Chapter4_notes.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns; sns.set()\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.formula.api as smf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Log odds and odds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4.000000000000001\n",
      "4.5555555555555545\n"
     ]
    }
   ],
   "source": [
    "# the 'odds' : p/(1-p)\n",
    "print(.8/(1-.8))\n",
    "print(.82/(1-.82))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8\n",
      "0.8181818181818182\n",
      "0.9090909090909091\n",
      "0.6666666666666666\n"
     ]
    }
   ],
   "source": [
    "# % chance of winning\n",
    "# odds/(odds+1)\n",
    "print(4/(4+1))\n",
    "print(4.5/(4.5+1))\n",
    "print(10/(10+1)) # example of a 10-1 favorite, % win\n",
    "print(2/(2+1)) # example of a 2-1 favorite, % win"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Estimating the regression coefficients for Logistic Regression pg. 133 vs LDA pg. 139\n",
    "\n",
    "In Logistic Regression we use **_maximum liklihood_**: we seek estimates for $\\hat\\beta_0$ and $\\hat\\beta_1$ such that the predicted probability $\\hat p(x_i)$ of a particular class for each individual corresponds as closely as possible to the true observation class status.\n",
    "\n",
    "In other words, we try to find $\\hat\\beta_0$ and $\\hat\\beta_1$ such that plugging these estimates into the model for $\\hat p(x_i)$, given in the logistic funcition below, yields a number close to one for all the observations in the positive class, and a number close to zero for all observations in the negative class.\n",
    "\n",
    "The logistic function:\n",
    "$$p(X) = \\frac{{{e^{{\\beta _0} + {\\beta _1}x}}}}{{1 + {e^{{\\beta _0} + {\\beta _1}x}}}}$$\n",
    "\n",
    "LDA classifiers, on the other hand, use the **_estimated mean and variance from a normal distribution_** to compute estimates.\n",
    "\n",
    "LDA assumes that the observations within each class come from a gaussian (normal) distribution with a class-specific mean vector and a commor variance.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Confusion Matrix\n",
    "\n",
    "----------------\n",
    "\n",
    "**True Positive (TP)** = hit\n",
    "\n",
    "**True Negative (TN)** = correct rejection\n",
    "\n",
    "**False Positive (FP)** = Type 1 error, (false alarm)\n",
    "\n",
    "**False Negative (FN)** = Type 2 error, (a miss)\n",
    "\n",
    "***\n",
    "\n",
    "**Recall (TPR)**\n",
    "* sensitivity\n",
    "* hit rate\n",
    "* true positive rate (TPR)\n",
    "* TP/(TP+FN)\n",
    "* 1-FNR\n",
    "\n",
    "**Precision**\n",
    "* positive predicted value (PPV)\n",
    "* TP/(TP+FP)\n",
    "\n",
    "**Specificity (TNR)**\n",
    "* selectivity\n",
    "* true negative rate (TNR)\n",
    "* 1-FPR\n",
    "* TN/(TN+FP)\n",
    "\n",
    "**False positive rate (FPR)**\n",
    "* fall out\n",
    "* FP/(FP+TN)\n",
    "* 1-TNR\n",
    "\n",
    "**False negative rate (FNR)**\n",
    "* miss rate\n",
    "* FN/(FN+TP)\n",
    "* 1-TPR\n",
    "\n",
    "**Accuracy**\n",
    "* how many overall did you get correct\n",
    "* (tp + tn)/(tp + tn + fp +fn)\n",
    "* Error rate = 1-accuracy (how many overall did you get wrong)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make the connection with the epidemiology literature, we think of `positive` as the “disease” that we are trying to detect, and `negative` as the “non-disease” state. To make the connection to the classical hypothesis testing literature, we think of `negative` as the null hypothesis and `positive` as the alternative (non-null) hypothesis. In the context of the `Default` data, `positive` indicates an individual who defaults, and `negative` indicates one who does not.\n",
    "<img src=\"https://cdn-images-1.medium.com/max/1600/1*Z54JgbS4DUwWSknhDCvNTQ.png\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "recall/sensitivity: 24.3\n",
      "precision: 77.9\n",
      "specificity: 99.8\n",
      "miss rate: 75.7\n",
      "accuracy: 0.9725\n",
      "overall error rate: 0.02749999999999997\n",
      "fpr: 0.0023792283024723286\n"
     ]
    }
   ],
   "source": [
    "# table 4.4 pg. 145\n",
    "# threshold = p>0.5 (bayes default for 2-class case)\n",
    "\n",
    "tn = 9644\n",
    "fp = 23\n",
    "fn = 252\n",
    "tp = 81\n",
    "\n",
    "\n",
    "recall = round((tp/(tp+fn) * 100), 1)\n",
    "print(\"recall/sensitivity: \" + str(recall))\n",
    "\n",
    "precision = round((tp/(tp+fp) * 100), 1)\n",
    "print(\"precision: \" + str(precision))\n",
    "\n",
    "specificity = round((tn/(tn+fp) * 100), 1)\n",
    "print(\"specificity: \" + str(specificity))\n",
    "\n",
    "miss_rate = round((fn/(fn+tp) * 100), 1)\n",
    "print(\"miss rate: \" + str(miss_rate))\n",
    "\n",
    "accuracy = (tp + tn)/(tp + tn + fp +fn)\n",
    "print(\"accuracy: \" + str(accuracy))\n",
    "print(\"overall error rate: \" + str(1-accuracy))\n",
    "\n",
    "fpr = fp/(fp+tn)\n",
    "print(\"fpr: \" + str(fpr))\n",
    "\n",
    "# FNR/miss_rate = 1-recall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "recall/sensitivity: 58.6\n",
      "precision: 45.3\n",
      "specificity: 97.6\n",
      "miss rate: 41.4\n",
      "accuracy: 96.3\n",
      "overall error rate: 0.0373\n",
      "fpr: 0.02430950656873901\n"
     ]
    }
   ],
   "source": [
    "# table 4.5 pg. 146\n",
    "# changed threshold = p>0.2\n",
    "\n",
    "tn = 9432\n",
    "tp = 195\n",
    "fn = 138\n",
    "fp = 235\n",
    "\n",
    "recall = round((tp/(tp+fn) * 100), 1)\n",
    "print(\"recall/sensitivity: \" + str(recall))\n",
    "\n",
    "precision = round((tp/(tp+fp) * 100), 1)\n",
    "print(\"precision: \" + str(precision))\n",
    "\n",
    "specificity = round((tn/(tn+fp) * 100), 1)\n",
    "print(\"specificity: \" + str(specificity))\n",
    "\n",
    "miss_rate = round((fn/(fn+tp) * 100), 1)\n",
    "print(\"miss rate: \" + str(miss_rate))\n",
    "\n",
    "accuracy = round(((tp + tn)/(tp + tn + fp +fn) *100), 1)\n",
    "print(\"accuracy: \" + str(accuracy))\n",
    "print(\"overall error rate: \" + str(1-((tp + tn)/(tp + tn + fp + fn))))\n",
    "\n",
    "fpr = fp/(fp+tn)\n",
    "print(\"fpr: \" + str(fpr))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape: (1250, 9)\n"
     ]
    },
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Lag1</th>\n",
       "      <th>Lag2</th>\n",
       "      <th>Lag3</th>\n",
       "      <th>Lag4</th>\n",
       "      <th>Lag5</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Today</th>\n",
       "      <th>Direction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2001</td>\n",
       "      <td>0.381</td>\n",
       "      <td>-0.192</td>\n",
       "      <td>-2.624</td>\n",
       "      <td>-1.055</td>\n",
       "      <td>5.010</td>\n",
       "      <td>1.1913</td>\n",
       "      <td>0.959</td>\n",
       "      <td>Up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2001</td>\n",
       "      <td>0.959</td>\n",
       "      <td>0.381</td>\n",
       "      <td>-0.192</td>\n",
       "      <td>-2.624</td>\n",
       "      <td>-1.055</td>\n",
       "      <td>1.2965</td>\n",
       "      <td>1.032</td>\n",
       "      <td>Up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2001</td>\n",
       "      <td>1.032</td>\n",
       "      <td>0.959</td>\n",
       "      <td>0.381</td>\n",
       "      <td>-0.192</td>\n",
       "      <td>-2.624</td>\n",
       "      <td>1.4112</td>\n",
       "      <td>-0.623</td>\n",
       "      <td>Down</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2001</td>\n",
       "      <td>-0.623</td>\n",
       "      <td>1.032</td>\n",
       "      <td>0.959</td>\n",
       "      <td>0.381</td>\n",
       "      <td>-0.192</td>\n",
       "      <td>1.2760</td>\n",
       "      <td>0.614</td>\n",
       "      <td>Up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2001</td>\n",
       "      <td>0.614</td>\n",
       "      <td>-0.623</td>\n",
       "      <td>1.032</td>\n",
       "      <td>0.959</td>\n",
       "      <td>0.381</td>\n",
       "      <td>1.2057</td>\n",
       "      <td>0.213</td>\n",
       "      <td>Up</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year   Lag1   Lag2   Lag3   Lag4   Lag5  Volume  Today Direction\n",
       "0  2001  0.381 -0.192 -2.624 -1.055  5.010  1.1913  0.959        Up\n",
       "1  2001  0.959  0.381 -0.192 -2.624 -1.055  1.2965  1.032        Up\n",
       "2  2001  1.032  0.959  0.381 -0.192 -2.624  1.4112 -0.623      Down\n",
       "3  2001 -0.623  1.032  0.959  0.381 -0.192  1.2760  0.614        Up\n",
       "4  2001  0.614 -0.623  1.032  0.959  0.381  1.2057  0.213        Up"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/JWarmenhoven/ISLR-python/master/Notebooks/Data/Smarket.csv')\n",
    "df=df.drop(columns=['Unnamed: 0'])\n",
    "print(\"Shape: \" + str(df.shape))\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1250 entries, 0 to 1249\n",
      "Data columns (total 9 columns):\n",
      "Year         1250 non-null int64\n",
      "Lag1         1250 non-null float64\n",
      "Lag2         1250 non-null float64\n",
      "Lag3         1250 non-null float64\n",
      "Lag4         1250 non-null float64\n",
      "Lag5         1250 non-null float64\n",
      "Volume       1250 non-null float64\n",
      "Today        1250 non-null float64\n",
