{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Icke fungerande RAÄ länkar Wikipedia -> RAÄ   \n",
    "version 1.0 \n",
    "\n",
    "* Denna [Notebook](https://github.com/salgo60/open-data-examples/blob/master/Icke%20fungerande%20RA%C3%84%20l%C3%A4nkar.ipynb)\n",
    "\n",
    "* Larske tog fram en lista som en python snutt kollade igenom\n",
    "  * Larske lista i [Quarry](https://quarry.wmflabs.org/query/46216) = 164141 länkar kulturarvsdata \n",
    "* [Python kod](https://gist.github.com/salgo60/f33116056e2698186b9ee424626246fd) som om länken skickar fel status <> 200 --> länkröta i Wikipedia och länkas skall bort \n",
    "  * Filer som inte gav [http Status 200](https://raw.githubusercontent.com/salgo60/open-data-examples/master/data/RA%C3%84files20200630.txt) = 7602 unika filnamn\n",
    "* Förklaring [Abbe98 på Bybrunnen](https://sv.wikipedia.org/wiki/Wikipedia:Bybrunnen#K-sams%C3%B6k_anv%C3%A4nds_det?_N%C3%A5gon_som_lyckats_felrapportera) som kan ge ledtråd vad som skall städas eller ej  \n",
    "  * svårt att förstå om/vad RAÄ gör\n",
    "  * RAÄ feedback [Wikipedia vissa delar fixade](https://sv.wikipedia.org/wiki/Malldiskussion:BBR-l%C3%A4nk#BeBR_410-poster_tillbaka)\n",
    "  * [GIST](https://gist.github.com/salgo60/f33116056e2698186b9ee424626246fd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7602\n"
     ]
    }
   ],
   "source": [
    "import urllib3, json  \n",
    "import pandas as pd\n",
    "nonWorkingfiles = \"https://raw.githubusercontent.com/salgo60/open-data-examples/master/data/RA%C3%84files20200630.txt\"\n",
    " \n",
    "http = urllib3.PoolManager()\n",
    "r1 = http.request('GET', nonWorkingfiles) \n",
    "files = r1.data.decode('utf-8').split(\"\\n\")   \n",
    "print(len(files))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7602 entries, 0 to 7601\n",
      "Data columns (total 1 columns):\n",
      "Line    7602 non-null object\n",
      "dtypes: object(1)\n",
      "memory usage: 59.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df=pd.DataFrame(files,columns=[\"Line\"])  \n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option(\"display.max.rows\", None)   \n",
    "pd.set_option(\"display.max.columns\", None) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfsplit = df.Line.str.split(\"\\t\",n=0,expand = True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7602 entries, 0 to 7601\n",
      "Data columns (total 2 columns):\n",
      "0    7602 non-null object\n",
      "1    7602 non-null object\n",
      "dtypes: object(2)\n",
      "memory usage: 118.9+ KB\n"
     ]
    }
   ],
   "source": [
    "dfsplit.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Status:  410</td>\n",
       "      <td>http://kulturarvsdata.se/BHM/media/html/BM_UM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Status:  410</td>\n",
       "      <td>http://kulturarvsdata.se/BHM/media/html/BM_UM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Status:  410</td>\n",
       "      <td>http://kulturarvsdata.se/BHM/media/html/BM_UM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Status:  410</td>\n",
       "      <td>http://kulturarvsdata.se/BHM/media/html/BM_UM...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Status:  410</td>\n",
       "      <td>http://kulturarvsdata.se/BHM/media/html/BM_UM...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                0                                                  1\n",
       "0  Status:  410     http://kulturarvsdata.se/BHM/media/html/BM_UM...\n",
       "1  Status:  410     http://kulturarvsdata.se/BHM/media/html/BM_UM...\n",
       "2  Status:  410     http://kulturarvsdata.se/BHM/media/html/BM_UM...\n",
       "3  Status:  410     http://kulturarvsdata.se/BHM/media/html/BM_UM...\n",
       "4  Status:  410     http://kulturarvsdata.se/BHM/media/html/BM_UM..."
