0.85pub_0.69priv_final.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "from sklearn.preprocessing import LabelEncoder, MinMaxScaler\n",
    "from sklearn.model_selection import cross_val_score, StratifiedKFold\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix\n",
    "from scipy import stats\n",
    "import math\n",
    "from sklearn.linear_model import LogisticRegression, Ridge, Lasso, ElasticNet\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, BaggingClassifier, ExtraTreesClassifier, GradientBoostingClassifier, VotingClassifier\n",
    "import lightgbm as lgb\n",
    "import xgboost as xgb\n",
    "import gc\n",
    "import itertools\n",
    "from tsfresh.feature_extraction.feature_calculators import kurtosis, skewness, mean_abs_change, mean_change, sample_entropy, abs_energy, absolute_sum_of_changes, quantile\n",
    "from tsfresh.feature_selection.selection import select_features\n",
    "from scipy.stats import mode\n",
    "from rgf.sklearn import RGFClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_X shape: (3810, 128, 10) , test_X shape: (3816, 128, 10)\n"
     ]
    }
   ],
   "source": [
    "train_orig = pd.read_csv(\"X_train.csv\")\n",
    "train = train_orig\n",
    "test_orig = pd.read_csv(\"X_test.csv\")\n",
    "test = test_orig\n",
    "label_orig = pd.read_csv(\"y_train.csv\")\n",
    "label = label_orig\n",
    "sub_orig = pd.read_csv(\"sample_submission.csv\")\n",
    "sub = sub_orig\n",
    "train_X = train.iloc[:,3:].values.reshape(-1,128,10)\n",
    "test_X  = test.iloc[:,3:].values.reshape(-1,128,10)\n",
    "print('train_X shape:', train_X.shape, ', test_X shape:', test_X.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Convert to numbers:  {'fine_concrete': 0, 'concrete': 1, 'soft_tiles': 2, 'tiled': 3, 'soft_pvc': 4, 'hard_tiles_large_space': 5, 'carpet': 6, 'hard_tiles': 7, 'wood': 8}\n"
     ]
    }
   ],
   "source": [
    "df_train_y = pd.read_csv('y_train.csv')\n",
    "\n",
    "# build a dict to convert surface names into numbers\n",
    "surface_names = df_train_y['surface'].unique()\n",
    "num_surfaces = len(surface_names)\n",
    "surface_to_numeric = dict(zip(surface_names, range(num_surfaces)))\n",
    "print('Convert to numbers: ', surface_to_numeric)\n",
    "\n",
    "# y and group data as numeric values:\n",
    "train_y = df_train_y['surface'].replace(surface_to_numeric).values\n",
    "train_group = df_train_y['group_id'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sq_dist(a,b):\n",
    "    ''' the squared euclidean distance between two samples '''\n",
    "    \n",
    "    return np.sum((a-b)**2, axis=1)\n",
    "\n",
    "\n",
    "def find_run_edges(data, edge):\n",
    "    ''' examine links between samples. left/right run edges are those samples which do not have a link on that side. '''\n",
    "\n",
    "    if edge == 'left':\n",
    "        border1 = 0\n",
    "        border2 = -1\n",
    "    elif edge == 'right':\n",
    "        border1 = -1\n",
    "        border2 = 0\n",
    "    else:\n",
    "        return False\n",
    "    \n",
    "    edge_list = []\n",
    "    linked_list = []\n",
    "    \n",
    "    for i in range(len(data)):\n",
    "        dist_list = sq_dist(data[i, border1, :4], data[:, border2, :4]) # distances to rest of samples\n",
    "        min_dist = np.min(dist_list)\n",
    "        closest_i   = np.argmin(dist_list) # this is i's closest neighbor\n",
    "        if closest_i == i: # this might happen and it's definitely wrong\n",
    "            print('Sample', i, 'linked with itself. Next closest sample used instead.')\n",
    "            closest_i = np.argsort(dist_list)[1]\n",
    "        dist_list = sq_dist(data[closest_i, border2, :4], data[:, border1, :4]) # now find closest_i's closest neighbor\n",
    "        rev_dist = np.min(dist_list)\n",
    "        closest_rev = np.argmin(dist_list) # here it is\n",
    "        if closest_rev == closest_i: # again a check\n",
    "            print('Sample', i, '(back-)linked with itself. Next closest sample used instead.')\n",
    "            closest_rev = np.argsort(dist_list)[1]\n",
    "        if (i != closest_rev): # we found an edge\n",
    "            edge_list.append(i)\n",
    "        else:\n",
    "            linked_list.append([i, closest_i, min_dist])\n",
    "            \n",
    "    return edge_list, linked_list\n",
    "\n",
    "\n",
    "def find_runs(data, left_edges, right_edges):\n",
    "    ''' go through the list of samples & link the closest neighbors into a single run '''\n",
    "    \n",
    "    data_runs = []\n",
    "\n",
    "    for start_point in left_edges:\n",
    "        i = start_point\n",
    "        run_list = [i]\n",
    "        while i not in right_edges:\n",
    "            tmp = np.argmin(sq_dist(data[i, -1, :4], data[:, 0, :4]))\n",
    "            if tmp == i: # self-linked sample\n",
    "                tmp = np.argsort(sq_dist(data[i, -1, :4], data[:, 0, :4]))[1]\n",
    "            i = tmp\n",
    "            run_list.append(i)\n",
    "        data_runs.append(np.array(run_list))\n",
    "    \n",
    "    return data_runs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample 1 (back-)linked with itself. Next closest sample used instead.\n",
      "Sample 216 linked with itself. Next closest sample used instead.\n",
      "Sample 335 linked with itself. Next closest sample used instead.\n",
      "Sample 748 (back-)linked with itself. Next closest sample used instead.\n",
      "Sample 799 linked with itself. Next closest sample used instead.\n",
      "Sample 1205 linked with itself. Next closest sample used instead.\n",
      "Sample 1913 linked with itself. Next closest sample used instead.\n",
      "Sample 1986 linked with itself. Next closest sample used instead.\n",
      "Sample 2555 linked with itself. Next closest sample used instead.\n",
      "Sample 2612 linked with itself. Next closest sample used instead.\n",
      "Sample 2761 linked with itself. Next closest sample used instead.\n",
      "Sample 2917 linked with itself. Next closest sample used instead.\n",
      "Sample 3312 linked with itself. Next closest sample used instead.\n",
      "Sample 181 linked with itself. Next closest sample used instead.\n",
      "Sample 272 linked with itself. Next closest sample used instead.\n",