      "Direction    1250 non-null object\n",
      "dtypes: float64(7), int64(1), object(1)\n",
      "memory usage: 88.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Lag1</th>\n",
       "      <th>Lag2</th>\n",
       "      <th>Lag3</th>\n",
       "      <th>Lag4</th>\n",
       "      <th>Lag5</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Today</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1250.000000</td>\n",
       "      <td>1250.000000</td>\n",
       "      <td>1250.000000</td>\n",
       "      <td>1250.000000</td>\n",
       "      <td>1250.000000</td>\n",
       "      <td>1250.00000</td>\n",
       "      <td>1250.000000</td>\n",
       "      <td>1250.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2003.016000</td>\n",
       "      <td>0.003834</td>\n",
       "      <td>0.003919</td>\n",
       "      <td>0.001716</td>\n",
       "      <td>0.001636</td>\n",
       "      <td>0.00561</td>\n",
       "      <td>1.478305</td>\n",
       "      <td>0.003138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.409018</td>\n",
       "      <td>1.136299</td>\n",
       "      <td>1.136280</td>\n",
       "      <td>1.138703</td>\n",
       "      <td>1.138774</td>\n",
       "      <td>1.14755</td>\n",
       "      <td>0.360357</td>\n",
       "      <td>1.136334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2001.000000</td>\n",
       "      <td>-4.922000</td>\n",
       "      <td>-4.922000</td>\n",
       "      <td>-4.922000</td>\n",
       "      <td>-4.922000</td>\n",
       "      <td>-4.92200</td>\n",
       "      <td>0.356070</td>\n",
       "      <td>-4.922000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2002.000000</td>\n",
       "      <td>-0.639500</td>\n",
       "      <td>-0.639500</td>\n",
       "      <td>-0.640000</td>\n",
       "      <td>-0.640000</td>\n",
       "      <td>-0.64000</td>\n",
       "      <td>1.257400</td>\n",
       "      <td>-0.639500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2003.000000</td>\n",
       "      <td>0.039000</td>\n",
       "      <td>0.039000</td>\n",
       "      <td>0.038500</td>\n",
       "      <td>0.038500</td>\n",
       "      <td>0.03850</td>\n",
       "      <td>1.422950</td>\n",
       "      <td>0.038500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2004.000000</td>\n",
       "      <td>0.596750</td>\n",
       "      <td>0.596750</td>\n",
       "      <td>0.596750</td>\n",
       "      <td>0.596750</td>\n",
       "      <td>0.59700</td>\n",
       "      <td>1.641675</td>\n",
       "      <td>0.596750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2005.000000</td>\n",
       "      <td>5.733000</td>\n",
       "      <td>5.733000</td>\n",
       "      <td>5.733000</td>\n",
       "      <td>5.733000</td>\n",
       "      <td>5.73300</td>\n",
       "      <td>3.152470</td>\n",
       "      <td>5.733000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Year         Lag1         Lag2         Lag3         Lag4  \\\n",
       "count  1250.000000  1250.000000  1250.000000  1250.000000  1250.000000   \n",
       "mean   2003.016000     0.003834     0.003919     0.001716     0.001636   \n",
       "std       1.409018     1.136299     1.136280     1.138703     1.138774   \n",
       "min    2001.000000    -4.922000    -4.922000    -4.922000    -4.922000   \n",
       "25%    2002.000000    -0.639500    -0.639500    -0.640000    -0.640000   \n",
       "50%    2003.000000     0.039000     0.039000     0.038500     0.038500   \n",
       "75%    2004.000000     0.596750     0.596750     0.596750     0.596750   \n",
       "max    2005.000000     5.733000     5.733000     5.733000     5.733000   \n",
       "\n",
       "             Lag5       Volume        Today  \n",
       "count  1250.00000  1250.000000  1250.000000  \n",
       "mean      0.00561     1.478305     0.003138  \n",
       "std       1.14755     0.360357     1.136334  \n",
       "min      -4.92200     0.356070    -4.922000  \n",
       "25%      -0.64000     1.257400    -0.639500  \n",
       "50%       0.03850     1.422950     0.038500  \n",
       "75%       0.59700     1.641675     0.596750  \n",
       "max       5.73300     3.152470     5.733000  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# numericals\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Direction</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1250</td>\n",
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       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Up</td>\n",
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       "      <th>freq</th>\n",
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      ],
      "text/plain": [
       "       Direction\n",
       "count       1250\n",
       "unique         2\n",
       "top           Up\n",
       "freq         648"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# categoricals\n",
    "df.describe(include='object')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Scatterplot Matrix\n",
    "equivalent to `pairs()` in `R`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 72 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Correlation Matrix\n",
    "\n",
    "Equivalent to `cor()` in `R`. Python exludes categorical data by default."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>Year</th>\n",
       "      <th>Lag1</th>\n",
       "      <th>Lag2</th>\n",
       "      <th>Lag3</th>\n",
       "      <th>Lag4</th>\n",
       "      <th>Lag5</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Today</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.029700</td>\n",
       "      <td>0.030596</td>\n",
       "      <td>0.033195</td>\n",
       "      <td>0.035689</td>\n",
       "      <td>0.029788</td>\n",
       "      <td>0.539006</td>\n",
       "      <td>0.030095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag1</th>\n",
       "      <td>0.029700</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.026294</td>\n",
       "      <td>-0.010803</td>\n",
       "      <td>-0.002986</td>\n",
       "      <td>-0.005675</td>\n",
       "      <td>0.040910</td>\n",
       "      <td>-0.026155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag2</th>\n",
       "      <td>0.030596</td>\n",
       "      <td>-0.026294</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.025897</td>\n",
       "      <td>-0.010854</td>\n",
       "      <td>-0.003558</td>\n",
       "      <td>-0.043383</td>\n",
       "      <td>-0.010250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag3</th>\n",
       "      <td>0.033195</td>\n",
       "      <td>-0.010803</td>\n",
       "      <td>-0.025897</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.024051</td>\n",
       "      <td>-0.018808</td>\n",
       "      <td>-0.041824</td>\n",
       "      <td>-0.002448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag4</th>\n",
       "      <td>0.035689</td>\n",
       "      <td>-0.002986</td>\n",
       "      <td>-0.010854</td>\n",
       "      <td>-0.024051</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.027084</td>\n",
       "      <td>-0.048414</td>\n",
       "      <td>-0.006900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lag5</th>\n",
       "      <td>0.029788</td>\n",
       "      <td>-0.005675</td>\n",
       "      <td>-0.003558</td>\n",
       "      <td>-0.018808</td>\n",
       "      <td>-0.027084</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.022002</td>\n",
       "      <td>-0.034860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Volume</th>\n",
       "      <td>0.539006</td>\n",
       "      <td>0.040910</td>\n",
       "      <td>-0.043383</td>\n",
       "      <td>-0.041824</td>\n",
       "      <td>-0.048414</td>\n",
       "      <td>-0.022002</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.014592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Today</th>\n",
       "      <td>0.030095</td>\n",
       "      <td>-0.026155</td>\n",
       "      <td>-0.010250</td>\n",
       "      <td>-0.002448</td>\n",
       "      <td>-0.006900</td>\n",
       "      <td>-0.034860</td>\n",
       "      <td>0.014592</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Year      Lag1      Lag2      Lag3      Lag4      Lag5    Volume  \\\n",
       "Year    1.000000  0.029700  0.030596  0.033195  0.035689  0.029788  0.539006   \n",
       "Lag1    0.029700  1.000000 -0.026294 -0.010803 -0.002986 -0.005675  0.040910   \n",
       "Lag2    0.030596 -0.026294  1.000000 -0.025897 -0.010854 -0.003558 -0.043383   \n",
       "Lag3    0.033195 -0.010803 -0.025897  1.000000 -0.024051 -0.018808 -0.041824   \n",
       "Lag4    0.035689 -0.002986 -0.010854 -0.024051  1.000000 -0.027084 -0.048414   \n",
       "Lag5    0.029788 -0.005675 -0.003558 -0.018808 -0.027084  1.000000 -0.022002   \n",
       "Volume  0.539006  0.040910 -0.043383 -0.041824 -0.048414 -0.022002  1.000000   \n",
       "Today   0.030095 -0.026155 -0.010250 -0.002448 -0.006900 -0.034860  0.014592   \n",
       "\n",
       "           Today  \n",
       "Year    0.030095  \n",
       "Lag1   -0.026155  \n",
       "Lag2   -0.010250  \n",
       "Lag3   -0.002448  \n",
       "Lag4   -0.006900  \n",
       "Lag5   -0.034860  \n",
       "Volume  0.014592  \n",
       "Today   1.000000  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# seaborn heatmap correlation heatmap example\n",