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfsplit.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Status:  410      7479\n",
       "Status:  404       122\n",
       "Status:  400         1\n",
       "Name: 0, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfsplit[0].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline  \n",
    "import matplotlib.pyplot as plt \n",
    "dfsplit[0].value_counts().plot.pie()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Enligt Bybrunnen Abbe98 finns det en logik i felen och tolkas enligt nedan\n",
    "* 410 = 7479 poster skall tolkas som borttagen är att RAÄ har problem med upphovsrätt\n",
    "* 404 = 122 poster finns inte  \n",
    "* 400 = 1 ???   \n",
    "\n",
    "Normal tolkning \n",
    "\n",
    "404: ”Den begärda resursen hittades inte.” Det vanligaste felmeddelandet av dem alla. Denna kod betyder att den begärda resursen inte existerar och att servern inte vet om den någonsin existerade.\n",
    "\n",
    "410: ”Den begärda resursen är borta och kommer inte att komma tillbaka.” Liknande en 404 ”sidan finns inte” -kod, förutom att en 410 indikerar att tillståndet är förväntat och permanent.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 7479 entries, 0 to 7599\n",
      "Data columns (total 3 columns):\n",
      "0    7479 non-null object\n",
      "1    7479 non-null object\n",
      "3    7479 non-null object\n",
      "dtypes: object(3)\n",
      "memory usage: 233.7+ KB\n"
     ]
    }
   ],
   "source": [
    "dfStatus410Flag = dfsplit[0].str.strip() == \"Status:  410\" \n",
    "dfStatus410 =  dfsplit[dfStatus410Flag]  \n",
    "dfStatus410.info()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfsplit[4].value_counts().plot.pie()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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LIohLXSEhdb2HvZ4b+7Wza7QAWIR7r/eGtXwD+ClwCO6XcC8uGAq4FlAB13r5GNAF3AP8GRATkT/gNoeIAf8G3I/bmPFs4GfAL8LHmws8rKqnisituJ7PF3BBuDwMsz8HvgKcCVwK5MP7G4CHReQ34Ws4Drf44DrgYVxIPrSvFz6kQFHVNcAHRCSFax760ouFUNnNl43Bvv6uHuovzW97+6X5bTzS1Pj81dOmbFuVSLwFkUQQk8SyA3nTsgPjb/rx6e74pj7dfmROXz1xmW47/DVtmL6NZFyZDVBf2DG1vrBj6uRtKwZ8rkDi/b2N0zZ2Nc/a3NVywI6uljnF7qaZsb6Gyc2Fuuadran9DtMQSTQiExqFCTNG2mZWLfahfdtUe7sIerpVu3tVe/oJuouq3SUNehTtEdW+GNpXp1qoR4sNu4JMJ5a02FzSYnM/PW9ome3D8vD2XOAa4JXw+w8A/bgeyc3hcd24QCoAP8aFTw8uaJ7DnU+6GfdZ/RIuOO4J//4I3GmV/2bXuSFwJ8B3frafwrWIzgkf610ickZ4fzI85l3A0SLy/vD7VlzrqR94PMwMwu5dktGG0E6qmsU1FX2x80IVcIB0Dul9cHJP75G/XLOedYn4+qunTXn5waamo1Vkj8F4PQ0y8YnD5LgndltdeVpe1x+/XFctXqZ9h67X1ok9LJABpuDEtFTf3LPpoOaeTQfN6FwyYA39dS1belxrKr9jj9bUpImleMN0kJnhafARE0k0IIkZQssogqzUj/ZtV+3LDfFHHg5vP4HrSnUCVwN/iWv9PIIbfX0zrvVzCi405uK6Pn3h1wnAY8BvcS2QM4H/BT4CvIrrdnXgukzfxLX8YrjP1s4maAnXzVsBrAVW47p7f2RXZghwharevfuLCLtjfbvdVWKQnPHZtRqJDtw/jimjGZIf1vCHA4qlOddv7JjTK9JzY+uk39/SOnF2Xyy2z8W7Oltlzj3Hy5x7jnffi2pw8AaWLV4WbDh2hXJQOzPriyyQIZzvqy90TakvrJzSum3lgH8fSKzQ2zhtXXfz7M4dLXN2hOemYr0Nk5uKiZYpQSwxC5GKz0EUidcjzdNkiA13Vf2tiHThWhgJ4ERc66IdN+p6Ae4U2jbg67iW0nzcVbGrcSFTD2zFdYfmA/cCV+ICpgvX2jkC14L6Ee6y/2244OsFSiLyHLtOdD8fPk49riW2e7jfDXxcRO4NT3a/CRdYwxa1EFqHS2RTRhPpbh3JzzWqNl2xNf+OK7bm+W1z0zNfmzalsD4eXzxYS0RFYivmsHDFnPjCW0919zX0a9ebX9Pli1/RLUeu0voZeebHdfi/cGIa1DX3tM9t7mmfO30fralCojnf3TRzY1fL7HxXywE9Xc2ztbdpWl1//aRJxXhjWVpTu2kfykEicgLuw74Adz7mBeCfgRnARar6PRF5BjhZVa8RkedxQbQGdxL7TOAPwC+Bv8GdNJ4CPK2qi0VkEi50Hg7v/yluq+qzd9agqmeEtVwJTFDVNhG5H7hSVTeLyPTdSr4J1816Ohxz1A68b5j/Nu617+ek9biTTGf/C7jEdx3VZkXDhzpjomWZaJlLJF776vSpK//Q2HAc7o0/YlO266bjluvKxcu0d+E6nTipmwWy5/iXiggkVuxtmLqxu3l2Z1fLnB1dLXMK3c0zY70NU5qKiebJQaxuFu7y9lB86fIbznjDKOa9icingWmq+uXw+6twH+wrVXVeeN8ZwKdU9X07wwGYjeuirQkfqh54FNfVukFV377X83wEWKyqnxxi/RUXxZaQKaM6iv2Clm2SZbJYnHfThk3zukR2XD+l9YGfTpo4vyCSHMljbZkoM+89Vmbeu3OnOVWdv4nli5fp+uOWBzqvnekNBRZKmd/HMQ0Szb0dBzb3dhw4ffPzAx5TSDRt63Gtqa07mg/o6W6ZrT2N0+v66ydNLCUapimxWbjL2KN9z+7dStj7ewHuUdUP7nGnyFGjfN4xE7UQGlGf0+zbbNncLvL6uJGyaVGd8LnNW0/7u81b9c4JzU9cO2VKrCMRP2FUDyoiq2Zx6KpZcuhtp7jeUn1Bew5frUsXv6Kbj1qldTO3Mi8RMLccr2F/6oo9k+q2r5o0afuqAf9ekVJv49R1fQ2ty3eNIdyv3wM3i0gGFyznAh8GrhORt6nqo7gRzXtfZXoM+HcRWaCqr4q7enggbgT2HBE5UVWfCAcm9gDb2XUCelyIWghZS6jM5smmrVD+ENpJQM7Z0X3iOTu6eam+bvlV06au/WND/eK9By6OVH+dND13iBz13CG77mvdoe3HrtDc4mXa9aa1OnFyFwvEneQdM4LGm3o7D2jq7Rz0F6e4luL3gO8Cj4d33wRswYXJ5SLyXdzshf/c7UcVN9bnauDH4XgdgC+q6ivh/LF/E5EmXACdCdwHpMNL59eo6k9H90pHL2ohtHzwQ8xwzJcN28fquRb1Fw794fqNh+Zjsa3XTpn8xO0TWw4tiZS91ZKfIDMeOFpmPLDzEoaqzu1g5eJluu645UEpuYnpjf0skAFGV5dZERi4qTQAVf0GbmDi7hbt4/BpuCkeAE+q6g0DPN4TuJPPeztxqDWNhaiF0Mu4wVCVfvPUjIMHGC1daa1BMLmtc/NpX+rcXPr5xAmP/duU1qZ8PH5MxZ5QRNbM4OA1M+Tg20923bhEUfsWrdEXTnxFO47Kad3sLRyYCJhf5mdecfhLSwvDLPUQ3GXzH+HG+bTgBgH+C+59/2HcTsS/VdWV4WT4D4vITbjP8yWq+vhAjz1eRSqEwvljL2GX6ctmf6OlKy0O8fO27zjpvO07eK6h/uWrpk1tf7m+7kR2dSsqppiQhueT8ubnk7vum9itm49ZoSsWL9Mdi9bohMk7OCQ2upURlw5+yC4ichjwE9yYn+Nwc6+Ow02deBX4nKoeJyLXsmcLq1lVjw1nyX83/LnIiFQIhZZgIVQ2B0jnuJgQfExf/2E/X7fhsI54rP1rU6e8cHdL8+GByJju2bW9WaY+dKRMfWi3j/ABnbrqhGW69vjlWkhu1GnNfSyUoc8tG/jS2sBm4NYF+n+q+qKIHAfcp6rbge0ikgfuDI/d+zPwYwBVfVBEJonIZFXdOozn9iqqIWTKZIZsbfJdw+6ml4IZX3MTZws/aJ348Lcnt07uisXe7KueddNk/rppMv/O8MxKvKSFN63lxRNfCTqOzml8zmYOSJRIiruitbfnhvFUeeA13HSMF8P7dp/+EOz2fcCen93BLuOPaxZCNW4i3ePqcu1OdVB3cX772y/Ob+exxobn/2na1G25Ojdx1mddpbjULZ3HEUvn7WpAtvRo/piVunzxMt22aLW2TN1BMqbMAJ4cxkP34y7L3z2CBerPA+4TkVNwM9vzw/x5r6IYQk/5LqCaNFIY91vSnNTbd+Sda9ezPu4mzj7Q3HSUioyburuapPWRI+T4R47Ydd8Bnfrs3X/z/MAT3PZBVbtE5D24Ge/fH8aP9oZTOuqI4IyCSE3b2Ck8OX3YoAea/UpQLCxruDDhljeNjj6h98bW1iduHmTirGe3L7loybm+i4iCqO5ecZ/vAqrBbNnSEbUAAmhQGj+5Nf+OJ1etWXjdxvZnDygU/4BbgG88eXjwQwxEN4Tu911ANZgrmzYPftT4dkZ3z7F3r1n31l+uWb/2pJ7eBxg/50MshIbIQqiGHSwbunzXUC7zi8WDbtyw6bTHVq2JX5jf9mCd6rDOx5RZN3bucsgiGUK5TGoj8JLvOqIuKRuqbqXKFtUJn9289dSncquT12zqeHJ6sfQUY3/i854lFy0Z85HoURXJEArd47uAqJsvG6N3VWKIBOQ9Xd2L71u99oSfr92w8tjevgdRHauW352DH2J2inII3e67gKg7UDqi/P8/ZIcVCod8f/3GUx96bU3x/du2PxAPF2GvEGWM12EPt4VeHP75Vzs3J42KKL8JH2TXLGIzAjMkP65GS1daa6CtX+ncctpTudVzvtSx+bHWUunZCjzN40suWrJh8MMqQ1X/PEpTNiDCIZTLpIq4uTZmhCaN09HSlRaH+F9u33HSQ6+tPfaH6za8vKiv/yFUy3V+7NahHBTu/f6SiNwsIq+IyA9F5EwReVhElonIW0SkRUS+KyKPi8gzIvLe8GebROQnIrJURP4Xt3b0zsfN7VwLWkRuF5GnROQFEflomV5f2UVxxPTufgpc7LuIqGqkf9yMOvbl6L7+w362bsNhnbFYx9enTXns1y3NiwKR2SN8uJ2LjA3VAty+YpfgNjM8Hzd37BzcxoMvAveq6iVhF+txEfkt8NdAt6oeLiJHA0/v4/EvCReobwKeEJHbVLVzRK+sgiLbEgr9jiHuZmD2FKdUFMqzuH01mBYE0zPtnac/mVs97W87tzzSEgQvjOBhHl1y0ZLVwzh+paouCXc6fgH4Xbhd8hLcThbvYtcqiPfjlvSYB5wK/ABAVf+I2w9sIJ8Kt/B5DDgIty7RuBPpEAq7ZD/xXUcUzWZzJEdLV1od1H1k2/aTH1u15s03rd/4wsH9hUdQHerCZMN9Lw42S16Av1DVY8Oveao6pDWKwk0IzwTepqrHAM/gQmzciXQIhd6wrKUZ3Fxpt5P6g3hrb9+bf7F2/cn3rF7X+c6u7gdEtWM/h/cQtk7K6G7ginBfL8I1hsBdlDk/vO9IBl5fqxXYoqrdIrKIgZd5HRciH0K5TOpF4AHfdURNMrZhuMtF1KzZpdLsb23qOO2JVasnfGLL1ocag+DlAQ77yZKLlmwp81NfhZsZ/0cReSH8Htxi9xNEZCnwjww8OvsuIBEek8F1ycalSM6i31synT0P65YNSzrxowc/lvjlqb7riKr7m5uezUyd0rs2EX9LuFvr4iUXLbGpGiMQ9atjO/0PsBEY0+VAo6yaR0uPhdO7e449vbuH1xKJNV+bOvm+6z+x3AJohCLfHQPIZVIF3D5NZohqZbR0pc0rFudev6njV77riLJqeiP+O1B1EzIrZYZsHZdXSiLoNeDnvouIsqoJoVwmtR640XcdUdFao6OlK+A62vJF30VEWdWEUCjDnmMvzD402GjpctiADREZtaoKoVwmtQ5rDQ0qRlCK2WjpcriKtny37yKirqpCKHQN1hrar9lsbhepyv/7sbQc+4VXFlX3RgxbQ9/2Xcd4ZqOly+LLtOWHtc+8GVjVhVDoH7G1hvbJRkuP2nOEWy+b0avKEMplUp3A3/uuY7w6uArXlh5jn6ctb4M9y6QqQyj0HdzMYbMXGy09KnfQlv+17yKqSdWGUC6TCoBP4haaMrux0dIjth33njJlVNVvxlwm9QjD29O7Jsy00dIj9Xna8pVcJL8mVXUIha7ETW41oUl0TfBdQwQ9iltCw5RZ1YdQLpNqBy7zXcd4YmtLD1s/cBlt+fG2331VqPoQAshlUndis+yB10dLT/ddR8RcQ1t+JGtOmyGoiRAKfQZY4bsI32axpcNGSw/Lg+xa0dBUQM28GXOZ1A7gw0DJdy0+2WjpYdkEfJC2fE2/ZyqtZkIIXr9a9g++6/DJRksPWQBcQFt+ne9Cql1NhVDoq8D/+i7Cl6SNlh6qq2nL3+O7iFpQcyGUy6QUuBC32VzNScpGu8IzuPuBNs811IyaCyF4/fzQe4Fyb9Ey7tlo6UGtAM6z80Bjp2bfkLlMajnwQVzfv2bYaOn96gD+jLb8Jt+F1JKaDSGAXCZ1N3C57zrGUquNlt6XHuBs2vLLfBdSa2o6hABymdQN1NCyH430TfVdwzgU4C7Fj9tdSqtZzYcQQC6Tuhr4F991VJoQBDZaekBX0Ja/w3cRtcpCKJTLpD4L/JfvOippJls7RIj7rmOc+TJt+f/wXUQtsxDa00eBW30XUSkHSXun7xrGmc/SlrcpGZ5ZCO0mXAjtfOC7vmupBBst/TrFdcGqvgseBRZCe8llUqVcJnUpVXiOyEZLA+4k9Edpy1/vuxDjWAjtQ3iO6Au+6ygnGy1NCfgIbXlb1