      "Sample 464 linked with itself. Next closest sample used instead.\n",
      "Sample 851 linked with itself. Next closest sample used instead.\n",
      "Sample 990 linked with itself. Next closest sample used instead.\n",
      "Sample 1179 linked with itself. Next closest sample used instead.\n",
      "Sample 1334 linked with itself. Next closest sample used instead.\n",
      "Sample 1584 linked with itself. Next closest sample used instead.\n",
      "Sample 1679 linked with itself. Next closest sample used instead.\n",
      "Sample 1730 linked with itself. Next closest sample used instead.\n",
      "Sample 1860 linked with itself. Next closest sample used instead.\n",
      "Sample 2567 linked with itself. Next closest sample used instead.\n",
      "Sample 2720 linked with itself. Next closest sample used instead.\n",
      "Sample 3005 linked with itself. Next closest sample used instead.\n",
      "Found 76 left edges and 76 right edges.\n"
     ]
    }
   ],
   "source": [
    "train_left_edges, train_left_linked  = find_run_edges(train_X, edge='left')\n",
    "train_right_edges, train_right_linked = find_run_edges(train_X, edge='right')\n",
    "print('Found', len(train_left_edges), 'left edges and', len(train_right_edges), 'right edges.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_runs = find_runs(train_X, train_left_edges, train_right_edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3810 3810\n"
     ]
    }
   ],
   "source": [
    "flat_list = [series_id for run in train_runs for series_id in run]\n",
    "print(len(flat_list), len(np.unique(flat_list)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1]\n"
     ]
    }
   ],
   "source": [
    "print([len(np.unique(train_y[run])) for run in train_runs ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2, 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 1, 1, 2, 1, 2, 1, 2, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 3, 2, 1, 1, 3, 2, 1, 1, 1, 2, 1, 1, 2, 1, 2, 1, 2, 1, 1, 4, 1, 1, 2, 1, 1, 2, 1, 1, 1, 3, 1, 2, 1, 1, 1, 1]\n"
     ]
    }
   ],
   "source": [
    "print([len(np.unique(train_group[run])) for run in train_runs ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>series_id</th>\n",
       "      <th>group_id</th>\n",
       "      <th>surface</th>\n",
       "      <th>run_id</th>\n",
       "      <th>run_pos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3805</th>\n",
       "      <td>3805</td>\n",
       "      <td>55</td>\n",
       "      <td>tiled</td>\n",
       "      <td>46</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3806</th>\n",
       "      <td>3806</td>\n",
       "      <td>67</td>\n",
       "      <td>wood</td>\n",
       "      <td>74</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3807</th>\n",
       "      <td>3807</td>\n",
       "      <td>48</td>\n",
       "      <td>fine_concrete</td>\n",
       "      <td>65</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3808</th>\n",
       "      <td>3808</td>\n",
       "      <td>54</td>\n",
       "      <td>tiled</td>\n",
       "      <td>54</td>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3809</th>\n",
       "      <td>3809</td>\n",
       "      <td>56</td>\n",
       "      <td>soft_pvc</td>\n",
       "      <td>69</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      series_id  group_id        surface  run_id  run_pos\n",
       "3805       3805        55          tiled      46        4\n",
       "3806       3806        67           wood      74        2\n",
       "3807       3807        48  fine_concrete      65       57\n",
       "3808       3808        54          tiled      54       97\n",
       "3809       3809        56       soft_pvc      69      123"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train_y['run_id'] = 0\n",
    "df_train_y['run_pos'] = 0\n",
    "\n",
    "for run_id in range(len(train_runs)):\n",
    "    for run_pos in range(len(train_runs[run_id])):\n",
    "        series_id = train_runs[run_id][run_pos]\n",
    "        df_train_y.at[ series_id, 'run_id'  ] = run_id\n",
    "        df_train_y.at[ series_id, 'run_pos' ] = run_pos\n",
    "\n",
    "df_train_y.to_csv('y_train_with_runs.csv', index=False)\n",
    "df_train_y.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train_y.drop(columns=['series_id', 'group_id', 'surface']).to_csv('y_train_with_groups.csv', index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([21, 32,  5, 12, 31, 24,  9, 18, 22,  8, 17, 28, 26,  0, 14, 27, 10,\n",
       "       25, 11, 23,  1, 30,  2,  4,  6, 29, 20, 19,  7, 13,  3, 15, 16, 69,\n",
       "       75, 43, 64, 58, 63, 47, 45, 49, 59, 65, 57, 41, 60, 44, 56, 40, 73,\n",
       "       46, 68, 53, 33, 72, 38, 66, 54, 48, 62, 61, 50, 51, 35, 34, 39, 37,\n",
       "       36, 52, 42, 55, 71, 67, 74, 70], dtype=int64)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train_y['run_id'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample 355 linked with itself. Next closest sample used instead.\n",
      "Sample 580 linked with itself. Next closest sample used instead.\n",
      "Sample 1402 linked with itself. Next closest sample used instead.\n",
      "Sample 1547 linked with itself. Next closest sample used instead.\n",
      "Sample 1716 linked with itself. Next closest sample used instead.\n",
      "Sample 2136 (back-)linked with itself. Next closest sample used instead.\n",
      "Sample 2474 linked with itself. Next closest sample used instead.\n",
      "Sample 2495 (back-)linked with itself. Next closest sample used instead.\n",
      "Sample 2600 linked with itself. Next closest sample used instead.\n",
      "Sample 2922 linked with itself. Next closest sample used instead.\n",
      "Sample 580 linked with itself. Next closest sample used instead.\n",
      "Sample 1216 linked with itself. Next closest sample used instead.\n",
      "Sample 1409 linked with itself. Next closest sample used instead.\n",
      "Sample 1410 linked with itself. Next closest sample used instead.\n",
      "Sample 1670 linked with itself. Next closest sample used instead.\n",
      "Sample 1700 linked with itself. Next closest sample used instead.\n",
      "Sample 2650 linked with itself. Next closest sample used instead.\n",
