5-6.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 例5-6. ビンカウンティングの例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8208, 24)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "# train_subsetを読み込み(サンプルコードの対象のデータ件数が、8208件です。)\n",
    "df = pd.read_csv('data/avazu/train_subset.csv')\n",
    "\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "906"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# device_idが何種類あるか計算\n",
    "len(df['device_id'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "  </tbody>\n",
       "</table>\n",
       "<p>906 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         clicks no_clicks  total_clicks        N+        N-    log_N+\n",
       "a99f214a   1279      5878          7157  0.178706  0.821294  0.217591\n",
       "c357dbff      2        12            14  0.142857  0.857143  0.166667\n",
       "25635c83      2         0             2  1.000000  0.000000       inf\n",
       "e62f1261      2         1             3  0.666667  0.333333  2.000000\n",
       "135f7d9a      2         0             2  1.000000  0.000000       inf\n",
       "9af87478      2         0             2  1.000000  0.000000       inf\n",
       "77cf1a27      1         0             1  1.000000  0.000000       inf\n",
       "d62216cc      1         0             1  1.000000  0.000000       inf\n",
       "fcc5c7c0      1         0             1  1.000000  0.000000       inf\n",
       "7181509e      1         0             1  1.000000  0.000000       inf\n",
       "2a32a3ca      1         0             1  1.000000  0.000000       inf\n",
       "2ad16ba3      1         0             1  1.000000  0.000000       inf\n",
       "938f494b      1         0             1  1.000000  0.000000       inf\n",
       "24dbae83      1         0             1  1.000000  0.000000       inf\n",
       "ca9b95aa      1         0             1  1.000000  0.000000       inf\n",
       "7c369899      1         0             1  1.000000  0.000000       inf\n",
       "3bf8c26c      1         0             1  1.000000  0.000000       inf\n",
       "45378128      1         0             1  1.000000  0.000000       inf\n",
       "023ca1f9      1         0             1  1.000000  0.000000       inf\n",
       "3b9ab74d      1         0             1  1.000000  0.000000       inf\n",
       "9eb9a972      1         0             1  1.000000  0.000000       inf\n",
       "59bcd1ae      1         0             1  1.000000  0.000000       inf\n",
       "7f8c00b4      1         0             1  1.000000  0.000000       inf\n",
       "8d61d7eb      1         0             1  1.000000  0.000000       inf\n",
       "b441c41f      1         0             1  1.000000  0.000000       inf\n",
       "e317838f      1         0             1  1.000000  0.000000       inf\n",
       "2e7d4b65      1         0             1  1.000000  0.000000       inf\n",
       "70d97ece      1         0             1  1.000000  0.000000       inf\n",
       "9809e6c9      1         0             1  1.000000  0.000000       inf\n",
       "cb73ba55      1         0             1  1.000000  0.000000       inf\n",
       "...         ...       ...           ...       ...       ...       ...\n",
       "0c3bbac0      0         1             1  0.000000  1.000000  0.000000\n",
       "34c9f908      0         1             1  0.000000  1.000000  0.000000\n",
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       "1168ce02      0         1             1  0.000000  1.000000  0.000000\n",
       "83c34e93      0         1             1  0.000000  1.000000  0.000000\n",
       "c8c31032      0         1             1  0.000000  1.000000  0.000000\n",
       "004270bf      0         1             1  0.000000  1.000000  0.000000\n",
       "e6d0facc      0         1             1  0.000000  1.000000  0.000000\n",
       "844524dc      0         1             1  0.000000  1.000000  0.000000\n",
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       "5015495b      0         1             1  0.000000  1.000000  0.000000\n",
       "a12e8a45      0         1             1  0.000000  1.000000  0.000000\n",
       "7b5c2c3b      0         1             1  0.000000  1.000000  0.000000\n",
       "4a6b5af3      0         1             1  0.000000  1.000000  0.000000\n",
       "2c8ae68c      0         1             1  0.000000  1.000000  0.000000\n",
       "84565c92      0         1             1  0.000000  1.000000  0.000000\n",
       "2a6fe2a5      0         1             1  0.000000  1.000000  0.000000\n",
       "e0f70006      0         1             1  0.000000  1.000000  0.000000\n",
       "cef4c8cc      0         1             1  0.000000  1.000000  0.000000\n",
       "7f4b1f1e      0         1             1  0.000000  1.000000  0.000000\n",
       "7efe14f0      0         1             1  0.000000  1.000000  0.000000\n",
       "02b99e77      0         1             1  0.000000  1.000000  0.000000\n",
       "cbb50c1c      0         1             1  0.000000  1.000000  0.000000\n",
       "\n",
       "[906 rows x 6 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def click_counting(x, bin_column):\n",
    "    clicks = pd.Series(x[x['click'] > 0][bin_column].value_counts(), name='clicks')\n",
    "    no_clicks = pd.Series(x[x['click'] < 1][bin_column].value_counts(), name='no_clicks')\n",
    "\n",
    "    counts = pd.DataFrame([clicks,no_clicks]).T.fillna('0')\n",
    "    counts['total_clicks'] = counts['clicks'].astype('int64') + counts['no_clicks'].astype('int64')\n",
    "    return counts\n",
    "\n",
    "def bin_counting(counts):\n",
