06_통계분석_2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 06_통계분석_2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 판별분석 QDA(Quadratic Discriminant Analysis) \n",
    "- LDA는 선형 판별분석 - 07_기계학습_1에서 차원축소를 다룸\n",
    "- 여기서는 이차 판별분석으로 \"분류\"하는 예시"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T11:46:19.181223Z",
     "start_time": "2020-09-17T11:46:19.175239Z"
    }
   },
   "outputs": [],
   "source": [
    "# 데이터 생성\n",
    "import numpy as np\n",
    "X = np.array([[-1,-1], [-2,-1], [-3,-2], [1,1], [2,1], [3,2]])\n",
    "y = np.array([1,1,1,2,2,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T11:46:23.786148Z",
     "start_time": "2020-09-17T11:46:21.019885Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "QuadraticDiscriminantAnalysis(priors=None, reg_param=0.0,\n",
       "                              store_covariance=False, tol=0.0001)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis\n",
    "clf2 = QuadraticDiscriminantAnalysis()\n",
    "clf2.fit(X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T11:46:24.801421Z",
     "start_time": "2020-09-17T11:46:24.795438Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf2.predict([[-0.8,-1]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 다차원척도법 MDS - 계량적(구간척도, 비율척도)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T12:49:28.655762Z",
     "start_time": "2020-09-17T12:49:28.537095Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1797, 64)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.datasets import load_digits\n",
    "X, _ = load_digits(return_X_y=True)\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T12:49:28.666721Z",
     "start_time": "2020-09-17T12:49:28.658747Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  0.,  5., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ..., 10.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ..., 16.,  9.,  0.],\n",
       "       ...,\n",
       "       [ 0.,  0.,  1., ...,  6.,  0.,  0.],\n",
       "       [ 0.,  0.,  2., ..., 12.,  0.,  0.],\n",
       "       [ 0.,  0., 10., ..., 12.,  1.,  0.]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T12:49:29.083607Z",
     "start_time": "2020-09-17T12:49:28.669714Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 2)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.manifold import MDS\n",
    "mds = MDS(n_components=2)\n",
    "X_transformed = mds.fit_transform(X[:100])\n",
    "X_transformed.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T12:49:29.095579Z",
     "start_time": "2020-09-17T12:49:29.087597Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 11.11239257,  28.49680269],\n",
       "       [  6.36983387, -20.64867765],\n",
       "       [ 16.55445425, -28.66577144],\n",
       "       [-15.10684346,  23.71246291],\n",
       "       [ 35.91298301, -18.21678131]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_transformed[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 다차원척도법 MDS - 비계량적(순서척도)\n",
    "- Metric = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T13:02:22.842543Z",
     "start_time": "2020-09-17T13:02:22.803648Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 2)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.manifold import MDS\n",
    "nmds = MDS(n_components=2, metric=False) # 이거 차이\n",
    "X_transformed = nmds.fit_transform(X[:100])\n",
    "X_transformed.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T13:02:26.392041Z",
     "start_time": "2020-09-17T13:02:26.386087Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.08422334, -0.1115282 ],\n",
       "       [-0.22082   ,  0.40054218],\n",
       "       [-0.27584893,  0.28528715],\n",
       "       [-0.3236553 ,  0.31823446],\n",
       "       [ 0.20126871, -0.26102463]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_transformed[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 대응분석\n",
    "- 카이제곱 검정은 두 범주형 변수과 의 연관성 여부를 결정하는 것이며, 구체적으로 두 변수가 가지고 있는 범주들 사이의 관계를 살펴볼 수는 없다. 이러한 문제점을 해결해 주는 통계적 기법이 대응분석이다. \n",
    "- 대응분석은 두 개 이상의 범주 군 사이의 상관성을 분석하는 기법이라 할 수 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T13:13:15.442257Z",
     "start_time": "2020-09-17T13:13:15.415324Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.cross_decomposition import CCA\n",
    "X = [[0., 0., 1.], [1.,0.,0.], [2.,2.,2.], [3.,5.,4.]]\n",