    "# https://seaborn.pydata.org/examples/many_pairwise_correlations.html\n",
    "\n",
    "# Compute the correlation matrix\n",
    "corr = df.corr()\n",
    "\n",
    "# Generate a mask for the upper triangle\n",
    "mask = np.zeros_like(corr, dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "\n",
    "# Set up the matplotlib figure\n",
    "f, ax = plt.subplots(figsize=(11, 9))\n",
    "\n",
    "# Generate a custom diverging colormap\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "\n",
    "# Draw the heatmap with the mask and correct aspect ratio\n",
    "sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot Volume over the index.\n",
    "\n",
    "Equivalent to `plot(Volume)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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apZTKKaWOCvjdLwCf1lqPaa3HgT3AEtt3Hge0aq1/WT50A/De4E2fm8Tl8ZOEgdj0XVFrHQtCHKzp6WbtyYt8z7MWan39g5FW8HF5MZniMeLAd0ehlPrfgW3ABPCnwGNKqXO11r8wfU5r3W/7jhMpqaB6bacsoiRMLF4Ajg3edOjsbA9z+gy6uuZF/mycvOIx2b4yPDqrzWH60LWglf0uqp6uBa1Vuxam37jo7BXctH0PLx8Y4Zjy63WnLDZ+34MPPxv6M2mQ1bEUlFpvP4Tvw4MPP8svfvdioHPHJqa4/aGnuGRDD9f98LFQKUCCGqfz+RxTISb/ySLc/tBTnLfuxMCfqYQgqqergfXA/9RaP6eUuhD4JnBakB9QSvUAPwE2a61/b3srT0klZZEDQikAh4YOhrq4Fl1d8wIVY0+Doz3ywRzd0TyjzWH7cP7px7saiM8//fiqXQvTb/Qsme9quPb6bacKbv+BEa7950cZfu1wplRSWR5LQaj19kO0PtxwZ3+oCX//gRF6lsznonepaduZ5bSRY+ZEFpb21mh1tPcfGAnd73w+F2mBHUT1dJTWetpNQGt9FwFtG0qpXuCnwJVa6xsdbz8HvNH2uhsIn/93jhFXHEUSbrfV/I1b73tCgu6E2AircrXG9Jqe7uln1FqjVqoEOjgyQT6CjiprxuxxpdQCytdDKaWCfLFSajFwO/A+rfX9zve11s8opQ4rpXq11juBC4HtwZueDnG7mMbp8ZOEgbgav9HXP+i5wpKgu2BUY5zO5XxbYcqiOhdq1fZ+ilKiNWl38SCC4m+BHUC3UupWSp5MHwnwuc8ALcDXbbLlO8B5wBe11r8BPghsUUp1AL8FrgnX/GRJKgdRLXv8VGNyMe0aJOjOn2qM07meb8svk6uFW6R2NRcrlvfS7Q895Wrfg9KYP2lpJ7sGhlIT2r6CQmt9p1JqL/AOoAB8RWu9J8DnPgF8wuWt79jOeQx4a/DmpkstZ3ZNgmpNLqYHUYLu/PEbp3Zh3rWglfNPPz5Q8ru5Ntajeg61tRQ4dDhcTQs37EKoY14Lf3/rb3HKrVwORscneeCRfbS1FGhvbWBoeHR6MZXUvQgaR3GQ0q4CIKeUWmm3W9QLkoPITLUmF68HsakhV9MR60nhl8XX6STgJszn+li/9b4nZk3KblgpPeDI9clFLbxto721gWs+8fbp1+tOWcw/3LZrlsq1WGT6mP2ZSHqHF8Q99uvAx4D/pGTgh5K9YmGM7cokXrpEUYeUqNbk4vUgNkUoYenHXFGx2IWdVwqVzo7mQML85nu8i/vMhbFusoG54UzpEcVDyU4+l+OC9ctmHQ/7vUnu8IJ4PW0EFmmtF2qtu8r/1Z2QgNrO7JoEpknEL2OsHa8HptIH1I25kNLcEnaWQHYTEtY49RPmN9+z1zO9xVwZ61Hu7dDw6HTm40o2FM2NBT68YYXr5B5FCCe1wwuienoCyF5tvhSI4pE019QaJtyS+VmEWak3N+YYHZ8927W1VH9HEXUXZN3XV4ZHOTrl+xrEC6d3VclBwquEpzVJ7XjU20O9VrIY+1HJ5Br1s/nc7Gp5TkzPjxdJ7fCCCIprgB1KqQeAceug1vorsbUqw4TxSJorao2gWH265V7tamMYm5hiyx272bZjgI1rl3LeutnRtH39g65CAqqjG3biFexkegCzdl+DTF67BoYA/8y8JvuuWzbVWlsE9fUPBspuXG2miv5jw7kQ9TOaJ7nDCyIorgSGgfkxt2XOkTXPkaQe7MOjZo8Qa2LtmNdCz5KZw8qkFqi26qmvf5CRw7O/0y/hWtbuaxA/fOt952Rk93oyqQad8WBZE5ZBMGU3bmrIMz45RTEmAeJXB8PCuRD1UgX6FViqNkFa36a1Pj32lsxBsuQ5EveDbRdCQXCrR9HXP2j8fLW32dt2DLh6vjQ35qeviZtwzdJ9hWAqC/u1s09G9vQXJiHtTKCXlrB0ux9uO1O38007iVwuF5uQABgLkS7EjpXpNu2dWxBBoZVSJ2mtd8XemjlGlrykvB7sW+7VVa91ERR7PQrrO0yYqotF2S15TezWdt9LuEZRV8WJc5fgJKiKwiTonPWj4xSWznt50tJOfrXnxVlqGNPO1Poe+/0zqZvC5H2KQtDkgF7jOO1dWhBBsQT4jVLqKWB6FGitT4qtVXOEJCu1+U2Upkmxr3+w6rUugmCvRxHkO3Y+PsgJx8531ZVH2S35CXIv4drYkKOpIZ+pCnzWZNLXPzjDRhRGRRFmYRPXIqivf3BGxPTQ8KixyJCpUmLWCg35kWV1XhBB8d9ib8UcpZK8TWFWyEEGmEmPXam6IOoq0l6PIsh3eKk2TLsl0zX0E+Qm4Xr5uSsz4/Vk4bazGxsPPlGGWdhUYxHkNsZvuluHLvTjVSkxS8GBQWwUWbN92QkiKB6PvRVzmCjbxrAriyADbOPapZ61git9oKIkNYNSNKqlHw/6HW7nmCZ0a2Xtdg39BLlp1Wzd1yyl6a50orHKhO54dB9TxZIB23KrdTvX+s0ounO3Me5Xy9qLIqU4HfvvB43ZSYKGgnuAnZOs2b7sBBEUL1O6F/a066GLDNUiabn/hX3ggwywNT3d3HrfE7Ho1r1Wl72ruj3VBs4VlkmQ+bU1qJBxu4YmQZ6k6rAaVDrR9PUPsvPxwWld/lTRW90HlSWvrLZaaGh4dEaqjawETIaZN7Jk03TiG5mttc5rrQta6zzQCnwYuDn2lqWMM9rVXhIxbkwPvFuEs9dAch6/YP2yRGtdWL77bjhXWGt6ullxnL8HtptB2y1i3gvnte3rH2Tz9Tuno27t1zaJGh7VwpR2I5fDtX9OkoxSj2OVPDFZ5Nb7nqjo+9taCjQ3Videp721IdTiMsuZH4ImBQRAaz0G3KCU+g1z3HaRpr7QtEJ28/Twco+0BIvTcyKpWhemHYLbb77koWu247bCdevX6Pik7+4piIrPrV9evu1puS729Q8aDb6W26efCtNvgVLNvkVVV0JJ8Hm5sh4cmWDz9TtDV42z7l1pPFTHT/bgyEQoY3Scz2elBEkKeLTtZQ44FVgQW4syQpr6Qj+/eKenh8k90jk5JOlq5zUZ5HOlyc3p/x5UfWSP7vaa0N0Mu0EK0PgtBky5kIJ6qVRbpRlmxW/qX5AFCnj37eZ79s6wb6w9edEst1qLKOkqCjnI5XO+xu4oz+jGtUtj8ZIam5jie3eWFkxBhUUWBIOTsDYKgJdwrzMxp0hTX+jnFw+zPT2sAbb5+p2zPuNViyDuFYvXZDBVZNauKKxKz2/iCrI6M02KXtfJlAsJStf6xu17+N6du10nzGq6QIYNcrT3z40gCxQvIeMUoFNFpl+7CYsgY9zJZNH6p/pEuY5BscY7pO/mGpUghYuCKX/nGGkaMoNMAPYYBDt+k1+SftrWd1qTpp2xiSn+8fbH+eZfvw2IltHTb/XvtzrzWgy0tRRcPXKCeuXYVRfOCTPILiaIMI8a5Gj1z1pQ2FN4+OXqAu/x5SVAdzy6z3NXYf3mpqtmVUpOnLg1BVlxc42Kp6BQSn3K9EGt9der35zsUA33v6jxE34TQFNDfkYMgh3TTqgSu0vU/qzp6facYF97fXw62C/qg1rJA+61GMjlcoxNVDdS15ow/VSaXm6jN92tuehdasa4jCIkCjkYHZ/i0OHS7+0/MMLWO3dPe8R1djRj6rpXPIBX1HOQ5Hth7QlZIoytxVqs1aKwMO0oVhneSzj3YjpE1RdWsnL3mwByuVK6Z3sMgh3TTihqHEWlO5EgwX6VZPSsxNDa2JBjrDxHWVHMUf35TVh9ixINDqUUE3b3z6gCsqGhMCtdxaStiprf9xY9rMhe98+ZTDDMdzqx++dbNDXkyedzHB6rnmB3+x0vrr6id8brvv5B1x20Ra2qoDwFhdb6UvtrpdRxQKPW+snYW1XjVLJy939QzYPMtBPyq0XgRZgazPbfC6JCs96rJO2ztep+8rlXPdUcTkxRzHGloe7rH4wcDQ4zK615CRy/Sa7SnEZeKqm1Jy9yNfIrlxxMQb/TTltLgdHxqVmG7N5V3Txo8PgKS2dHM4fHJgK1yU0IWkGLXg4PtaqCCuL1dALwL8AiIK+Uehn4c621OYNbHVOJx1SQraybx5Adr52Q1yR10tLOaZ11FKOv227jyedeZefjg77qEXuMQqV64gce2TfLddZLiHkJP9NqsFJu3L6Xi89ezsVnL5+V9G7bjgG23LHbV0hZ18jtXhZy0NoSrxrHa1Fx4VnLGXzldfY8M7PG2cDzw77qliD3vqWpYVpdZmfXwBBNjXlGQ6Qq8cJv5+1kqui+mzXFD0E2Iq3DEsRQfR3wVa31Aq31G4C/Ba6Pt1m1TdAAODeCGMujBkC5BZD1rupm5+NH0nu7BRaa+uM14e54dJ+vkGhuLEz3d+PapRSqEOd0y716+m8rwZy9b1vu2M3N9+z1fFjjLGhjX01uXLt0eoJ84JF9gXdW1r1Y09NN76ruGatauwrJi0ousZ8zh1scjClgzwp29Js4/dx2KxESls3FHkwZxrPRGlP2gMYg/ak1ggiKP9Ja32i90Fr/E9AVX5Nqn0oiLNf0dPsmEIu6InFbXe8aGPKNxjX1J+qE29nRzMff++YZcRCbNqykqaEyaWFlw918/U623LHb1ef+gUf2BS4k46StpVBRzWT7Liyqvz/MTrcRlErkoFfeJ4swO+mg18AaZ1Hvlx8XrF/G1ivP5OoremfkRQsa6W/HWmT5jY8sRFqHJcjVb1BKHa21fgVAKXUMdWLMrsTTB2a6GTY1Bh94F6xfZvR8irIicfq5W4Pa6zeceaIgnN3Di86O5mkDoDOhXpTvc8OeptqLYrE4K1W4H5aevJICN167sLCkkUL7gUf28eu9L3mmLQ8Te2Rqv+UFZY2zJ597NTZ1mpu9IEqMh4XfPWlrKdScfQKCCYprgV8qpf4XJQHxfuAbsbYqA1Qj5mDc5k8fJpzf5M8eJZbDK8WD2QV35rLIZPfYeufuwHFQQ8OjXPZ39zNVZIYPv/39SgmSpvrQ4UlWHDd/lk7d7zOVEkYH7oY1saWl5z44MjHD+8rOSUs7XceZW34uU/vHxqc4Y/Uidg0MxeKBFqQd1nivJF7FjQ+8Q0X+bJo1yk1xFLcB12mt/1Ep9XvgXUABuEJrfV8irUuRSnM9VSNXVMmANzlt4LQPjgcffpYb7uz3DcqKukIfd0y2pspbXllpvbDUJfsPjMyoapdkxs/Ojmb0H4ILiWpR6a7J+pwp31Hc2L2v7Pxqz4uu5z/o4mTQ1lLwFLxjE1PG3FXVJF9OmOj1DGWl+FHaRY1MO4qHgOuUUlAyXv+t1jp04n2lVAfwC2CD1vppx3tfAjYBB8qHtmitvxX2N+Kg0lxPlXzerYSjtZOwVjk33a2nXR3tgwaqk46gWPQWNJYB79b7nuCC9csqUgtYKS+misF2AtUgn8tVvLKPQltLAYiW58iis6OZvv7B1ISExdDw6KwJ1mviLzI7fiBXiaGniliLFq+Jt9o7t6iusWkXNTLFUXwN+JpSai1wOfAFpdSPgG9prfuDfLlS6k+ALYBX1Y5TgfdrrfvCNTt+TOkdTK6kfp8PYl/wGxTbdgzM8oe3kuVVEz9dv6VOqzSytlrZOq2J2E9FNFUspaNOelV+6PAkN9+zdzrW47t37A5t7LNcabNC0PQmzkkti5HYbhOv6Tm++oreWTvthQtajerMamcgSEoFGaQexQ6t9YeA5YAGblJKBU3OcjnwMcBrH3kq8DdKqV1KqeuUUi0Bvzd23DwfrPQHJldS0+crLXJv/91qcMbqRcb3g6zwxyamKBaLVXFtrZTR8SmW/JF3fImdgyMTqazKH3hkHzffs5dtOwYieYTsGhiqST98mDlus+oi6ry2fs/xmp5urr6id9pzavMFbzE+V1H7XYnLfTUI43M2ChwChoFjgnxAa30ZQFl9NQOlVDvwCLAZeBK4AfgC8LmgDersbA966iy6uswTynnr5tExr4Wbtu/h5QMjHLOglcOjE7z2+viM88Ymprj9oac4b92Jvp+/6OwVrDtlsX/bFrSy38UnvWtBK11d8zzfD0MuB29Z0c1v9P5ZfQpLNYy81WDz+zzRAAAgAElEQVRisoh+9j/TboYvlejfXxkepaWpUNWUFUlhjV+ASzb0cN0PH6s4Urza2NsI0Z7jT33oNN6y4tlZ/WtuLHDJhh7Pucc0J7ldL7/vqyY5vzwrSqle4DLg3cC9wPVa6x1hfkQp9TSwzmmjcJyzGtiqtV4d4CvfBDw1NHSQqQgRUv1/eNXXEOyGKcvl1ivPDN0OL7xqHjQ3lvL0eKUzyCpnrHZP7yCEJ0weoizR1JCfVR2wr38wcTuRCbc2VkIYL6Ugtder4fWUz+esBfbxwNNBP2fyevosJUNzG/BdoEdr/UKoVhlQSi0B1mutt5YP5YDKlrYBMBmC/S56UjUqvFIAWG3Oygo+CG0tBS48a7lRZVKrk18a1NJ1shY2WarUZmfFcfN56cBIbO6m1S5ClGZRI5Pq6V3A54HbtNZxzEwjwFeVUg9QkmwfA26L4Xdm4GUI9vMe6Osf5PDYbANctWtUBEkBUEvkcrnpZHhuxnEr4jaLxk2hMkbHJ1132pW4bVeTP7z4Gtd+cm2qbQhDJuMotNbV06XYUErdBXxRa/0bpdRHgTuAJkruuF+L4zftRPEe8Aq6sdJSA4E8ofywfmcuYXlG9a7qpuhQExbyOU5bvlDUUnMYS11rf1aqGcBWCbW0M89yHEXV0Fq/yfb3Oba/fwz8OIk2gLncpuVaaT/Xkt5eqpHmxtJngtzAIPWEsxLc01DI0dJUqNoq30oS6DQnTU4VqyIkLBWHcCQo01SlLg2siO6WpkJsY7yzo5nR8ck5uTtNO46irsqcmvzP7QFAzoRlXnrhoeFR4w20sIzT1kRplce8+Z6ZuwfTrqYhQf/TicnidC6kahFnVtZiMX3hmhWs3ey1n1ybORfUiclirJP41Vf0hvp+v0SDVnJJe2bYtMh8HMVcwnRRD45MzMg6GmTV45f+2MJUT9iOVzWwfA4uPWfFrF1PnBw6PEnvquqtVIJUOotKtQL2LAq5ZAVztThj9aJYo4qzjDW+ggrHhkJuWhXmhnOxaIqZSgJTv5JoU10JCtPFbmsphE79bDq3raUwLXiC1hP2O2+8yhOiibaWgmfuniioJfOrukOJi/bWBjZtWMml57jXJM8ql5+7cpYqM2s7ijixnpGNa5fOEvINhRxnrF40ow7LpeesMKpsgmgKksTkMJNEmxKxUWSFjWuXeqZNmJj0TxEchonJqUBGO3u+HFN1szgrr7lRbf32wPPD9K7q5ld7XsyU7tzJwZEJttyxm/bWhpqyfXhl9s1SnEKcWMn92loKTDoelOJUkROOnR+4TC6kr+pxsqanO3LN+2qQ/SVeFVnT002bh16y2hPC6HgxsOCxtrUmQZCkkIiDsYkpdg0M0dIUbm2SlgLo4MhEzQiJONV6tYL1fBw6PDkrNctkMfyqO+2UGWF+O4k21ZWggOz6649NTM35B35oeDTU6qepIU9T4xy/KFVg7cnuuYVuve+JSN8X1xWPQ/UY9JkJu+quJFdbXKTZproTFCZPh3yVUh83NeQjlW600onPVTo7mikYnuxCPjerhvHoeG1tpdpaCoknSHRTqfT1D0ZeFMV1xavpHAGlMRJ0px3WEcStvnw103tEpdFWUKy9tSGxNtWVjaKvf5BDhodnqgrpRC17AxBaP9zZ0cxJSztdYw5qnaaGPAsXtBpXdpZu+fJzV1ZUjhLSK+xjVTCLkkK8mmQpFbmFl/efCS+7nbWSDjo+Rsen6OsfDDWpppkyw4lb0O/YeHJu4XN3+erCLffq2B7eFcfNn3aXtR5SvzTedpoa8py0tJOdjw/OOSFhrcaCVJSzIrktl7+ohe7zpLM723LHbrbtGGBdiHvvh5+rrpt7ZBZdY8OM686OZrZeeSbf/b/PZOuVZ3L5uStdV/cb1y6dDnw1YVXlq1XS9sKqqx1FnN429mIlQ8OjbL1zN60twS5vPgcXn708M5HZ1cAtlUnQHZY94tS5szB5htmZLMKms5enEqE8NDxa1bQkfnp4q3CQ/ZqbYnxqAafe3Wt1v6anm455LTOyQWfNY6kapN2nuhIUSTJZDG44nyqa3d9qEbd8V0EneZj5ANgnCVOqdyfbdgxkpuRmJQQNKLSnjwlbbjVL6S/aWgqhVD7rTllMz5L506+tvGtOajmuJKnM1V7UleopioE5CXKU1AdJ3fQk5k63KFYv7xw3quEKODQ8WvWJr7OjOdJ9amspzDCoFmJ68uy7Macx1sTVV/RywfplqTtTNDXkp+08Ucmix1KlpN2nwpe//OVEfqjKzAc+OTIyFspgOX9eM799Yn9sjaqEXQMv89YVC9n38qFZAUPVpKkhx9vfvIinB81FUiplcqrIM4PDvPO0JdPH3nzCMdz973/w7V9TQ54L1i/juf0HueZHj/GDnz7JQ7v2Me+oJla86Wh+9x9DsV4jU7tOW76QZ158LXSU/PhEkfGJIvlcyasozhocI6OTvPv041m8sJ13nraEd59+PO88bQn/8tBTnp9ZuKCVbTsGODgyMd3Gzo7mxCvpbfpzc8S0G21tzbz++tj068UL2+l8QwvPDA4zMlqqh3HB+mWZMUy74eyDk2r1KZfLcdRRTQDfBPyNhtbn/CrcZZQ3EaHCnVfluKxg6ZizkKu/mth1514p2+2sOG4+p5+0aNZ5VgUyiO4NFRXLI23n44OJ2pGiRId3djRz9RW9s47/9Td/5rrDam7MUSzmZvUr6cqEZ6yenVE5CEGqw2WdpPoQtcJd3aie+voHMy0k4Eg2WssoF8SbAwh8XlrYE6o5VSJu7HnmVW66WxvTKl99RW9gVWKlmrb21gauvqKXXQNDrkKis6OZy89dWeGvzMRSDzYUwiUoNKkjLli/zDUPUmODe+rvBx7Zl4iaEkqLgyhCQkiGuhEUteIaZ89WGWQlefm5K2si1YTdlc+a6LsWtHqe79Un+y7CbeJz0tSQZ93qRZF17/YsoybPE8vTqBKaGvKcUW6rtdE/dHiSyclioAnb8p7zUkes6enm0nNWzLBbfOJ9q412nKQUDi8dGEnmh4RIZNO6GwOVqimsAK4s1Xfu7GhmTU93zaiqnG3cH2FysE/GTtdZSz1k1ee2q7xOOHZ+JK+ylqYjuzU/z5OwnkZ28rlS5LLbrqU4/Y+ZqeKRtB0mYWF/r6tr3rRraZp4/X6a5T+FI9SNoIjqV26VcLQGZ1//YCbcWJsbC2xcu9SzlncWsU/yQXLoNzXkZ9ko/Pzr+/oH2TUwNOu7/ASq3f6x9c7dWKW9D45MsPXO0v12EwTWfbB+A2YLriAqz6kiVbF/WJXk7O3xw5Rltq2lkEgcittuLO3yn8IR6sbrad5RTZG8ZcYmpvjtE/v5l4ee4qcPP8uqP+7kiWcPpBoY19ZSoKEhT1//i/z2if2zPHDaWxtoasxnKnjP8mRavLAdgGt+9Bgjo94T0BmrF3HmKcfO8PI4bflCHnzk+RleUNb3wZGJxVKljIxO8rv/GKLzDS0sXtjuOQbaWxv40FmKNT3dfPWWhxl1XM8i8Lv/eJn/4/xVszxPPvIXq3jLicdMn+v0NHp9dCKwp93k1BGvqCB0djS7XsOpIrM8zrxoa2vm6LYmhg+NzvKEa2rIc+FZy0OP9xylaxr0M86xYXHNjx6bpRZz86bz8xiqBZLqQ1Svp7rZUVgrkErqOli1CtKikANyVoS59yRrrXKdq99CDqZw1ztXQ6XW1lKgpamBoeFR2loK5HI5Do5MuKoMTLu7pobctGHTvpMzrS77+gdd760pytutXV6r57GJ4rQx3qm6MXmrhLWNBR2bfjvksLvnE46dP6NWiHMnbd9l+VEo5Dht+cLAO6TeVe5R12lHIwtHqBtBAUcmnZvu1jVhAM4Bba0NHByZoK2lwOujkwQpD20ZV2H2pAizH/pCDt5+8qKKVR+HDk9y7SfXBjrXNNG5RSL75box1fPwivIOS5RC9pVOas2NOSanSrmK7IyOT9JeHhtuhDGs+yWcW9PTza33PRE4eHFissiv9rxIY0OOIFpRN1UhpB+NLByhrgQFlAb98y8f4q6+Z9JuipF8Dj684UgW1c3X7wysK7YeJLdJsa9/kFw+h11S5PI5Tjh2PiccO7+i3EhhUjmbdPduE4FpdemXI8vuRutnHDVNvlFtXJVEh7e3NrFx7dJZ9+XgyASFnHuW3IZCLlTErkkIW9cmbB/CjCGv6+q2K671COtapW7cY+38eu9LaTfBFyv/k0XQScrvQdq2Y2DW6tTKrLmmp7ui9AlWKmc/+voH2fm4+3le7Tel9PC7NlZQqbVytrsgO1ONWK6wXr8VFlNAq72OsxfW7tCtMuBkEY5qLtBkq1GQy8HbTnpjqJ1PEBVPnKt4r+/Oak2IeqQuBcXLNeCz7VydB31Q/R4k06RgTaRRCZrK2WsHYIoDMOW68bs21uo2SKrmNT3drunho65kTSvrXQNDbFy7lK1Xnumb28rrvpW+/4igKJa9p4IIbOdvmI5HTffuh991tWJutl55Jldf0StCIiXqUlC0H9WYdhN8GRmduTrfuHapb+W0IGUhTZNCNdKc+63u+/oHPc9x7qLsmFaXfhO432TrPH7hWcs96x+ExSTE7Dsar4n4pKWdxu/J56i4TkGQhHPO619yVnD/vqDB3LJDqB3qzkZRK0wVj6iDLL26n9fJVBFfP3OT3tfPo+uM1f4Gb9PE6Ldj8dsZmGoSmNpuTXhhjKPVqm62ce1So8eQNamX2jj7pJ2PD3LCsfM975vXvQhjTwniDWad54xZcWtT76pu4zgp5GCTzf4mZJ9YBYVSqgP4BbBBa/20472Tge8CHcDPgL/SWicSOXbw9fHA5+Zz0NgQPjFbNbCrg5wP4/rTFnP3L58xuoO6YZoU/CK8LzxrOSccO9/zvCD2EZOQOTgywaar7o8UgeslBOy1DdIyjjqdB5xYOws3by/rflpJ/pz3zavkatgUTVEEo2ksmRwjihVn3xKSJjZBoZT6E2AL4GUd/D5wmdb6l0qp7wGXA9+Oqz12jlnQGih9xNYrzwTcV05J4KUOGpuY4uePedfV9ltNek0Kpl2F05OqdE32TE9uuZy3P3zQdlnCOEoErpcQsBvng66cq4mb84ATN/WRHeu6ud03r/uVVJoZ0y5v244BV0Fh3y0LtUGcO4rLgY8BNzvfUEodB7RqrX9ZPnQD8N9JSFBcdPYK/v7W3xpVOaacQkmxcEHrjBKrdl4z7Iqieqis6enmyedeneW26lx19/UPzlKnFIvw810vcMKx8z0ngDBpVPx2Rm5th/Dqk7jx669JfWRRq3ED1QwIdGJ3c+5a0Mr5px8vgidGYhMUWuvLAJRydbdcBLxge/0CcGzY3yjnVQ/Nuq55AHz91t96pgC5ZEMPXeXzAM5bN4/z1p3Ipr/9t9DJ7HJAU2Oe0fFwOxIvIWGiubEwq+1h+NSHTuMtK57lpu17ePnACMcsaOWis1ew7pTF0+fc/lCfq5CdmCxy+0NPcd66E12/+5INPVz3w8cCq/FeGR4N1Q/rHiWNqY1dPrvX9act5td7X/I8x+9+zjuq0XXRMO+oxsDXLupY8f1eQ9+7FrRG/t1v/+jRGXFQ+w+McNPdmo55LTPGaa0R132oBmkZs/PM3B3nKGWXCEXYwkUWXV3z6Fkyn8s2rHRVKZ2xehE9S+a7pmY4//TjQ6mh7MVYwtR7jspF71L0LJnPvz74+8gqlp4l8/m7j66Zccx+LUwT3/4DI54pLXqWzOeid6nAQX1HdzRnviCNXwoPv/Gy45Hn+MA7lOs5VhoNr7EI8P4/O9E10v79f3ZioGsXZ8Gc808/3tWQ31DIcf7px0//bpgMsX39g67BsqPjk9xwZ/+M2tm1RAqFi0KRlqB4Dnij7XU3kHhVIVOaai+jqvW3XT/vRj5XqhF94VnLpx+EuLHSjsedddOkQgrqudTXP8gPfvp7TxXaXInAta63ly3BEpgXn708kmBPw+4SFKsN9oWBWzbmMGPV9BxJDqj4SEVQaK2fUUodVkr1aq13AhcC29Noi11nHSTxnPVAesUsOMtQxmEIb2spMDE5s7iPfWINkpKhErxcPsOmjhjzUMVlabKrBn4eZZZXU9T+Jm13CYPz+dq2Y4Atd+yedgkOO1ZNwqBWbTm1QKIBd0qpu5RSp5ZffhD4hlJqL9AOXJNkW9wwDVpn+oegHkfVCGKzY3nyfPy9b/YMCIs76+aanm42bVg5I3q8vbWBS89ZEXjC2rZjwNVWYQnarE58UTEJ0HpYCXulTwk7Vk3CYKGhYqJQGbHvKLTWb7L9fY7t78eAt8b9+2GoJPGcHSsdtek7g9LcmKO9tWmWWsGys7iRz7kLsiCR20FxqjzC1u2utxTSpgys9bAS9lqEeY1Vr2ticuHWfwjv/CEEQyKzbZgid8NMYLfcq2eoqKLWvwAYHS/y7U/3+p9ow+v3KmmHk0rtIPWYQvqC9cvqNhuqKW1LkEqGFqYo/GqOb2EmdZnryYtKEs/ZOXR40ldFFZQoE6c9rXaQ41EIkmDPxMa1S2ftQub6pFnP2VBNOcbCXhOvnXE1d8zCTGRHYcPPg6QSo7S1swizw4g6cXqltjalvA5LpaqjNT3ddMxr4YY7+6d3XnZBM1cnzywbnuOir3+Q11zKfFrjO+w1WXvyItdaJmtPnp31V6gOIigcmFISwEwhcnBkInDw2FSxlBIkjBeUX0oML7xiFKIWJHKjGqqjdacsZvi1w7G68grp4hbFbxF1fF941nIGX3l9RkDqiuPmT8crCdVHVE8hcObGD5Mo0J4ryb7VNuFVIjLobwU9HoUgqamDUKkKS8g2pqzHUcd3X/8gA88Pzzg28PxwqBocQjhEUFRAmInXmdt/49qlvjrVqB5A1ZrETVRL315v3k/1Rhz5nmRxkTyieqoAt4ylXrjl8fezVVSa3G/Ho/um7SJRt/l+v1Ppd9aj91M9UUkUvxeyuEge2VFUgLWq9tsZOB+IIDEZlewArJrUliCailAeMymS2P0kRV//IJuv38mmq+5n8/U7M3m9k8arMmPYKH47zjLBfseFypEdRYX4eUS5TXp+Kx9nPpywxJ3Co5pUM1dRmORy1Sbu/Fq1SpB8T2HJedRg9TouVI4IiirgnOwsF1ivycprO57PwYerUCKy1rbm1VBhpT1R15JwTppquwS7RbebjguVI4KiSoR5GLyqsVUr+Koe9f5pT9S1JpxrmXoc32kjgiIG/FQgcaeGTqs2dJqkPVHL5JUc9TC+01SjuiGCosoEVYHEGaGbdo2CNAZ5e2uDq+qhmmlLTNTD5JUVnON7rpVCTVuN6oYIiiqTtgrEIq1UEWkN8iTSlphIWzjXG/bxnVR1uKTIyhxiRwRFlUlbBZI2aQ3yJNKW+FGPeZyE6pPFOUTiKKpMEukzskxag7zer7swd8jiWBZBUWXmUgBZFJIc5PYAt8NjEzQ4Irvq6boLc4csziGieqoy9a6rTsqo67SFHDo8SSF3xKidteueNS8WIbtkcQ4RQREDTl21tfLNyk2Pk6QGuZstZLIIzY0FrvnE26v6W5WSRS8WIdtkzd4lgiJm6nGSSGKQZ9Hg50UWvVgEIQxio4gZSYkcD1k0+HlRS0JNENwQQREzMknEQxYNfl7UklATBDdEUMSMTBLxUK3CSUlQS0JNENwQG0XMSGqH+Miawc+LLHqxCEIYRFDEjEwSAtSOUBMEN0RQJIBMEkJcSHyGkASxCgql1AeAzwONwN9rrb/leP9LwCbgQPnQFuc5giC4Uy+u1yIM0yc2QaGU+i/A/wBOAUaBXyilHtBa77addirwfq11X1ztEIS5hH3StCop2plr8Rn1IgyzTpxeT+uB+7XWr2itDwE/At7jOOdU4G+UUruUUtcppVpibI8g1DTWpGm5VjuFhMVccr2WOKRsEKfqaRHwgu31C8BbrRdKqXbgEWAz8CRwA/AF4HNBf6Czsz1y47q65kX+bFaQPszkwYef5abte3j5wAjHLGjlorNXsO6UxVX7fi+Sug+3P9Q3a9J0o2tBa6g2ZXkcveIh9F4ZHp3R7iz3IShZ7kOcgiIP2Nc8OWB6lGutDwLnWK+VUl8DthJCUAwNHWTKa1llYC4UOpE+zMSpoth/YIRr//lRhl87HKuKIsn7sP/AiO85TQ15zj/9+MBtyvo4OtqjxOzRHc3T7c56H4KQVB/y+VykBXacqqfngDfaXncD+6wXSqklSqlNtvdzwHiM7akb7Om3N1+/k77+wbSbFDv1oKLwCtLM5468n9Wgw6hIsGI2iHNHcR/wZaVUF3AI+K/AR2zvjwBfVUo9ADwNfAy4Lcb21AX1avyrh1QpXsGbc0042JE4pGwQm6DQWj+vlPoc8ADQBHxXa/0rpdRdwBe11r9RSn0UuKP8/kPA1+Jqz1zF6To4Oj5Zl5lKOz1UFHMpVUq9TpoSh5Q+scZRaK1vAW5xHDvH9vePgR/H2Ya5jNvuwYu5tLJ2o15SpcikKaSBRGbXMG56eS/m0srajXpdbQtCEoigqGGC7hLm4srajXpcbUvUspAEkma8hvHaJbS1FGoi/bZQGc4APMtxoR683IRkkR1FDeOll//AO5QIhjpASqwKSSGCooYRvXx9Uw8uwUI2EEFR49SjXl4oUQ8uwUI2EBuFINQoErUsJIXsKAShRhHVo5AUIigEoYYR1aOQBKJ6EgRBEIyIoBAEQRCMiKAQBEEQjIigEARBEIyIoBAEQRCM1KrXUwFKZf2iUslns4L0IRvUeh9qvf0gfYjwG4Uwn8sVi+FrTmeA04Gfp90IQRCEGuVtlIrFBaJWBUUzcBrwAjCZclsEQRBqhQLwRuDXQOCkYLUqKARBEISEEGO2IAiCYEQEhSAIgmBEBIUgCIJgRASFIAiCYEQEhSAIgmBEBIUgCIJgRASFIAiCYKRWU3hERin1AeDzQCPw91rrb6XcJFeUUl8C/rL88ida688qpdYDXwdagf+ltf58+dyTge8CHcDPgL/SWk+k0GxXlFL/H3CM1voSr7YqpZYA3wcWAhr4oNb6YGqNLqOUOhf4EtAG/JvW+hO1dB+UUh8C/lv55Xat9Wdq5R4opTqAXwAbtNZPh73uWeiPSx8+Avw1UAR+A3xUaz2W5T5Ane0olFL/BfgflFKAnAx8RCm1Mt1Wzab8QLwTWE2pnacopS4AtgLvBlYApymlzi5/5PvAx7XWy4AccHnyrXZHKfVnwMW2Q15tvR64Xmu9nNID9IVEG+qCUuqPge8A5wMnAW8pX/OauA9KqaOAa4C1wJuBt5XHVubvgVLqTyilmFhWft1K+Ouean9c+rAM2Az8KaXxlAc+Vj49k32wqCtBAawH7tdav6K1PgT8CHhPym1y4wXg01rrMa31OLCH0mD7vdb6qfIq9fvAe5VSxwGtWutflj97A/DeNBrtRCl1NCXB/P+WX7u2VSnVCLyd0v2YPp5oY935C0or1+fK9+F9wOvUzn0oUHrG2yjtoBuBcWrjHlxOaRLdV379VkJc94z0x9mHUeAKrfWw1roIPA4syXgfgPpTPS2iNAlbvEBpAGYKrXW/9bdS6kRKKqhrmd32Y3Hv07EJNDMI/wB8Dlhcfu3V1mOAYZuaJit9OAEYU0r9K7AEuBPop0bug9b6NaXUF4C9lATcDmCMGrgHWuvLAJRS1iGv65vZMeXsg9b6GeCZ8rEu4OPAJWS4Dxb1tqPIU9INWuSAqZTa4otSqge4l9J29T9wb3sm+6SUugx4Vmv9U9thr7Y6j0MG+kBpIbUe+DCwBvgT4I+pkfuglDoJ2AQcR2kymqSk0qyle2ARdOxkvj9lFfhPge9prR+kBvpQb4LiOUqZEy26ObItzBRKqV5Kg+lKrfWNeLc9q316H/BOpdSjwFeA84DLcG/rS8AblFJWjvw3ko0+DAL3aa33a61HgNsoCY5auQ9nAT/VWr+ktR6lpLpYR23dA4uw4z+T/VFKLadk3L5Ra/3/lA9nvg/1JijuA/5MKdVVNvT9V+DulNs0C6XUYuB24ANa6x+UD/976S11QnngfICSF8szwOGyYAG4ENieeKMdaK3fobX+37TWJwNfBP5Va30pLm0t6/9/Tkm4AFxEBvpASdV0llJqfvman01JX1wr9+ExYL1Sqk0plQPOpaR+qqV7YBFq/GexP0qpecC/AZ/XWn/NOl4LfagrQaG1fp6SzvwB4FHgFq31r9JtlSufAVqAryulHi2vyi8p//djYDclvbNl5Pog8A2l1F6gnZKnS1bxausVlLzQdlMqqvL5lNo3jdb634GvUvJc2U1Jv/xtauQ+aK3/DbgVeBjYRcmYfRU1dA8stNaHCX/ds9afy4A/Aj5tPddKqa+U38t0H6QehSAIgmCkrnYUgiAIQnhEUAiCIAhGRFAIgiAIRkRQCIIgCEZEUAiCIAhGRFAIggGl1NNKqVNDnP8ZpdQNMTZJEBJHBIUgCIJgpN6SAgpCJJRShykFq72TUiqFr2qtv13O8HkN8A5KKRdeBP6z/Jk3AN8EVlEKdvsppbxdJ1JK43CG1vpRpdRNwLjW+sPJ9koQgiE7CkEIRjPwstb6Tymlpv+GUqqFUuTsMmAlJWGxxPaZbwAPa61PoVRb5BjgU1rrPcBngRuVUh+mVCvi44n1RBBCIoJCEILzL+X//5aS4GijlCTwlnLtkEPA/7SdvwH4aDkFy8OUUtqvAtBabwF+Tyl9/HvKSQcFIZOI6kkQgjMCoLUulmsM5MrHc7Zz7KVPC8B7yzsIlFLzKaeNVko1U6p38Z+Uqhj+PtaWC0IFyI5CECpjO3CRUqqlrIp6n+29e4D/SymVKwuGf+WIiulq4HeUbB7XlqucCUImEUEhCJXxD5RqGf+OUgrvp2zv/TUl9dTjlLK3Pg58VSn155TKrH5ca/04JVvGrUop2eELmUSyxwqCIAhGZEchCIIgGBFBIQiCIDeC+DIAAAAySURBVBgRQSEIgiAYEUEhCIIgGBFBIQiCIBgRQSEIgiAYEUEhCIIgGBFBIQiCIBj5/wHUXVTZ/NgKLwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df.index, df['Volume'])\n",
    "plt.xlabel(\"Index\")\n",
    "plt.ylabel(\"Volume\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.6.2. Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>Year</th>\n",
       "      <th>Lag1</th>\n",
       "      <th>Lag2</th>\n",
       "      <th>Lag3</th>\n",
       "      <th>Lag4</th>\n",
       "      <th>Lag5</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Today</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Direction_Up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2001</td>\n",
       "      <td>0.381</td>\n",
       "      <td>-0.192</td>\n",
       "      <td>-2.624</td>\n",
       "      <td>-1.055</td>\n",
       "      <td>5.010</td>\n",
       "      <td>1.1913</td>\n",
       "      <td>0.959</td>\n",
       "      <td>Up</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2001</td>\n",
       "      <td>0.959</td>\n",
       "      <td>0.381</td>\n",