    "    counts['N+'] = counts['clicks'].astype('int64').divide(counts['total_clicks'].astype('int64'))\n",
    "    counts['N-'] = counts['no_clicks'].astype('int64').divide(counts['total_clicks'].astype('int64'))\n",
    "    counts['log_N+'] = counts['N+'].divide(counts['N-'])\n",
    "    # Bin Countingのプロパティを返すだけの場合、ここでフィルタリングを実行\n",
    "    bin_counts = counts.filter(items= ['N+', 'N-', 'log_N+'])\n",
    "    return counts, bin_counts\n",
    "\n",
    "# device_idを対象としたビンカウンティング\n",
    "bin_column = 'device_id'\n",
    "device_clicks = click_counting(df.filter(items=[bin_column, 'click']), bin_column)\n",
    "device_all, device_bin_counts = bin_counting(device_clicks)\n",
    "\n",
    "device_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "    <tr>\n",
       "      <th>7f4b1f1e</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7efe14f0</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02b99e77</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cbb50c1c</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>906 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                N+        N-    log_N+\n",
       "a99f214a  0.178706  0.821294  0.217591\n",
       "c357dbff  0.142857  0.857143  0.166667\n",
       "25635c83  1.000000  0.000000       inf\n",
       "e62f1261  0.666667  0.333333  2.000000\n",
       "135f7d9a  1.000000  0.000000       inf\n",
       "9af87478  1.000000  0.000000       inf\n",
       "77cf1a27  1.000000  0.000000       inf\n",
       "d62216cc  1.000000  0.000000       inf\n",
       "fcc5c7c0  1.000000  0.000000       inf\n",
       "7181509e  1.000000  0.000000       inf\n",
       "2a32a3ca  1.000000  0.000000       inf\n",
       "2ad16ba3  1.000000  0.000000       inf\n",
       "938f494b  1.000000  0.000000       inf\n",
       "24dbae83  1.000000  0.000000       inf\n",
       "ca9b95aa  1.000000  0.000000       inf\n",
       "7c369899  1.000000  0.000000       inf\n",
       "3bf8c26c  1.000000  0.000000       inf\n",
       "45378128  1.000000  0.000000       inf\n",
       "023ca1f9  1.000000  0.000000       inf\n",
       "3b9ab74d  1.000000  0.000000       inf\n",
       "9eb9a972  1.000000  0.000000       inf\n",
       "59bcd1ae  1.000000  0.000000       inf\n",
       "7f8c00b4  1.000000  0.000000       inf\n",
       "8d61d7eb  1.000000  0.000000       inf\n",
       "b441c41f  1.000000  0.000000       inf\n",
       "e317838f  1.000000  0.000000       inf\n",
       "2e7d4b65  1.000000  0.000000       inf\n",
       "70d97ece  1.000000  0.000000       inf\n",
       "9809e6c9  1.000000  0.000000       inf\n",
       "cb73ba55  1.000000  0.000000       inf\n",
       "...            ...       ...       ...\n",
       "0c3bbac0  0.000000  1.000000  0.000000\n",
       "34c9f908  0.000000  1.000000  0.000000\n",
       "41a1ae5f  0.000000  1.000000  0.000000\n",
       "5d03585e  0.000000  1.000000  0.000000\n",
       "7d242dfd  0.000000  1.000000  0.000000\n",
       "9ffa0563  0.000000  1.000000  0.000000\n",
       "2fd58990  0.000000  1.000000  0.000000\n",
       "01e47a3d  0.000000  1.000000  0.000000\n",
       "bcd5195e  0.000000  1.000000  0.000000\n",
       "a318236b  0.000000  1.000000  0.000000\n",
       "1168ce02  0.000000  1.000000  0.000000\n",
       "83c34e93  0.000000  1.000000  0.000000\n",
       "c8c31032  0.000000  1.000000  0.000000\n",
       "004270bf  0.000000  1.000000  0.000000\n",
       "e6d0facc  0.000000  1.000000  0.000000\n",
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       "c90a30a1  0.000000  1.000000  0.000000\n",
       "5015495b  0.000000  1.000000  0.000000\n",
       "a12e8a45  0.000000  1.000000  0.000000\n",
       "7b5c2c3b  0.000000  1.000000  0.000000\n",
       "4a6b5af3  0.000000  1.000000  0.000000\n",
       "2c8ae68c  0.000000  1.000000  0.000000\n",
       "84565c92  0.000000  1.000000  0.000000\n",
       "2a6fe2a5  0.000000  1.000000  0.000000\n",
       "e0f70006  0.000000  1.000000  0.000000\n",
       "cef4c8cc  0.000000  1.000000  0.000000\n",
       "7f4b1f1e  0.000000  1.000000  0.000000\n",
       "7efe14f0  0.000000  1.000000  0.000000\n",
       "02b99e77  0.000000  1.000000  0.000000\n",
       "cbb50c1c  0.000000  1.000000  0.000000\n",
       "\n",
       "[906 rows x 3 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device_bin_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "906"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(device_bin_counts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>clicks</th>\n",
       "      <th>no_clicks</th>\n",
       "      <th>total_clicks</th>\n",
       "      <th>N+</th>\n",
       "      <th>N-</th>\n",
       "      <th>log_N+</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a99f214a</th>\n",
       "      <td>1279</td>\n",
       "      <td>5878</td>\n",
       "      <td>7157</td>\n",
       "      <td>0.178706</td>\n",
       "      <td>0.821294</td>\n",
       "      <td>0.217591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c357dbff</th>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         clicks no_clicks  total_clicks        N+        N-    log_N+\n",
       "a99f214a   1279      5878          7157  0.178706  0.821294  0.217591\n",
       "c357dbff      2        12            14  0.142857  0.857143  0.166667\n",
       "a167aa83      0         7             7  0.000000  1.000000  0.000000\n",
       "d2bbb640      0         6             6  0.000000  1.000000  0.000000"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device_all.sort_values(by = 'total_clicks', ascending=False).head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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