    "Y = [[0.1, -0.2], [0.9, 1.1], [6.2, 5.9], [11.9, 12.3]]\n",
    "cca = CCA(n_components=1)\n",
    "cca.fit(X, Y)\n",
    "\n",
    "X_c, Y_c = cca.transform(X, Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T13:13:33.502918Z",
     "start_time": "2020-09-17T13:13:33.496912Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1.3373174 ],\n",
       "       [-1.10847164],\n",
       "       [ 0.40763151],\n",
       "       [ 2.03815753]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T13:13:44.764760Z",
     "start_time": "2020-09-17T13:13:44.758778Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.85511537],\n",
       "       [-0.70878547],\n",
       "       [ 0.26065014],\n",
       "       [ 1.3032507 ]])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y_c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T13:29:09.411103Z",
     "start_time": "2020-09-17T13:29:09.404123Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[14.04112465, 14.35630774]])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test = [[2,4,5]]\n",
    "Y_test = [[0.4, 5,5]]\n",
    "cca.predict(X_test, Y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 시계열 분석 - fbprophet\n",
    "- prophet은 페이스북에서 개발한 시계열 예측 패키지다. ARIMA와 같은 확률론적이고 이론적인 모형이 아니라 몇가지 경험적 규칙(heuristic rule)을 사용하는 단순 회귀모형이지만 단기적 예측에서는 큰 문제 없이 사용할 수 있다."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T14:50:09.574596Z",
     "start_time": "2020-09-17T14:50:08.777728Z"
    }
   },
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2900</th>\n",
       "      <td>2016-01-16</td>\n",
       "      <td>7.817223</td>\n",
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       "      <th>2901</th>\n",
       "      <td>2016-01-17</td>\n",
       "      <td>9.273878</td>\n",
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       "    <tr>\n",
       "      <th>2902</th>\n",
       "      <td>2016-01-18</td>\n",
       "      <td>10.333775</td>\n",
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       "    <tr>\n",
       "      <th>2903</th>\n",
       "      <td>2016-01-19</td>\n",
       "      <td>9.125871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2904</th>\n",
       "      <td>2016-01-20</td>\n",
       "      <td>8.891374</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "              ds          y\n",
       "2900  2016-01-16   7.817223\n",
       "2901  2016-01-17   9.273878\n",
       "2902  2016-01-18  10.333775\n",
       "2903  2016-01-19   9.125871\n",
       "2904  2016-01-20   8.891374"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "url = \"https://raw.githubusercontent.com/facebook/prophet/master/examples/example_wp_log_peyton_manning.csv\"\n",
    "df = pd.read_csv(url)\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T14:50:17.762725Z",
     "start_time": "2020-09-17T14:50:09.603520Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:numexpr.utils:NumExpr defaulting to 4 threads.\n",
      "INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x1ec2c8e2308>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from fbprophet import Prophet\n",
    "m = Prophet()\n",
    "m.fit(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T14:50:22.821158Z",
     "start_time": "2020-09-17T14:50:22.810187Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3265</th>\n",
       "      <td>2017-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3266</th>\n",
       "      <td>2017-01-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3267</th>\n",
       "      <td>2017-01-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3268</th>\n",
       "      <td>2017-01-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3269</th>\n",
       "      <td>2017-01-19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ds\n",
       "3265 2017-01-15\n",
       "3266 2017-01-16\n",
       "3267 2017-01-17\n",
       "3268 2017-01-18\n",
       "3269 2017-01-19"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "future = m.make_future_dataframe(periods=365)\n",
    "future.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- yhat이 예측값"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T14:50:37.487918Z",
     "start_time": "2020-09-17T14:50:33.961353Z"
    }
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>yhat</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3265</th>\n",