      "Sample 2864 linked with itself. Next closest sample used instead.\n",
      "Sample 3332 linked with itself. Next closest sample used instead.\n",
      "Sample 3397 linked with itself. Next closest sample used instead.\n",
      "Found 75 left edges and 75 right edges.\n"
     ]
    }
   ],
   "source": [
    "test_left_edges, test_left_linked  = find_run_edges(test_X, edge='left')\n",
    "test_right_edges, test_right_linked = find_run_edges(test_X, edge='right')\n",
    "print('Found', len(test_left_edges), 'left edges and', len(test_right_edges), 'right edges.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_runs = find_runs(test_X, test_left_edges, test_right_edges)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3790 3790\n"
     ]
    }
   ],
   "source": [
    "flat_list = [series_id for run in test_runs for series_id in run]\n",
    "print(len(flat_list), len(np.unique(flat_list)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 264  361  529  620  733  954 1148 1248 1432 1534 1570 1738 1739 2090\n",
      " 2205 2714 2847 2978 2991 3115 3173 3183 3195 3359 3517 3655]\n",
      "26\n"
     ]
    }
   ],
   "source": [
    "lost_samples = np.array([ i for i in range(len(test_X)) if i not in np.concatenate(test_runs) ])\n",
    "print(lost_samples)\n",
    "print(len(lost_samples))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 5, 2.0548399999999954e-07]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "find_run_edges(test_X[lost_samples], edge='left')[1][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "lost_run = np.array(lost_samples[find_runs(test_X[lost_samples], [0], [5])[0]])\n",
    "test_runs.append(lost_run)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3816 3816\n"
     ]
    }
   ],
   "source": [
    "flat_list = [series_id for run in test_runs for series_id in run]\n",
    "print(len(flat_list), len(np.unique(flat_list)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test_y = pd.DataFrame()\n",
    "df_test_y['run_id'] = 0\n",
    "df_test_y['run_pos'] = 0\n",
    "\n",
    "for run_id in range(len(test_runs)):\n",
    "    for run_pos in range(len(test_runs[run_id])):\n",
    "        series_id = test_runs[run_id][run_pos]\n",
    "        df_test_y.at[ series_id, 'run_id'  ] = run_id\n",
    "        df_test_y.at[ series_id, 'run_pos' ] = run_pos\n",
    "\n",
    "df_test_y.to_csv('y_test_with_runs.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test_y.to_csv(\"df_test_y_grouped.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def reduce_mem_usage(df):\n",
    "    # iterate through all the columns of a dataframe and modify the data type\n",
    "    #   to reduce memory usage.        \n",
    "    \n",
    "    start_mem = df.memory_usage().sum() / 1024**2\n",
    "    print('Memory usage of dataframe is {:.2f} MB'.format(start_mem))\n",
    "\n",
    "    for col in df.columns:\n",
    "        col_type = df[col].dtype\n",
    "\n",
    "        if col_type != object:\n",
    "            c_min = df[col].min()\n",
    "            c_max = df[col].max()\n",
    "            if str(col_type)[:3] == 'int':\n",
    "                if c_min > np.iinfo(np.int8).min and c_max < np.iinfo(np.int8).max:\n",
    "                    df[col] = df[col].astype(np.int8)\n",
    "                elif c_min > np.iinfo(np.int16).min and c_max < np.iinfo(np.int16).max:\n",
    "                    df[col] = df[col].astype(np.int16)\n",
    "                elif c_min > np.iinfo(np.int32).min and c_max < np.iinfo(np.int32).max:\n",
    "                    df[col] = df[col].astype(np.int32)\n",
    "                elif c_min > np.iinfo(np.int64).min and c_max < np.iinfo(np.int64).max:\n",
    "                    df[col] = df[col].astype(np.int64)  \n",
    "            else:\n",
    "                if c_min > np.finfo(np.float16).min and c_max < np.finfo(np.float16).max:\n",
    "                    df[col] = df[col].astype(np.float16)\n",
    "                elif c_min > np.finfo(np.float32).min and c_max < np.finfo(np.float32).max:\n",
    "                    df[col] = df[col].astype(np.float32)\n",
    "                else:\n",
    "                    df[col] = df[col].astype(np.float64)\n",
    "\n",
    "    end_mem = df.memory_usage().sum() / 1024**2\n",
    "    print('Memory usage after optimization is: {:.2f} MB'.format(end_mem))\n",
    "    print('Decreased by {:.1f}%'.format(100 * (start_mem - end_mem) / start_mem))\n",
    "\n",
    "    return df\n",
    "\n",
    "def plot_confusion_matrix(truth, pred, classes, normalize=False, title=''):\n",
    "    cm = confusion_matrix(truth, pred)\n",
    "    if normalize:\n",
    "        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
    "    \n",
    "    plt.figure(figsize=(10, 10))\n",
    "    plt.imshow(cm, interpolation='nearest', cmap=plt.cm.Blues)\n",
    "    plt.title('Confusion matrix', size=15)\n",
    "    plt.colorbar(fraction=0.046, pad=0.04)\n",
    "    tick_marks = np.arange(len(classes))\n",
    "    plt.xticks(tick_marks, classes, rotation=45)\n",
    "    plt.yticks(tick_marks, classes)\n",
    "\n",
    "    fmt = '.2f' if normalize else 'd'\n",
    "    thresh = cm.max() / 2.\n",
    "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, format(cm[i, j], fmt),\n",
    "                 horizontalalignment=\"center\",\n",
    "                 color=\"white\" if cm[i, j] > thresh else \"black\")\n",
    "\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')\n",
    "    plt.grid(False)\n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Memory usage of dataframe is 48.37 MB\n",
      "Memory usage after optimization is: 14.88 MB\n",
      "Decreased by 69.2%\n",
      "Memory usage of dataframe is 48.45 MB\n",
      "Memory usage after optimization is: 14.91 MB\n",
      "Decreased by 69.2%\n"
     ]
    }
   ],
   "source": [
    "train = reduce_mem_usage(train)\n",
    "test = reduce_mem_usage(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_valid_set(label):\n",
    "    # Lets try creating a validation set of 10% of the total size.\n",
    "    ldict = {\n",
    "        'concrete': 0.16,\n",
    "        'soft_pvc': 0.18,\n",
    "        'wood': 0.06,\n",
    "        'tiled': 0.03,\n",
    "        'fine_concrete': 0.10,\n",
    "        'hard_tiles_large_space': 0.12,\n",
    "        'soft_tiles': 0.23,\n",