       "      <td>-0.192</td>\n",
       "      <td>-2.624</td>\n",
       "      <td>-1.055</td>\n",
       "      <td>1.2965</td>\n",
       "      <td>1.032</td>\n",
       "      <td>Up</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2001</td>\n",
       "      <td>1.032</td>\n",
       "      <td>0.959</td>\n",
       "      <td>0.381</td>\n",
       "      <td>-0.192</td>\n",
       "      <td>-2.624</td>\n",
       "      <td>1.4112</td>\n",
       "      <td>-0.623</td>\n",
       "      <td>Down</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2001</td>\n",
       "      <td>-0.623</td>\n",
       "      <td>1.032</td>\n",
       "      <td>0.959</td>\n",
       "      <td>0.381</td>\n",
       "      <td>-0.192</td>\n",
       "      <td>1.2760</td>\n",
       "      <td>0.614</td>\n",
       "      <td>Up</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2001</td>\n",
       "      <td>0.614</td>\n",
       "      <td>-0.623</td>\n",
       "      <td>1.032</td>\n",
       "      <td>0.959</td>\n",
       "      <td>0.381</td>\n",
       "      <td>1.2057</td>\n",
       "      <td>0.213</td>\n",
       "      <td>Up</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year   Lag1   Lag2   Lag3   Lag4   Lag5  Volume  Today Direction  \\\n",
       "0  2001  0.381 -0.192 -2.624 -1.055  5.010  1.1913  0.959        Up   \n",
       "1  2001  0.959  0.381 -0.192 -2.624 -1.055  1.2965  1.032        Up   \n",
       "2  2001  1.032  0.959  0.381 -0.192 -2.624  1.4112 -0.623      Down   \n",
       "3  2001 -0.623  1.032  0.959  0.381 -0.192  1.2760  0.614        Up   \n",
       "4  2001  0.614 -0.623  1.032  0.959  0.381  1.2057  0.213        Up   \n",
       "\n",
       "   Direction_Up  \n",
       "0             1  \n",
       "1             1  \n",
       "2             0  \n",
       "3             1  \n",
       "4             1  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert 'Direction' from 'Yes/No' to 0/1. For ease in modeling.\n",
    "df['Direction_Up'] = np.where(df['Direction'] == 'Up', 1, 0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 0.691034\n",
      "         Iterations 4\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Logit Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>   <td>Direction_Up</td>   <th>  No. Observations:  </th>  <td>  1250</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>               <td>Logit</td>      <th>  Df Residuals:      </th>  <td>  1243</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>               <td>MLE</td>       <th>  Df Model:          </th>  <td>     6</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>          <td>Fri, 19 Oct 2018</td> <th>  Pseudo R-squ.:     </th> <td>0.002074</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>              <td>10:24:35</td>     <th>  Log-Likelihood:    </th> <td> -863.79</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>converged:</th>           <td>True</td>       <th>  LL-Null:           </th> <td> -865.59</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th> </th>                      <td> </td>        <th>  LLR p-value:       </th>  <td>0.7319</td> \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>   -0.1260</td> <td>    0.241</td> <td>   -0.523</td> <td> 0.601</td> <td>   -0.598</td> <td>    0.346</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag1</th>      <td>   -0.0731</td> <td>    0.050</td> <td>   -1.457</td> <td> 0.145</td> <td>   -0.171</td> <td>    0.025</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag2</th>      <td>   -0.0423</td> <td>    0.050</td> <td>   -0.845</td> <td> 0.398</td> <td>   -0.140</td> <td>    0.056</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag3</th>      <td>    0.0111</td> <td>    0.050</td> <td>    0.222</td> <td> 0.824</td> <td>   -0.087</td> <td>    0.109</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag4</th>      <td>    0.0094</td> <td>    0.050</td> <td>    0.187</td> <td> 0.851</td> <td>   -0.089</td> <td>    0.107</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag5</th>      <td>    0.0103</td> <td>    0.050</td> <td>    0.208</td> <td> 0.835</td> <td>   -0.087</td> <td>    0.107</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Volume</th>    <td>    0.1354</td> <td>    0.158</td> <td>    0.855</td> <td> 0.392</td> <td>   -0.175</td> <td>    0.446</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                           Logit Regression Results                           \n",
       "==============================================================================\n",
       "Dep. Variable:           Direction_Up   No. Observations:                 1250\n",
       "Model:                          Logit   Df Residuals:                     1243\n",
       "Method:                           MLE   Df Model:                            6\n",
       "Date:                Fri, 19 Oct 2018   Pseudo R-squ.:                0.002074\n",
       "Time:                        10:24:35   Log-Likelihood:                -863.79\n",
       "converged:                       True   LL-Null:                       -865.59\n",
       "                                        LLR p-value:                    0.7319\n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept     -0.1260      0.241     -0.523      0.601      -0.598       0.346\n",
       "Lag1          -0.0731      0.050     -1.457      0.145      -0.171       0.025\n",
       "Lag2          -0.0423      0.050     -0.845      0.398      -0.140       0.056\n",
       "Lag3           0.0111      0.050      0.222      0.824      -0.087       0.109\n",
       "Lag4           0.0094      0.050      0.187      0.851      -0.089       0.107\n",
       "Lag5           0.0103      0.050      0.208      0.835      -0.087       0.107\n",
       "Volume         0.1354      0.158      0.855      0.392      -0.175       0.446\n",
       "==============================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glm = smf.logit('Direction_Up ~ Lag1+Lag2+Lag3+Lag4+Lag5+Volume', data=df).fit()\n",
    "glm.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Access the coefficients of the model\n",
    "\n",
    "Equiv. to `coef()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Intercept   -0.126000\n",
       "Lag1        -0.073074\n",
       "Lag2        -0.042301\n",
       "Lag3         0.011085\n",
       "Lag4         0.009359\n",
       "Lag5         0.010313\n",
       "Volume       0.135441\n",
       "dtype: float64"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glm.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Access p-values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Intercept    0.600700\n",
       "Lag1         0.145232\n",
       "Lag2         0.398352\n",
       "Lag3         0.824334\n",
       "Lag4         0.851445\n",
       "Lag5         0.834998\n",
       "Volume       0.392404\n",
       "dtype: float64"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glm.pvalues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Predict\n",
    "\n",
    "Here, since no data set is supplied to the predict function, then the probabilities are computed for the training data that was used to fit the log reg model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.50708413, 0.48146788, 0.48113883, 0.51522236, 0.51078116,\n",
       "       0.50695646, 0.49265087, 0.50922916, 0.51761353, 0.48883778])"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glm_probs = glm.predict()\n",
    "glm_probs[:10] # get the first 10 values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Up', 'Down', 'Down', ..., 'Up', 'Up', 'Up'], dtype='<U4')"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glm_pred = np.where(glm_probs>.5, 'Up', 'Down')\n",
    "glm_pred"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create confusion matrix\n",
    "\n",
    "We use `crosstab` from pandas. In this case, equiv to `table()`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "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>Actual</th>\n",
       "      <th>Down</th>\n",
       "      <th>Up</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Predicted</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Down</th>\n",
       "      <td>145</td>\n",
       "      <td>141</td>\n",
       "      <td>286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Up</th>\n",
       "      <td>457</td>\n",
       "      <td>507</td>\n",
       "      <td>964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>602</td>\n",
       "      <td>648</td>\n",
       "      <td>1250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Actual     Down   Up   All\n",
       "Predicted                 \n",
       "Down        145  141   286\n",
       "Up          457  507   964\n",
       "All         602  648  1250"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(glm_pred, df['Direction'], rownames=['Predicted'],\n",
    "           colnames=['Actual'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5216\n"
     ]
    }
   ],
   "source": [
    "print((507+145)/1250)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Up      0.5184\n",
       "Down    0.4816\n",
       "Name: Direction, dtype: float64"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Direction.value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array(['Down', 'Up'], dtype='<U4'), array([286, 964]))"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(glm_pred, return_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2005    252\n",