mUcsRDaj1wmdQ3wMapkQOOB0i6+a/AoD7yHtrwt9zvOWAgNIpdJfRs4B9jmu5bRquHR0suAk2jL3+W7EPNGFkJDkMukssBJwKu+axmNGh0tfQ/wVtryL/kuxAzMQj5WLYgAAASeSURBVGiIcpnUUuBE4Je+axmpJvprbbT0t4CzaMvX3ETlKLEQGoZcJrUV1zX7MhE7T+RGSwczfNcxRnYAF9OW/7TNhh//RNX2BhyJZDp7CnALcIjvWoZiJpvbH2/8ZC2E0CPAh2nL1/x64lFhLaERymVSDwHHADf6rmUo5kpHtY+WLgBfBE61AIqWhO8CoixcHO2jyXT2DtyWQrM9l7RPSdmw3XcNFfQy8CHa8k/5LsQMn7WEyiC8enYUbsvpcdm/PThWlaOlC8DXgeMtgKLLWkJlksukOoALk+nsDcD1wHGeS9rD/OobLf0A8Ana8i/6LsSMjrWEyizcVmgxbqR1h+dyXje3ekZLrwL+irb86RZA1cFCqAJymVQQjrR+E26sSp/nkqphtPQ23InnRbTlf+q7GFM+dol+DCTT2QOBzwGXAV7C4PmGS16cIL1H+HjuUdoCXAd8ywYdVicLoTGUTGfn4MLoo0DTWD738oYLNsQlGLdX7wbQDvwr8B+05Yd0ZU9EksAvVfXIve7PAYtVddx0j80uFkIeJNPZWcCngEuBWZV+PiEIVjRcEIhE4kLEauAbwHdoy3cP5wdHE0IiklDV4rCrNaNmIeRRMp2tA84FPg6cXqnnmcGWjicaLx/PC9wXcHPybgTupi0/oit5YQjdBTwFHI/bZfdC4EXcsr1n4bb2OV9VXxWRm4Fe3JXMh4Gf4Lp+jeFxF6vqyyN9UWZoovCbsWrlMqkC7sNxazKdXYS7onY+UNbpFeFo6fEYQq/gNhe4hbb8xjI95mHApar6sIh8F/hEeH9eVY8SkQuBbwLvCe+fC5ysqiURmQS8Q1WLInImcDXwF2Wqy+yDhdA4kcukXgL+fzKd/VvgVOD9uFbSnNE+9jgbLf0qcCfwP7TlH6rA469W1YfDP/8A1+0F+PFut9fudvzPVHXnJNdW4BYRWYgbdFpXgfrMXiyExplcJlUC7gPuS6azVwAn434b/xmwaCSPmYxt6ClfhcMWAI/igucXtOWXVvj59j6/oAPcv/ufu3b781XAfap6bti1u7/cxZk3shAax8LdPx4Kvz4TntA+DXf+6HTg8KE8TlI2jOVo6X7gGeAxXPjcS1u+fQyff56IvE1VH8V1bR/CnfM5D8iEt4/u42dbgbXhnz9S4TpNyEIoQnKZ1EbCc0gAyXR2Jm6htSPDr6NwraWG3X9urnRUarR0N7Acd+L3D7gP9zO05X0OznwZuDw8H/Qi8J/AFcAUEfkjbuDoB/fxs1/Ddce+CGTHolhjV8eqTjKdTQALcaO1DwIOuqP+i4ljYiuOBmbiTno348537Pza2w7cwvB5YGt4uxlYiQudV4HltOXXV/bVmFpgIWSgrTWBC6ME0G2rEZqxZCFkjPHKJrAaY7yyEDLGeGUhZIzxykLIGOOVhZAxxisLIWOMVxZCxhivLISMMV5ZCBljvLIQMsZ4ZSFkjPHKQsgY45WFkDHGKwshY4xXFkLGGK8shIwxXlkIGWO8shAyxnhlIWSM8cpCyBjjlYWQMcYrCyFjjFcWQsYYryyEjDFeWQgZY7yyEDLGeGUhZIzx6v8ANcf6r6kWCqIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfsplit[4].value_counts()[1:10].plot.pie()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfsplit[4].value_counts()[2:].plot.pie()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}