    "        'carpet': 0.05,\n",
    "        'hard_tiles': 0.07,\n",
    "    }\n",
    "    score = 0\n",
    "    print(\"Required count of target classes for the Valid Set :: \")\n",
    "    for key, value in ldict.items():\n",
    "        score += value\n",
    "        print(key, int(value * 380)) # Multiplying by 380 i.e 10% of 3810 for our validation size of 10%.\n",
    "        ldict[key] = int(value * 380)\n",
    "    print(\"\\nTotal Weights of class :: \", score)\n",
    "    \n",
    "    # Grouping surface with group_id and the count attached to each surface.\n",
    "    ser = label.groupby(['surface'])['group_id'].value_counts()\n",
    "    ser = pd.DataFrame(ser)\n",
    "    ser.columns = ['count']\n",
    "    \n",
    "    # Maually creating the valid set using the counts using the required count and the count we have in the train set.\n",
    "    # This dictionary consists of the group_id for the required valid set. \n",
    "    cv_set = {\n",
    "        'concrete': [0],\n",
    "        'soft_pvc': [69],\n",
    "        'wood': [2],\n",
    "        'tiled': [28],\n",
    "        'fine_concrete': [36],\n",
    "        'hard_tiles_large_space': [16],\n",
    "        'soft_tiles': [4, 17],\n",
    "        'carpet': [52],\n",
    "        'hard_tiles': [27],\n",
    "    }\n",
    "\n",
    "    cv_size = 0\n",
    "    for key, value in cv_set.items():\n",
    "        print(key)\n",
    "        for i in value:\n",
    "            cv_size += label[label['group_id'] == i].shape[0]\n",
    "            print(\"\\nGot shape :: \", label[label['group_id'] == i].shape[0])\n",
    "        print(\"Expected shape :: \", ldict[key])\n",
    "    \n",
    "    val_df = pd.DataFrame()\n",
    "    for key, value in cv_set.items():\n",
    "        for i in value:\n",
    "            val_df = pd.concat([val_df, label[label['group_id'] == i]])\n",
    "    print(\"Valid Set Size :: \", val_df.shape[0])\n",
    "    \n",
    "    # We have only 1 group_id for the hard_tiles and it consists of only 21 records.\n",
    "    # So we have added the same group_id in the train as well as valid set. GROUP_ID = 27(for \"hard_tiles\")\n",
    "    hard_tiles_index = label[(label['surface'] == 'hard_tiles') & (label['group_id'] == 27)].index\n",
    "    \n",
    "    # Therefore train set = Total Set series_id - Valid Set series_id + Hard_Tiles.index\n",
    "    trn_series_id_list = list(set(label.series_id.unique()) - set(val_df.series_id.unique())) + hard_tiles_index.tolist()\n",
    "    \n",
    "    print(\"Train Set Distribution\")\n",
    "    print(label['surface'].iloc[trn_series_id_list].value_counts())\n",
    "    \n",
    "    print(\"Valid Set Distribution\")\n",
    "    print(label['surface'].iloc[val_df.index].value_counts())\n",
    "    \n",
    "    trn_df = label.iloc[trn_series_id_list]\n",
    "    \n",
    "    trn_df.set_index(['series_id'], inplace=True)\n",
    "    val_df.set_index(['series_id'], inplace=True)\n",
    "    \n",
    "    return trn_df, val_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def FE(data):\n",
    "    df = pd.DataFrame()\n",
    "    data['totl_anglr_vel'] = (data['angular_velocity_X']**2 + data['angular_velocity_Y']**2 +\n",
    "                             data['angular_velocity_Z']**2)** 0.5\n",
    "    data['totl_linr_acc'] = (data['linear_acceleration_X']**2 + data['linear_acceleration_Y']**2 +\n",
    "                             data['linear_acceleration_Z']**2)**0.5\n",
    "    #data['flat_xyz'] = (data['orientation_X'] + data['orientation_Y'] +\n",
    "    #                    data['orientation_Z'])\n",
    "    data['totl_xyz'] = (data['orientation_X']**2 + data['orientation_Y']**2 +\n",
    "                        data['orientation_Z']**2)**0.5\n",
    "    data['z_planar_anglr_vel'] = (data['angular_velocity_X']**2 + data['angular_velocity_Y']**2)**0.5\n",
    "    data['z_planar_linr_acc'] = (data['linear_acceleration_X']**2 + data['linear_acceleration_Y']**2)**0.5\n",
    "    #Lets derive one more column since there is a relationship in velocity and acceleration\n",
    "    # v = u + a*t , u is initial velocty. if u = 0, then v = at means t = v/a\n",
    "    # but value of acceleration is more and value of velocity is less, lets do a/v relation\n",
    "    # data['acc_vs_vel'] = data['totl_linr_acc'] / data['totl_anglr_vel']\n",
    "    \n",
    "    # Deriving more feature, since we are reducing rows now, we should know min,max,mean values\n",
    "    for col in data.columns:\n",
    "        if col in ['row_id','series_id','measurement_number']:\n",
    "            continue\n",
    "        df[col + '_mean'] = data.groupby(['series_id'])[col].mean()\n",
    "        df[col + '_median'] = data.groupby(['series_id'])[col].median()\n",
    "        df[col + '_max'] = data.groupby(['series_id'])[col].max()\n",
    "        df[col + '_min'] = data.groupby(['series_id'])[col].min()\n",
    "        df[col + '_std'] = data.groupby(['series_id'])[col].std()\n",
    "        df[col + '_maxtoMin'] = data.groupby(['series_id'])[col].max() / data.groupby(['series_id'])[col].min()\n",
    "        df[col + '_mean_abs_chg'] = data.groupby(['series_id'])[col].apply(lambda x: mean_abs_change(x))\n",
    "        df[col + '_abs_min'] = data.groupby(['series_id'])[col].apply(lambda x: np.min(np.abs(x)))\n",
    "        df[col + '_abs_max'] = data.groupby(['series_id'])[col].apply(lambda x: np.max(np.abs(x)))\n",
    "        df[col + '_kurtosis'] = data.groupby(['series_id'])[col].apply(lambda x: kurtosis(x))\n",
    "        df[col + '_skewness'] = data.groupby(['series_id'])[col].apply(lambda x: skewness(x))\n",
    "        df[col + '_abs_avg'] = (df[col + '_abs_min'] + df[col + '_abs_max'])/2\n",
    "        # df[\"diff_\"+col] = df[col]-df[col].shift(1)\n",
    "        # df[\"ma_\"+col] = np.square(abs(df[col]-df[col].rolling(8).mean()))\n",
    "        # df[col + '_first'] = data.groupby(['series_id'])[col].first()\n",
    "        # df[col + '_last'] = data.groupby(['series_id'])[col].last()\n",
    "    \n",
    "    for or_col in ['orientation_X', 'orientation_Y', 'orientation_Z', 'orientation_W']:\n",
    "        df[or_col + '_first'] = data.groupby(['series_id'])[col].first()\n",