       "      <td>2017-01-15</td>\n",
       "      <td>8.203217</td>\n",
       "      <td>7.465164</td>\n",
       "      <td>8.969418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3266</th>\n",
       "      <td>2017-01-16</td>\n",
       "      <td>8.528203</td>\n",
       "      <td>7.758541</td>\n",
       "      <td>9.264207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3267</th>\n",
       "      <td>2017-01-17</td>\n",
       "      <td>8.315601</td>\n",
       "      <td>7.668485</td>\n",
       "      <td>9.087909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3268</th>\n",
       "      <td>2017-01-18</td>\n",
       "      <td>8.148207</td>\n",
       "      <td>7.397069</td>\n",
       "      <td>8.896107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3269</th>\n",
       "      <td>2017-01-19</td>\n",
       "      <td>8.160103</td>\n",
       "      <td>7.498117</td>\n",
       "      <td>8.846597</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ds      yhat  yhat_lower  yhat_upper\n",
       "3265 2017-01-15  8.203217    7.465164    8.969418\n",
       "3266 2017-01-16  8.528203    7.758541    9.264207\n",
       "3267 2017-01-17  8.315601    7.668485    9.087909\n",
       "3268 2017-01-18  8.148207    7.397069    8.896107\n",
       "3269 2017-01-19  8.160103    7.498117    8.846597"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast = m.predict(future)\n",
    "forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T14:51:35.498720Z",
     "start_time": "2020-09-17T14:51:34.701880Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1 = m.plot(forecast)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-09-17T14:52:00.450983Z",
     "start_time": "2020-09-17T14:51:59.482556Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2 = m.plot_components(forecast)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 연관성 분석 = 장바구니분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-09T16:37:38.827804Z",
     "start_time": "2020-12-09T16:37:33.998875Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from mlxtend.preprocessing import TransactionEncoder\n",
    "from mlxtend.frequent_patterns import apriori, association_rules"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 구매한 물건이 담긴 데이터"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-09T16:37:38.856626Z",
     "start_time": "2020-12-09T16:37:38.848795Z"
    }
   },
   "outputs": [],
   "source": [
    "dataset = [['Milk', 'Onion', 'Nutmeg', 'Eggs', 'Yogurt'],\n",
    "           ['Onion', 'Nutmeg', 'Eggs', 'Yogurt'],\n",
    "           ['Milk', 'Apple', 'Eggs'],\n",
    "           ['Milk', 'Unicorn', 'Corn', 'Yogurt'],\n",
    "           ['Corn', 'Onion', 'Onion', 'Ice cream', 'Eggs']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Encoding을 해 줌 : 인스턴스 생성 -> fit -> transform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-09T16:53:51.197466Z",
     "start_time": "2020-12-09T16:53:51.192849Z"
    }
   },
   "outputs": [],
   "source": [
    "te = TransactionEncoder()\n",
    "te_ary = te.fit(dataset).transform(dataset)\n",
    "df = pd.DataFrame(te_ary, columns=te.columns_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-09T16:54:30.706611Z",
     "start_time": "2020-12-09T16:54:30.691595Z"
    }
   },
   "outputs": [],
   "source": [
    "frequent_itemsets = apriori(df, min_support=0.5, use_colnames=True)\n",
    "## parameter\n",
    "# max_len=3 : 아이템 조합이 3개까지 제한"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-09T16:54:32.106529Z",
     "start_time": "2020-12-09T16:54:32.093733Z"
    }
   },
   "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>support</th>\n",
       "      <th>itemsets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.8</td>\n",
       "      <td>(Eggs)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.6</td>\n",
       "      <td>(Milk)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.6</td>\n",
       "      <td>(Onion)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.6</td>\n",
       "      <td>(Yogurt)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.6</td>\n",
       "      <td>(Eggs, Onion)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   support       itemsets\n",
       "0      0.8         (Eggs)\n",
       "1      0.6         (Milk)\n",
       "2      0.6        (Onion)\n",