       "2004    252\n",
       "2003    252\n",
       "2002    252\n",
       "2001    242\n",
       "Name: Year, dtype: int64"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Year.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of train: (998, 10)\n",
      "Shape of test: (252, 10)\n"
     ]
    }
   ],
   "source": [
    "df_train = df.loc[df['Year'] != 2005]\n",
    "df_test = df.loc[df['Year'] == 2005]\n",
    "\n",
    "print(\"Shape of train: \" + str(df_train.shape))\n",
    "print(\"Shape of test: \" + str(df_test.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Fit a logisitic regression with train, predict on test."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 0.691936\n",
      "         Iterations 4\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Logit Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>   <td>Direction_Up</td>   <th>  No. Observations:  </th>  <td>   998</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>               <td>Logit</td>      <th>  Df Residuals:      </th>  <td>   991</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>               <td>MLE</td>       <th>  Df Model:          </th>  <td>     6</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>          <td>Mon, 22 Oct 2018</td> <th>  Pseudo R-squ.:     </th> <td>0.001562</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>              <td>09:13:29</td>     <th>  Log-Likelihood:    </th> <td> -690.55</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>converged:</th>           <td>True</td>       <th>  LL-Null:           </th> <td> -691.63</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th> </th>                      <td> </td>        <th>  LLR p-value:       </th>  <td>0.9044</td> \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    0.1912</td> <td>    0.334</td> <td>    0.573</td> <td> 0.567</td> <td>   -0.463</td> <td>    0.845</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag1</th>      <td>   -0.0542</td> <td>    0.052</td> <td>   -1.046</td> <td> 0.295</td> <td>   -0.156</td> <td>    0.047</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag2</th>      <td>   -0.0458</td> <td>    0.052</td> <td>   -0.884</td> <td> 0.377</td> <td>   -0.147</td> <td>    0.056</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag3</th>      <td>    0.0072</td> <td>    0.052</td> <td>    0.139</td> <td> 0.889</td> <td>   -0.094</td> <td>    0.108</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag4</th>      <td>    0.0064</td> <td>    0.052</td> <td>    0.125</td> <td> 0.901</td> <td>   -0.095</td> <td>    0.108</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Lag5</th>      <td>   -0.0042</td> <td>    0.051</td> <td>   -0.083</td> <td> 0.934</td> <td>   -0.104</td> <td>    0.096</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Volume</th>    <td>   -0.1163</td> <td>    0.240</td> <td>   -0.485</td> <td> 0.628</td> <td>   -0.586</td> <td>    0.353</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                           Logit Regression Results                           \n",
       "==============================================================================\n",
       "Dep. Variable:           Direction_Up   No. Observations:                  998\n",
       "Model:                          Logit   Df Residuals:                      991\n",
       "Method:                           MLE   Df Model:                            6\n",
       "Date:                Mon, 22 Oct 2018   Pseudo R-squ.:                0.001562\n",
       "Time:                        09:13:29   Log-Likelihood:                -690.55\n",
       "converged:                       True   LL-Null:                       -691.63\n",
       "                                        LLR p-value:                    0.9044\n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept      0.1912      0.334      0.573      0.567      -0.463       0.845\n",
       "Lag1          -0.0542      0.052     -1.046      0.295      -0.156       0.047\n",
       "Lag2          -0.0458      0.052     -0.884      0.377      -0.147       0.056\n",
       "Lag3           0.0072      0.052      0.139      0.889      -0.094       0.108\n",
       "Lag4           0.0064      0.052      0.125      0.901      -0.095       0.108\n",
       "Lag5          -0.0042      0.051     -0.083      0.934      -0.104       0.096\n",
       "Volume        -0.1163      0.240     -0.485      0.628      -0.586       0.353\n",
       "==============================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glm = smf.logit('Direction_Up ~ Lag1+Lag2+Lag3+Lag4+Lag5+Volume', \n",
    "               data=df_train).fit()\n",
    "glm.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "998     0.528220\n",
       "999     0.515669\n",
       "1000    0.522652\n",
       "1001    0.513854\n",
       "1002    0.498334\n",
       "1003    0.501091\n",
       "1004    0.502770\n",
       "1005    0.509568\n",
       "1006    0.504011\n",
       "1007    0.510641\n",
       "dtype: float64"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "glm_probs = glm.predict(df_test)\n",
    "glm_probs[:10] # see the first 10 probs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(252,)"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert probs to predictions ('Up'/'Down')\n",
    "glm_pred = np.where(glm_probs>.5, 'Up', 'Down')\n",
    "glm_pred.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "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>Actual</th>\n",
       "      <th>Down</th>\n",
       "      <th>Up</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Predicted</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Down</th>\n",
       "      <td>77</td>\n",
       "      <td>97</td>\n",
       "      <td>174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Up</th>\n",
       "      <td>34</td>\n",
       "      <td>44</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>111</td>\n",
       "      <td>141</td>\n",
       "      <td>252</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Actual     Down   Up  All\n",
       "Predicted                \n",
       "Down         77   97  174\n",
       "Up           34   44   78\n",
       "All         111  141  252"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(glm_pred, df_test['Direction'], rownames=['Predicted'],\n",
    "           colnames=['Actual'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.4801587301587302"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# accuracy\n",
    "(77+44)/252"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5198412698412699"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# test error rate\n",
    "(34+97)/252"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [],
   "source": [
    "smf.logit?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Up      0.508016\n",
       "Down    0.491984\n",
       "Name: Direction, dtype: float64"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.Direction.value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.6.3 Linear Discriminant Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Good [reference](https://www.shanelynn.ie/select-pandas-dataframe-rows-and-columns-using-iloc-loc-and-ix/) for loc and iloc for subsetting dataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train = df_train.loc[:,'Direction']\n",
    "x_train = df_train.loc[:,('Lag1','Lag2')]\n",
    "\n",
    "y_test = df_test.loc[:,'Direction']\n",
    "x_test = df_test.loc[:,('Lag1','Lag2')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = LDA()\n",
    "lda_fit = clf.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.49198397, 0.50801603])"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prior probabilities of groups:\n",
    "lda_fit.priors_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.04279022,  0.03389409],\n",
       "       [-0.03954635, -0.03132544]])"
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group means:\n",
    "lda_fit.means_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.05544078, -0.0443452 ]])"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Coefficients of linear discriminants (doesn't match R or book for some reason)\n",
    "lda_fit.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "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>Actual</th>\n",
       "      <th>Down</th>\n",
       "      <th>Up</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Predicted</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Down</th>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Up</th>\n",
       "      <td>76</td>\n",
       "      <td>106</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>111</td>\n",
       "      <td>141</td>\n",
       "      <td>252</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Actual     Down   Up  All\n",
       "Predicted                \n",
       "Down         35   35   70\n",
       "Up           76  106  182\n",
       "All         111  141  252"
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(lda_fit.predict(x_test), df_test['Direction'], rownames=['Predicted'],\n",
    "           colnames=['Actual'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5595238095238095"
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# accuracy\n",