    "        df[or_col + '_last'] = data.groupby(['series_id'])[col].last()\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Required count of target classes for the Valid Set :: \n",
      "concrete 60\n",
      "soft_pvc 68\n",
      "wood 22\n",
      "tiled 11\n",
      "fine_concrete 38\n",
      "hard_tiles_large_space 45\n",
      "soft_tiles 87\n",
      "carpet 19\n",
      "hard_tiles 26\n",
      "\n",
      "Total Weights of class ::  1.0\n",
      "concrete\n",
      "\n",
      "Got shape ::  57\n",
      "Expected shape ::  60\n",
      "soft_pvc\n",
      "\n",
      "Got shape ::  70\n",
      "Expected shape ::  68\n",
      "wood\n",
      "\n",
      "Got shape ::  18\n",
      "Expected shape ::  22\n",
      "tiled\n",
      "\n",
      "Got shape ::  36\n",
      "Expected shape ::  11\n",
      "fine_concrete\n",
      "\n",
      "Got shape ::  36\n",
      "Expected shape ::  38\n",
      "hard_tiles_large_space\n",
      "\n",
      "Got shape ::  45\n",
      "Expected shape ::  45\n",
      "soft_tiles\n",
      "\n",
      "Got shape ::  57\n",
      "\n",
      "Got shape ::  12\n",
      "Expected shape ::  87\n",
      "carpet\n",
      "\n",
      "Got shape ::  11\n",
      "Expected shape ::  19\n",
      "hard_tiles\n",
      "\n",
      "Got shape ::  21\n",
      "Expected shape ::  26\n",
      "Valid Set Size ::  363\n",
      "Train Set Distribution\n",
      "concrete                  722\n",
      "soft_pvc                  662\n",
      "wood                      589\n",
      "tiled                     478\n",
      "fine_concrete             327\n",
      "hard_tiles_large_space    263\n",
      "soft_tiles                228\n",
      "carpet                    178\n",
      "hard_tiles                 21\n",
      "Name: surface, dtype: int64\n",
      "Valid Set Distribution\n",
      "soft_pvc                  70\n",
      "soft_tiles                69\n",
      "concrete                  57\n",
      "hard_tiles_large_space    45\n",
      "tiled                     36\n",
      "fine_concrete             36\n",
      "hard_tiles                21\n",
      "wood                      18\n",
      "carpet                    11\n",
      "Name: surface, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "trn_df, val_df = create_valid_set(label)\n",
    "train = FE(train)\n",
    "test = FE(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "le = LabelEncoder()\n",
    "label['surface'] = le.fit_transform(label['surface'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "    .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>orientation_X_mean</th>\n",
       "      <th>orientation_X_median</th>\n",
       "      <th>orientation_X_max</th>\n",
       "      <th>orientation_X_min</th>\n",
       "      <th>orientation_X_std</th>\n",
       "      <th>orientation_X_maxtoMin</th>\n",
       "      <th>orientation_X_mean_abs_chg</th>\n",
       "      <th>orientation_X_abs_min</th>\n",
       "      <th>orientation_X_abs_max</th>\n",
       "      <th>orientation_X_kurtosis</th>\n",
       "      <th>...</th>\n",
       "      <th>z_planar_linr_acc_skewness</th>\n",
       "      <th>z_planar_linr_acc_abs_avg</th>\n",
       "      <th>orientation_X_first</th>\n",
       "      <th>orientation_X_last</th>\n",
       "      <th>orientation_Y_first</th>\n",
       "      <th>orientation_Y_last</th>\n",
       "      <th>orientation_Z_first</th>\n",
       "      <th>orientation_Z_last</th>\n",
       "      <th>orientation_W_first</th>\n",
       "      <th>orientation_W_last</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>series_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.758789</td>\n",
       "      <td>-0.758301</td>\n",
       "      <td>-0.758301</td>\n",
       "      <td>-0.759766</td>\n",
       "      <td>0.000423</td>\n",
       "      <td>0.998047</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.758301</td>\n",
       "      <td>0.759766</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.295654</td>\n",
       "      <td>2.837158</td>\n",
       "      <td>2.232422</td>\n",
       "      <td>0.964844</td>\n",
       "      <td>2.232422</td>\n",
       "      <td>0.964844</td>\n",
       "      <td>2.232422</td>\n",
       "      <td>0.964844</td>\n",
       "      <td>2.232422</td>\n",
       "      <td>0.964844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.958496</td>\n",
       "      <td>-0.958496</td>\n",
       "      <td>-0.958496</td>\n",
       "      <td>-0.958984</td>\n",
       "      <td>0.000244</td>\n",
       "      <td>0.999512</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>0.958496</td>\n",
       "      <td>0.958984</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.109497</td>\n",
       "      <td>3.401215</td>\n",
       "      <td>3.136719</td>\n",
       "      <td>2.072266</td>\n",
       "      <td>3.136719</td>\n",
       "      <td>2.072266</td>\n",
       "      <td>3.136719</td>\n",
       "      <td>2.072266</td>\n",
       "      <td>3.136719</td>\n",
       "      <td>2.072266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.512207</td>\n",
       "      <td>-0.512207</td>\n",
       "      <td>-0.509277</td>\n",
       "      <td>-0.514160</td>\n",
       "      <td>0.001359</td>\n",
       "      <td>0.990723</td>\n",
       "      <td>0.000038</td>\n",
       "      <td>0.509277</td>\n",
       "      <td>0.514160</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.008812</td>\n",
       "      <td>3.178711</td>\n",
       "      <td>3.628906</td>\n",
       "      <td>3.466797</td>\n",
       "      <td>3.628906</td>\n",
       "      <td>3.466797</td>\n",
       "      <td>3.628906</td>\n",
       "      <td>3.466797</td>\n",
       "      <td>3.628906</td>\n",
       "      <td>3.466797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.938965</td>\n",
       "      <td>-0.938965</td>\n",
       "      <td>-0.938965</td>\n",
       "      <td>-0.939453</td>\n",
       "      <td>0.000244</td>\n",
       "      <td>0.999512</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.938965</td>\n",
       "      <td>0.939453</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.500977</td>\n",
       "      <td>6.083130</td>\n",
       "      <td>1.804688</td>\n",
       "      <td>2.570312</td>\n",