       "3      0.6       (Yogurt)\n",
       "4      0.6  (Eggs, Onion)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frequent_itemsets # 전체 구매 데이터 중 해당 itemset이 포함된 확률"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-09T16:55:31.700751Z",
     "start_time": "2020-12-09T16:55:31.673981Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>antecedents</th>\n",
       "      <th>consequents</th>\n",
       "      <th>antecedent support</th>\n",
       "      <th>consequent support</th>\n",
       "      <th>support</th>\n",
       "      <th>confidence</th>\n",
       "      <th>lift</th>\n",
       "      <th>leverage</th>\n",
       "      <th>conviction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(Eggs)</td>\n",
       "      <td>(Onion)</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.75</td>\n",
       "      <td>1.25</td>\n",
       "      <td>0.12</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(Onion)</td>\n",
       "      <td>(Eggs)</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.25</td>\n",
       "      <td>0.12</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  antecedents consequents  antecedent support  consequent support  support  \\\n",
       "0      (Eggs)     (Onion)                 0.8                 0.6      0.6   \n",
       "1     (Onion)      (Eggs)                 0.6                 0.8      0.6   \n",
       "\n",
       "   confidence  lift  leverage  conviction  \n",
       "0        0.75  1.25      0.12         1.6  \n",
       "1        1.00  1.25      0.12         inf  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "association_rules(frequent_itemsets, metric=\"lift\", min_threshold=1) # metric 기준 min_threshold 이상"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**첫 줄 해석**\n",
    "- antencedents와 consequents가 있는데 각각의 support를 보여줌. \n",
    "- 그리고 조합의 support, confidence, lift를 보여주는데 \n",
    "- confidence : Onion을 사는 고객 중 Eggs+Onion이 75%\n",
    "- lift: 1이면 서로 영향이 없는 것. 그냥 Onion을 사는 것보다 Egg를 샀을 때 구매율이 1.25배 높아진다는 소리"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 요인분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-11T02:09:30.865903Z",
     "start_time": "2020-12-11T02:09:26.387159Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_digits\n",
    "X, _ = load_digits(return_X_y=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-11T02:09:39.604318Z",
     "start_time": "2020-12-11T02:09:39.591297Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1797, 64)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-11T02:09:40.648285Z",
     "start_time": "2020-12-11T02:09:40.640239Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  0.,  5., ...,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ..., 10.,  0.,  0.],\n",
       "       [ 0.,  0.,  0., ..., 16.,  9.,  0.],\n",
       "       ...,\n",
       "       [ 0.,  0.,  1., ...,  6.,  0.,  0.],\n",
       "       [ 0.,  0.,  2., ..., 12.,  0.,  0.],\n",
       "       [ 0.,  0., 10., ..., 12.,  1.,  0.]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-11T02:09:45.394099Z",
     "start_time": "2020-12-11T02:09:44.805832Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1797, 5)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.decomposition import FactorAnalysis\n",
    "transformer = FactorAnalysis(n_components=5, random_state=0)\n",
    "X_transformed = transformer.fit_transform(X)\n",
    "X_transformed.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-11T02:09:46.966067Z",
     "start_time": "2020-12-11T02:09:46.959009Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.15740939,  0.30545241,  1.88630105,  0.89678859, -0.17029374],\n",
       "       [-0.87586253,  0.13827044, -1.75345561, -0.83281075, -0.74288303],\n",
       "       [-0.99892214, -0.43236642, -1.22222905, -0.82192628, -0.77094974],\n",
       "       ...,\n",
       "       [-0.70066938,  0.09868465, -0.99651414, -0.14234655, -0.61502155],\n",
       "       [-0.37322424, -0.18103725,  1.07294051, -0.6538424 , -0.28351881],\n",
       "       [ 0.64021206, -0.87404644, -0.04237855,  0.32160612, -0.47697811]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_transformed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 사회연결망 분석(SNA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 모르겠음..."
   ]
  }
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