    "(35+106)/252"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.44047619047619047"
      ]
     },
     "execution_count": 242,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# error rate\n",
    "(76+35)/252\n",
    "#1-((35+106)/252) # can also use 1-accuracy as error rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [],
   "source": [
    "lda_pred = lda_fit.predict_proba(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 70, 182])"
      ]
     },
     "execution_count": 251,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# .5 threshold\n",
    "sum(lda_pred>.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 70, 182])"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# can calculate straight from predict_proba\n",
    "sum(lda_fit.predict_proba(x_test)>.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0])"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# .9 threshold\n",
    "sum(lda_fit.predict_proba(x_test)>.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.6.4 Quadratic Discriminant Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis as QDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "QuadraticDiscriminantAnalysis(priors=None, reg_param=0.0,\n",
       "               store_covariance=False, store_covariances=None, tol=0.0001)"
      ]
     },
     "execution_count": 273,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = QDA()\n",
    "clf.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.49198397, 0.50801603])"
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Prior probabilites of groups:\n",
    "clf.priors_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.04279022,  0.03389409],\n",
       "       [-0.03954635, -0.03132544]])"
      ]
     },
     "execution_count": 279,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Group means\n",
    "clf.means_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "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>Actual</th>\n",
       "      <th>Down</th>\n",
       "      <th>Up</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Predicted</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Down</th>\n",
       "      <td>30</td>\n",
       "      <td>20</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Up</th>\n",
       "      <td>81</td>\n",
       "      <td>121</td>\n",
       "      <td>202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>111</td>\n",
       "      <td>141</td>\n",
       "      <td>252</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Actual     Down   Up  All\n",
       "Predicted                \n",
       "Down         30   20   50\n",
       "Up           81  121  202\n",
       "All         111  141  252"
      ]
     },
     "execution_count": 280,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(clf.predict(x_test), df_test['Direction'], rownames=['Predicted'],\n",
    "           colnames=['Actual'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5992063492063492\n",
      "0.4007936507936508\n"
     ]
    }
   ],
   "source": [
    "# accuracy\n",
    "print((30+121)/252)\n",
    "# error rate\n",
    "print(1-((30+121)/252))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.6.5 K-Nearest Neighbors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier as KNNc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "           metric_params=None, n_jobs=1, n_neighbors=1, p=2,\n",
       "           weights='uniform')"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neigh = KNNc(n_neighbors=1)\n",
    "neigh.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "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>Actual</th>\n",
       "      <th>Down</th>\n",
       "      <th>Up</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Predicted</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Down</th>\n",
       "      <td>43</td>\n",
       "      <td>58</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Up</th>\n",
       "      <td>68</td>\n",
       "      <td>83</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>111</td>\n",
       "      <td>141</td>\n",
       "      <td>252</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Actual     Down   Up  All\n",
       "Predicted                \n",
       "Down         43   58  101\n",
       "Up           68   83  151\n",
       "All         111  141  252"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(neigh.predict(x_test), df_test['Direction'], rownames=['Predicted'],\n",
    "           colnames=['Actual'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5"
      ]
     },
     "execution_count": 287,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# accuracy\n",
    "(43+83)/252"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "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>Actual</th>\n",
       "      <th>Down</th>\n",
       "      <th>Up</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Predicted</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Down</th>\n",
       "      <td>48</td>\n",
       "      <td>55</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Up</th>\n",
       "      <td>63</td>\n",
       "      <td>86</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>111</td>\n",
       "      <td>141</td>\n",
       "      <td>252</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Actual     Down   Up  All\n",
       "Predicted                \n",
       "Down         48   55  103\n",
       "Up           63   86  149\n",
       "All         111  141  252"
      ]
     },
     "execution_count": 288,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# increase k=3\n",
    "neigh = KNNc(n_neighbors=3)\n",
    "neigh.fit(x_train, y_train)\n",
    "\n",
    "pd.crosstab(neigh.predict(x_test), df_test['Direction'], rownames=['Predicted'],\n",
    "           colnames=['Actual'], margins=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4.6.6 An Application to Caravan Insurance Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/JWarmenhoven/ISLR-python/master/Notebooks/Data/Caravan.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape of df: (5822, 86)\n"
     ]
    },
    {
     "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>MOSTYPE</th>\n",
       "      <th>MAANTHUI</th>\n",
       "      <th>MGEMOMV</th>\n",
       "      <th>MGEMLEEF</th>\n",
       "      <th>MOSHOOFD</th>\n",
       "      <th>MGODRK</th>\n",
       "      <th>MGODPR</th>\n",
       "      <th>MGODOV</th>\n",
       "      <th>MGODGE</th>\n",
       "      <th>MRELGE</th>\n",
       "      <th>...</th>\n",
       "      <th>APERSONG</th>\n",
       "      <th>AGEZONG</th>\n",
       "      <th>AWAOREG</th>\n",
       "      <th>ABRAND</th>\n",
       "      <th>AZEILPL</th>\n",
       "      <th>APLEZIER</th>\n",
       "      <th>AFIETS</th>\n",
       "      <th>AINBOED</th>\n",
       "      <th>ABYSTAND</th>\n",
       "      <th>Purchase</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>37</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 86 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   MOSTYPE  MAANTHUI  MGEMOMV  MGEMLEEF  MOSHOOFD  MGODRK  MGODPR  MGODOV  \\\n",
       "0       33         1        3         2         8       0       5       1   \n",
       "1       37         1        2         2         8       1       4       1   \n",
       "2       37         1        2         2         8       0       4       2   \n",
       "3        9         1        3         3         3       2       3       2   \n",
       "4       40         1        4         2        10       1       4       1   \n",
       "\n",
       "   MGODGE  MRELGE    ...     APERSONG  AGEZONG  AWAOREG  ABRAND  AZEILPL  \\\n",
       "0       3       7    ...            0        0        0       1        0   \n",
       "1       4       6    ...            0        0        0       1        0   \n",
       "2       4       3    ...            0        0        0       1        0   \n",
       "3       4       5    ...            0        0        0       1        0   \n",
       "4       4       7    ...            0        0        0       1        0   \n",
       "\n",
       "   APLEZIER  AFIETS  AINBOED  ABYSTAND  Purchase  \n",
       "0         0       0        0         0        No  \n",
       "1         0       0        0         0        No  \n",
       "2         0       0        0         0        No  \n",
       "3         0       0        0         0        No  \n",
       "4         0       0        0         0        No  \n",
       "\n",
       "[5 rows x 86 columns]"
      ]
     },
     "execution_count": 293,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=df.drop(columns=['Unnamed: 0'])\n",
    "print(\"shape of df: \" + str(df.shape))\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "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>MOSTYPE</th>\n",
       "      <th>MAANTHUI</th>\n",
       "      <th>MGEMOMV</th>\n",
       "      <th>MGEMLEEF</th>\n",
       "      <th>MOSHOOFD</th>\n",
       "      <th>MGODRK</th>\n",
       "      <th>MGODPR</th>\n",
       "      <th>MGODOV</th>\n",
       "      <th>MGODGE</th>\n",
       "      <th>MRELGE</th>\n",
       "      <th>...</th>\n",
       "      <th>ALEVEN</th>\n",
       "      <th>APERSONG</th>\n",
       "      <th>AGEZONG</th>\n",
       "      <th>AWAOREG</th>\n",
       "      <th>ABRAND</th>\n",