       "      <td>1.804688</td>\n",
       "      <td>2.570312</td>\n",
       "      <td>1.804688</td>\n",
       "      <td>2.570312</td>\n",
       "      <td>1.804688</td>\n",
       "      <td>2.570312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.891113</td>\n",
       "      <td>-0.891113</td>\n",
       "      <td>-0.886719</td>\n",
       "      <td>-0.896973</td>\n",
       "      <td>0.002970</td>\n",
       "      <td>0.988770</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.886719</td>\n",
       "      <td>0.896973</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.520020</td>\n",
       "      <td>2.586792</td>\n",
       "      <td>3.132812</td>\n",
       "      <td>2.775391</td>\n",
       "      <td>3.132812</td>\n",
       "      <td>2.775391</td>\n",
       "      <td>3.132812</td>\n",
       "      <td>2.775391</td>\n",
       "      <td>3.132812</td>\n",
       "      <td>2.775391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.464600</td>\n",
       "      <td>0.464600</td>\n",
       "      <td>0.465332</td>\n",
       "      <td>0.464111</td>\n",
       "      <td>0.000345</td>\n",
       "      <td>1.002930</td>\n",
       "      <td>0.000042</td>\n",
       "      <td>0.464111</td>\n",
       "      <td>0.465332</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.343262</td>\n",
       "      <td>4.263306</td>\n",
       "      <td>3.312500</td>\n",
       "      <td>6.117188</td>\n",
       "      <td>3.312500</td>\n",
       "      <td>6.117188</td>\n",
       "      <td>3.312500</td>\n",
       "      <td>6.117188</td>\n",
       "      <td>3.312500</td>\n",
       "      <td>6.117188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-0.402344</td>\n",
       "      <td>-0.402344</td>\n",
       "      <td>-0.398682</td>\n",
       "      <td>-0.405762</td>\n",
       "      <td>0.002129</td>\n",
       "      <td>0.982422</td>\n",
       "      <td>0.000056</td>\n",
       "      <td>0.398682</td>\n",
       "      <td>0.405762</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.053986</td>\n",
       "      <td>2.586914</td>\n",
       "      <td>3.294922</td>\n",
       "      <td>2.343750</td>\n",
       "      <td>3.294922</td>\n",
       "      <td>2.343750</td>\n",
       "      <td>3.294922</td>\n",
       "      <td>2.343750</td>\n",
       "      <td>3.294922</td>\n",
       "      <td>2.343750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-0.925781</td>\n",
       "      <td>-0.925781</td>\n",
       "      <td>-0.925781</td>\n",
       "      <td>-0.926270</td>\n",
       "      <td>0.000244</td>\n",
       "      <td>0.999512</td>\n",
       "      <td>0.000042</td>\n",
       "      <td>0.925781</td>\n",
       "      <td>0.926270</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.624023</td>\n",
       "      <td>5.661865</td>\n",
       "      <td>6.355469</td>\n",
       "      <td>2.447266</td>\n",
       "      <td>6.355469</td>\n",
       "      <td>2.447266</td>\n",
       "      <td>6.355469</td>\n",
       "      <td>2.447266</td>\n",
       "      <td>6.355469</td>\n",
       "      <td>2.447266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.012039</td>\n",
       "      <td>0.010986</td>\n",
       "      <td>0.018250</td>\n",
       "      <td>0.009155</td>\n",
       "      <td>0.002930</td>\n",
       "      <td>1.993164</td>\n",
       "      <td>0.000073</td>\n",
       "      <td>0.009155</td>\n",
       "      <td>0.018250</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.140991</td>\n",
       "      <td>2.389648</td>\n",
       "      <td>2.150391</td>\n",
       "      <td>2.042969</td>\n",
       "      <td>2.150391</td>\n",
       "      <td>2.042969</td>\n",
       "      <td>2.150391</td>\n",
       "      <td>2.042969</td>\n",
       "      <td>2.150391</td>\n",
       "      <td>2.042969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.789062</td>\n",
       "      <td>0.790039</td>\n",
       "      <td>0.824707</td>\n",
       "      <td>0.750977</td>\n",
       "      <td>0.021576</td>\n",
       "      <td>1.098633</td>\n",
       "      <td>0.000581</td>\n",
       "      <td>0.750977</td>\n",
       "      <td>0.824707</td>\n",
       "      <td>-1.207031</td>\n",
       "      <td>...</td>\n",
       "      <td>0.195312</td>\n",
       "      <td>4.376953</td>\n",
       "      <td>8.492188</td>\n",
       "      <td>5.492188</td>\n",
       "      <td>8.492188</td>\n",
       "      <td>5.492188</td>\n",
       "      <td>8.492188</td>\n",
       "      <td>5.492188</td>\n",
       "      <td>8.492188</td>\n",
       "      <td>5.492188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.849121</td>\n",
       "      <td>0.849121</td>\n",
       "      <td>0.850098</td>\n",
       "      <td>0.847168</td>\n",
       "      <td>0.000880</td>\n",
       "      <td>1.003906</td>\n",
       "      <td>0.000023</td>\n",
       "      <td>0.847168</td>\n",
       "      <td>0.850098</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.173340</td>\n",
       "      <td>3.347168</td>\n",
       "      <td>2.427734</td>\n",
       "      <td>3.025391</td>\n",
       "      <td>2.427734</td>\n",
       "      <td>3.025391</td>\n",
       "      <td>2.427734</td>\n",
       "      <td>3.025391</td>\n",
       "      <td>2.427734</td>\n",
       "      <td>3.025391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.494873</td>\n",
       "      <td>0.495117</td>\n",
       "      <td>0.502930</td>\n",
       "      <td>0.487305</td>\n",
       "      <td>0.004520</td>\n",
       "      <td>1.032227</td>\n",
       "      <td>0.000123</td>\n",
       "      <td>0.487305</td>\n",
       "      <td>0.502930</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.801758</td>\n",
       "      <td>4.684204</td>\n",
       "      <td>3.535156</td>\n",
       "      <td>2.636719</td>\n",
       "      <td>3.535156</td>\n",
       "      <td>2.636719</td>\n",
       "      <td>3.535156</td>\n",
       "      <td>2.636719</td>\n",
       "      <td>3.535156</td>\n",
       "      <td>2.636719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.333984</td>\n",
       "      <td>0.334473</td>\n",
       "      <td>0.338379</td>\n",
       "      <td>0.329346</td>\n",
       "      <td>0.002514</td>\n",
