'].set_visible(False)\n",
    "    x.spines['left'].set_visible(False)\n",
    "\n",
    "    # Switch off ticks\n",
    "    x.tick_params(axis=\"both\", which=\"both\", bottom=\"off\", top=\"off\", labelbottom=\"on\", left=\"off\", right=\"off\", labelleft=\"on\")\n",
    "\n",
    "    # Draw horizontal axis lines\n",
    "    vals = x.get_yticks()\n",
    "    for tick in vals:\n",
    "        x.axhline(y=tick, linestyle='dashed', alpha=0.4, color='#eeeeee', zorder=1)\n",
    "\n",
    "    # Remove title\n",
    "    x.set_title(\"\")\n",
    "\n",
    "    # Set x-axis label\n",
    "    x.set_xlabel(\"Количество сделок\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "    # Set y-axis label\n",
    "    x.set_ylabel(\"Магазины\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "    # Format y-axis label\n",
    "    x.yaxis.set_major_formatter(StrMethodFormatter('{x:,g}'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "datedate = pd.to_datetime(dfc['date'])\n",
    "dfcd = dfc.set_index(datedate)\n",
    "dfcd_month = dfcd.resample('M')['deals_count'].count()\n",
    "\n",
    "# registrations = pd.read_csv('./new_users_by_month.csv')\n",
    "# registrations = registrations.set_index(registrations['date'])\n",
    "# registrations.drop('date', axis=1, inplace=True)\n",
    "\n",
    "ax = dfcd_month.plot(grid=False, figsize=(12,8), color='#86bf91', zorder=2)\n",
    "\n",
    "# ax = ax[0]\n",
    "# for x in ax:\n",
    "x = ax\n",
    "    # Despine\n",
    "x.spines['right'].set_visible(False)\n",
    "x.spines['top'].set_visible(False)\n",
    "x.spines['left'].set_visible(False)\n",
    "\n",
    "# Switch off ticks\n",
    "x.tick_params(axis=\"both\", which=\"both\", bottom=\"off\", top=\"off\", labelbottom=\"on\", left=\"off\", right=\"off\", labelleft=\"on\")\n",
    "\n",
    "# Draw horizontal axis lines\n",
    "vals = x.get_yticks()\n",
    "for tick in vals:\n",
    "    x.axhline(y=tick, linestyle='dashed', alpha=0.4, color='#eeeeee', zorder=1)\n",
    "\n",
    "# Remove title\n",
    "x.set_title(\"\")\n",
    "\n",
    "# Set x-axis label\n",
    "x.set_xlabel(\"Месяц\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "# Set y-axis label\n",
    "x.set_ylabel(\"Новые юзеры\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "# Format y-axis label\n",
    "x.yaxis.set_major_formatter(StrMethodFormatter('{x:,g}'))"
   ]
  }
 ],
 "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",
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