       "      <th>AZEILPL</th>\n",
       "      <th>APLEZIER</th>\n",
       "      <th>AFIETS</th>\n",
       "      <th>AINBOED</th>\n",
       "      <th>ABYSTAND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "      <td>5822.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>24.253349</td>\n",
       "      <td>1.110615</td>\n",
       "      <td>2.678805</td>\n",
       "      <td>2.991240</td>\n",
       "      <td>5.773617</td>\n",
       "      <td>0.696496</td>\n",
       "      <td>4.626932</td>\n",
       "      <td>1.069907</td>\n",
       "      <td>3.258502</td>\n",
       "      <td>6.183442</td>\n",
       "      <td>...</td>\n",
       "      <td>0.076606</td>\n",
       "      <td>0.005325</td>\n",
       "      <td>0.006527</td>\n",
       "      <td>0.004638</td>\n",
       "      <td>0.570079</td>\n",
       "      <td>0.000515</td>\n",
       "      <td>0.006012</td>\n",
       "      <td>0.031776</td>\n",
       "      <td>0.007901</td>\n",
       "      <td>0.014256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>12.846706</td>\n",
       "      <td>0.405842</td>\n",
       "      <td>0.789835</td>\n",
       "      <td>0.814589</td>\n",
       "      <td>2.856760</td>\n",
       "      <td>1.003234</td>\n",
       "      <td>1.715843</td>\n",
       "      <td>1.017503</td>\n",
       "      <td>1.597647</td>\n",
       "      <td>1.909482</td>\n",
       "      <td>...</td>\n",
       "      <td>0.377569</td>\n",
       "      <td>0.072782</td>\n",
       "      <td>0.080532</td>\n",
       "      <td>0.077403</td>\n",
       "      <td>0.562058</td>\n",
       "      <td>0.022696</td>\n",
       "      <td>0.081632</td>\n",
       "      <td>0.210986</td>\n",
       "      <td>0.090463</td>\n",
       "      <td>0.119996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>35.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 85 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           MOSTYPE     MAANTHUI      MGEMOMV     MGEMLEEF     MOSHOOFD  \\\n",
       "count  5822.000000  5822.000000  5822.000000  5822.000000  5822.000000   \n",
       "mean     24.253349     1.110615     2.678805     2.991240     5.773617   \n",
       "std      12.846706     0.405842     0.789835     0.814589     2.856760   \n",
       "min       1.000000     1.000000     1.000000     1.000000     1.000000   \n",
       "25%      10.000000     1.000000     2.000000     2.000000     3.000000   \n",
       "50%      30.000000     1.000000     3.000000     3.000000     7.000000   \n",
       "75%      35.000000     1.000000     3.000000     3.000000     8.000000   \n",
       "max      41.000000    10.000000     5.000000     6.000000    10.000000   \n",
       "\n",
       "            MGODRK       MGODPR       MGODOV       MGODGE       MRELGE  \\\n",
       "count  5822.000000  5822.000000  5822.000000  5822.000000  5822.000000   \n",
       "mean      0.696496     4.626932     1.069907     3.258502     6.183442   \n",
       "std       1.003234     1.715843     1.017503     1.597647     1.909482   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.000000     4.000000     0.000000     2.000000     5.000000   \n",
       "50%       0.000000     5.000000     1.000000     3.000000     6.000000   \n",
       "75%       1.000000     6.000000     2.000000     4.000000     7.000000   \n",
       "max       9.000000     9.000000     5.000000     9.000000     9.000000   \n",
       "\n",
       "          ...            ALEVEN     APERSONG      AGEZONG      AWAOREG  \\\n",
       "count     ...       5822.000000  5822.000000  5822.000000  5822.000000   \n",
       "mean      ...          0.076606     0.005325     0.006527     0.004638   \n",
       "std       ...          0.377569     0.072782     0.080532     0.077403   \n",
       "min       ...          0.000000     0.000000     0.000000     0.000000   \n",
       "25%       ...          0.000000     0.000000     0.000000     0.000000   \n",
       "50%       ...          0.000000     0.000000     0.000000     0.000000   \n",
       "75%       ...          0.000000     0.000000     0.000000     0.000000   \n",
       "max       ...          8.000000     1.000000     1.000000     2.000000   \n",
       "\n",
       "            ABRAND      AZEILPL     APLEZIER       AFIETS      AINBOED  \\\n",
       "count  5822.000000  5822.000000  5822.000000  5822.000000  5822.000000   \n",
       "mean      0.570079     0.000515     0.006012     0.031776     0.007901   \n",
       "std       0.562058     0.022696     0.081632     0.210986     0.090463   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "50%       1.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "75%       1.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "max       7.000000     1.000000     2.000000     3.000000     2.000000   \n",
       "\n",
       "          ABYSTAND  \n",
       "count  5822.000000  \n",
       "mean      0.014256  \n",
       "std       0.119996  \n",
       "min       0.000000  \n",
       "25%       0.000000  \n",
       "50%       0.000000  \n",
       "75%       0.000000  \n",
       "max       2.000000  \n",
       "\n",
       "[8 rows x 85 columns]"
      ]
     },
     "execution_count": 384,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "No     0.940227\n",
       "Yes    0.059773\n",
       "Name: Purchase, dtype: float64"
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# only 6% purchase\n",
    "df.Purchase.value_counts(normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.05977327378907592"
      ]
     },
     "execution_count": 296,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Purchase.value_counts(normalize=True)[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [],
   "source": [
    "# standardize our data\n",
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = df.Purchase\n",
    "x = df.drop('Purchase', axis=1).astype('float64')\n",
    "standardize_X = preprocessing.scale(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now that our data has been standardized, let's examine to ensure columns have a standard deviation of one and a mean zero"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 380,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# standard deviation\n",
    "standardize_X.std(axis=0)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-7.749822006315075e-17"
      ]
     },
     "execution_count": 381,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mean\n",
    "# essentially zero\n",
    "standardize_X.mean(axis=0)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12.84670570205407\n",
      "24.25334936447956\n"
     ]
    }
   ],
   "source": [
    "# check our pre-standardized data\n",
    "print(df.std(axis=0)[0])\n",
    "print(df.mean(axis=0)[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "165.03784739518855\n",
      "1.0000000000000002\n"
     ]
    }
   ],
   "source": [
    "# in the book they use variance (squared std dev)\n",
    "print(df.var(axis=0)[0])\n",
    "print(standardize_X.var(axis=0)[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train = standardize_X[1000:,:]\n",
    "y_train = y[1000:]\n",
    "x_test = standardize_X[:1000,:]\n",
    "y_test = y[:1000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "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>Actual</th>\n",
       "      <th>No</th>\n",
       "      <th>Yes</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Predicted</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>873</td>\n",
       "      <td>50</td>\n",
       "      <td>923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>68</td>\n",
       "      <td>9</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>941</td>\n",
       "      <td>59</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Actual      No  Yes   All\n",
       "Predicted                \n",
       "No         873   50   923\n",
       "Yes         68    9    77\n",
       "All        941   59  1000"
      ]
     },
     "execution_count": 374,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neigh = KNNc(n_neighbors=1)\n",
    "neigh.fit(x_train, y_train)\n",
    "\n",
    "pd.crosstab(neigh.predict(x_test), y_test, rownames=['Predicted'],\n",
    "           colnames=['Actual'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 375,
   "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>Actual</th>\n",
       "      <th>No</th>\n",
       "      <th>Yes</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Predicted</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>No</th>\n",
       "      <td>921</td>\n",
       "      <td>54</td>\n",
       "      <td>975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yes</th>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>941</td>\n",
       "      <td>59</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Actual      No  Yes   All\n",
       "Predicted                \n",
       "No         921   54   975\n",
       "Yes         20    5    25\n",
       "All        941   59  1000"
      ]
     },
     "execution_count": 375,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# increase nn to 3\n",
    "neigh = KNNc(n_neighbors=3)\n",
    "neigh.fit(x_train, y_train)\n",
    "\n",
    "pd.crosstab(neigh.predict(x_test), y_test, rownames=['Predicted'],\n",
    "           colnames=['Actual'], margins=True)"
   ]
  }
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