market-basket.ipynb

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   "source": [
    "import pandas as pd\n",
    "from math import floor"
   ]
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   "source": [
    "asc = pd.read_csv('../input/market-basket-id-ndsc-2020/association_order.csv')\n",
    "rules = pd.read_csv('../input/market-basket-id-ndsc-2020/rules.csv')"
   ]
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    {
     "data": {
      "text/plain": [
       "itemid\n",
       "103572                                         {31347710941008}\n",
       "103580                                         {31338334007720}\n",
       "108696                                         {31372952019978}\n",
       "240094                                         {31380092284102}\n",
       "262532                         {31362741095032, 31379924542443}\n",
       "                                    ...                        \n",
       "7913347922                                     {31379086992486}\n",
       "7913352481                                     {31381524211086}\n",
       "7913353011                                     {31383656670416}\n",
       "7913354218                                     {31383649454865}\n",
       "7913354409    {31384651230530, 31383918929283, 3138366764822...\n",
       "Name: orderid, Length: 239702, dtype: object"
      ]
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   "source": [
    "group_itemid = asc.groupby('itemid')['orderid'].apply(lambda x: set(x))\n",
    "group_itemid"
   ]
  },
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     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rule</th>\n",
       "      <th>item</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100242812&gt;80361758</td>\n",
       "      <td>[[100242812], [80361758]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100242812&gt;89031406</td>\n",
       "      <td>[[100242812], [89031406]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003153762&gt;1016449477</td>\n",
       "      <td>[[1003153762], [1016449477]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1006024995&gt;2727415265</td>\n",
       "      <td>[[1006024995], [2727415265]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1006024995&gt;866012366</td>\n",
       "      <td>[[1006024995], [866012366]]</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "                    rule                          item\n",
       "0     100242812>80361758     [[100242812], [80361758]]\n",
       "1     100242812>89031406     [[100242812], [89031406]]\n",
       "2  1003153762>1016449477  [[1003153762], [1016449477]]\n",
       "3  1006024995>2727415265  [[1006024995], [2727415265]]\n",
       "4   1006024995>866012366   [[1006024995], [866012366]]"
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   "source": [
    "rules['item'] = rules['rule'].apply(lambda x: [i.split('&') for i in x.split('>')])\n",
    "rules.head()"
   ]
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   "outputs": [],
   "source": [
    "def confidence(data):\n",
    "    awal = set(group_itemid[int(data[0][0])])\n",
    "    if len(data[0]) > 1:\n",
    "        awal = awal.intersection(set(group_itemid[int(data[0][1])]))\n",
    "    akhir = set(awal)\n",
    "    for i in data[1]:\n",
    "        akhir = akhir.intersection(set(group_itemid[int(i)]))\n",
    "    return floor(len(akhir)/len(awal)*1000)"
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    "rules['confidence'] = rules['item'].apply(confidence)"
   ]
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   "source": [
    "hasil = rules[['rule','confidence']]"
   ]
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   },
   "outputs": [],
   "source": [
    "hasil.to_csv('submission.csv',index=False)"
   ]
  }
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