       "      <td>1.027344</td>\n",
       "      <td>0.000125</td>\n",
       "      <td>0.329346</td>\n",
       "      <td>0.338379</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.294189</td>\n",
       "      <td>3.912231</td>\n",
       "      <td>5.105469</td>\n",
       "      <td>4.960938</td>\n",
       "      <td>5.105469</td>\n",
       "      <td>4.960938</td>\n",
       "      <td>5.105469</td>\n",
       "      <td>4.960938</td>\n",
       "      <td>5.105469</td>\n",
       "      <td>4.960938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.374268</td>\n",
       "      <td>0.374512</td>\n",
       "      <td>0.380371</td>\n",
       "      <td>0.367188</td>\n",
       "      <td>0.003822</td>\n",
       "      <td>1.036133</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.367188</td>\n",
       "      <td>0.380371</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.196777</td>\n",
       "      <td>3.135742</td>\n",
       "      <td>2.837891</td>\n",
       "      <td>2.181641</td>\n",
       "      <td>2.837891</td>\n",
       "      <td>2.181641</td>\n",
       "      <td>2.837891</td>\n",
       "      <td>2.181641</td>\n",
       "      <td>2.837891</td>\n",
       "      <td>2.181641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>-0.504395</td>\n",
       "      <td>-0.503906</td>\n",
       "      <td>-0.502930</td>\n",
       "      <td>-0.505371</td>\n",
       "      <td>0.000598</td>\n",
       "      <td>0.995117</td>\n",
       "      <td>0.000065</td>\n",
       "      <td>0.502930</td>\n",
       "      <td>0.505371</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>1.115234</td>\n",
       "      <td>8.377579</td>\n",
       "      <td>3.576172</td>\n",
       "      <td>8.218750</td>\n",
       "      <td>3.576172</td>\n",
       "      <td>8.218750</td>\n",
       "      <td>3.576172</td>\n",
       "      <td>8.218750</td>\n",
       "      <td>3.576172</td>\n",
       "      <td>8.218750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-0.941895</td>\n",
       "      <td>-0.941895</td>\n",
       "      <td>-0.941406</td>\n",
       "      <td>-0.942871</td>\n",
       "      <td>0.000345</td>\n",
       "      <td>0.998535</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.941406</td>\n",
       "      <td>0.942871</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.071777</td>\n",
       "      <td>3.953430</td>\n",
       "      <td>4.179688</td>\n",
       "      <td>2.992188</td>\n",
       "      <td>4.179688</td>\n",
       "      <td>2.992188</td>\n",
       "      <td>4.179688</td>\n",
       "      <td>2.992188</td>\n",
       "      <td>4.179688</td>\n",
       "      <td>2.992188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-0.959473</td>\n",
       "      <td>-0.959961</td>\n",
       "      <td>-0.958008</td>\n",
       "      <td>-0.961426</td>\n",
       "      <td>0.000732</td>\n",
       "      <td>0.996582</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.958008</td>\n",
       "      <td>0.961426</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.512207</td>\n",
       "      <td>10.738770</td>\n",
       "      <td>7.359375</td>\n",
       "      <td>4.679688</td>\n",
       "      <td>7.359375</td>\n",
       "      <td>4.679688</td>\n",
       "      <td>7.359375</td>\n",
       "      <td>4.679688</td>\n",
       "      <td>7.359375</td>\n",
       "      <td>4.679688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.440186</td>\n",
       "      <td>0.440430</td>\n",
       "      <td>0.443604</td>\n",
       "      <td>0.434814</td>\n",
       "      <td>0.002729</td>\n",
       "      <td>1.020508</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.434814</td>\n",
       "      <td>0.443604</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.191284</td>\n",
       "      <td>3.021973</td>\n",
       "      <td>2.611328</td>\n",
       "      <td>1.994141</td>\n",
       "      <td>2.611328</td>\n",
       "      <td>1.994141</td>\n",
       "      <td>2.611328</td>\n",
       "      <td>1.994141</td>\n",
       "      <td>2.611328</td>\n",
       "      <td>1.994141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-0.288818</td>\n",
       "      <td>-0.288330</td>\n",
       "      <td>-0.282227</td>\n",
       "      <td>-0.295898</td>\n",
       "      <td>0.003914</td>\n",
       "      <td>0.953613</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.282227</td>\n",
       "      <td>0.295898</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000175</td>\n",
       "      <td>4.200928</td>\n",
       "      <td>1.773438</td>\n",
       "      <td>3.347656</td>\n",
       "      <td>1.773438</td>\n",
       "      <td>3.347656</td>\n",
       "      <td>1.773438</td>\n",
       "      <td>3.347656</td>\n",
       "      <td>1.773438</td>\n",
       "      <td>3.347656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.829102</td>\n",
       "      <td>0.829102</td>\n",
       "      <td>0.836914</td>\n",
       "      <td>0.821289</td>\n",
       "      <td>0.004456</td>\n",
       "      <td>1.018555</td>\n",
       "      <td>0.000123</td>\n",
       "      <td>0.821289</td>\n",
       "      <td>0.836914</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.422119</td>\n",
       "      <td>3.030273</td>\n",
       "      <td>3.892578</td>\n",
       "      <td>2.720703</td>\n",
       "      <td>3.892578</td>\n",
       "      <td>2.720703</td>\n",
       "      <td>3.892578</td>\n",
       "      <td>2.720703</td>\n",
       "      <td>3.892578</td>\n",
       "      <td>2.720703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.913086</td>\n",
       "      <td>0.913086</td>\n",
       "      <td>0.916504</td>\n",
       "      <td>0.908691</td>\n",
       "      <td>0.002155</td>\n",
       "      <td>1.008789</td>\n",
       "      <td>0.000062</td>\n",
       "      <td>0.908691</td>\n",
       "      <td>0.916504</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.028412</td>\n",
       "      <td>3.472412</td>\n",
       "      <td>2.796875</td>\n",
       "      <td>3.818359</td>\n",
       "      <td>2.796875</td>\n",
       "      <td>3.818359</td>\n",
       "      <td>2.796875</td>\n",
       "      <td>3.818359</td>\n",
       "      <td>2.796875</td>\n",
       "      <td>3.818359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.013313</td>\n",
       "      <td>0.013306</td>\n",
       "      <td>0.013481</td>\n",
       "      <td>0.013222</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.019531</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.013222</td>\n",
       "      <td>0.013481</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.675781</td>\n",
       "      <td>2.923828</td>\n",
       "      <td>2.851562</td>\n",
       "      <td>2.912109</td>\n",
       "      <td>2.851562</td>\n",
       "      <td>2.912109</td>\n",
       "      <td>2.851562</td>\n",
       "      <td>2.912109</td>\n",
       "      <td>2.851562</td>\n",
       "      <td>2.912109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>-0.961914</td>\n",
       "      <td>-0.961914</td>\n",
       "      <td>-0.961914</td>\n",
       "      <td>-0.962402</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.999512</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>0.961914</td>\n",
       "      <td>0.962402</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.260254</td>\n",
       "      <td>2.919922</td>\n",
       "      <td>2.931641</td>\n",
       "      <td>2.933594</td>\n",
       "      <td>2.931641</td>\n",
       "      <td>2.933594</td>\n",
       "      <td>2.931641</td>\n",
       "      <td>2.933594</td>\n",
       "      <td>2.931641</td>\n",
       "      <td>2.933594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>-0.283936</td>\n",
       "      <td>-0.284180</td>\n",
       "      <td>-0.281006</td>\n",
       "      <td>-0.285400</td>\n",
       "      <td>0.001315</td>\n",
       "      <td>0.984375</td>\n",
       "      <td>0.000054</td>\n",
       "      <td>0.281006</td>\n",
       "      <td>0.285400</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063232</td>\n",
       "      <td>3.687622</td>\n",
       "      <td>3.281250</td>\n",
       "      <td>2.673828</td>\n",
       "      <td>3.281250</td>\n",
       "      <td>2.673828</td>\n",
       "      <td>3.281250</td>\n",
       "      <td>2.673828</td>\n",
       "      <td>3.281250</td>\n",
       "      <td>2.673828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.954102</td>\n",
       "      <td>0.954102</td>\n",
       "      <td>0.955078</td>\n",
       "      <td>0.952637</td>\n",
       "      <td>0.000772</td>\n",
       "      <td>1.002930</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>0.952637</td>\n",
       "      <td>0.955078</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.022354</td>\n",
       "      <td>3.032227</td>\n",
       "      <td>3.472656</td>\n",
       "      <td>3.171875</td>\n",
       "      <td>3.472656</td>\n",
       "      <td>3.171875</td>\n",
       "      <td>3.472656</td>\n",
       "      <td>3.171875</td>\n",
       "      <td>3.472656</td>\n",
       "      <td>3.171875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.345459</td>\n",
       "      <td>0.345215</td>\n",
       "      <td>0.354980</td>\n",
       "      <td>0.337402</td>\n",
       "      <td>0.005085</td>\n",
       "      <td>1.051758</td>\n",
       "      <td>0.000138</td>\n",
       "      <td>0.337402</td>\n",
       "      <td>0.354980</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.427979</td>\n",
       "      <td>3.218750</td>\n",
       "      <td>2.343750</td>\n",
       "      <td>2.935547</td>\n",
       "      <td>2.343750</td>\n",
       "      <td>2.935547</td>\n",
       "      <td>2.343750</td>\n",
       "      <td>2.935547</td>\n",
       "      <td>2.343750</td>\n",
       "      <td>2.935547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>-0.819336</td>\n",
       "      <td>-0.819336</td>\n",
       "      <td>-0.812500</td>\n",
       "      <td>-0.826172</td>\n",
       "      <td>0.003944</td>\n",
       "      <td>0.983398</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.812500</td>\n",
       "      <td>0.826172</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.708496</td>\n",
       "      <td>3.332031</td>\n",
       "      <td>2.462891</td>\n",
       "      <td>2.585938</td>\n",
       "      <td>2.462891</td>\n",
       "      <td>2.585938</td>\n",
       "      <td>2.462891</td>\n",
       "      <td>2.585938</td>\n",
       "      <td>2.462891</td>\n",
       "      <td>2.585938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.636230</td>\n",
       "      <td>0.636230</td>\n",
       "      <td>0.652344</td>\n",
       "      <td>0.621582</td>\n",
       "      <td>0.008995</td>\n",
       "      <td>1.049805</td>\n",
       "      <td>0.000242</td>\n",
       "      <td>0.621582</td>\n",
       "      <td>0.652344</td>\n",
       "      <td>-1.494141</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.045502</td>\n",
       "      <td>2.750488</td>\n",
       "      <td>2.109375</td>\n",
       "      <td>2.957031</td>\n",
       "      <td>2.109375</td>\n",
       "      <td>2.957031</td>\n",
       "      <td>2.109375</td>\n",
       "      <td>2.957031</td>\n",
       "      <td>2.109375</td>\n",
       "      <td>2.957031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.940430</td>\n",
       "      <td>0.940430</td>\n",
       "      <td>0.940918</td>\n",
       "      <td>0.939941</td>\n",
       "      <td>0.000345</td>\n",
       "      <td>1.000977</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.939941</td>\n",
       "      <td>0.940918</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.432617</td>\n",
       "      <td>4.556030</td>\n",
       "      <td>2.375000</td>\n",
       "      <td>4.183594</td>\n",
       "      <td>2.375000</td>\n",
       "      <td>4.183594</td>\n",
       "      <td>2.375000</td>\n",
       "      <td>4.183594</td>\n",
       "      <td>2.375000</td>\n",
       "      <td>4.183594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.013443</td>\n",
       "      <td>0.013313</td>\n",
       "      <td>0.014542</td>\n",
       "      <td>0.012367</td>\n",
       "      <td>0.000690</td>\n",
       "      <td>1.175781</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.012367</td>\n",
       "      <td>0.014542</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.065186</td>\n",
       "      <td>3.023926</td>\n",
       "      <td>3.048828</td>\n",
       "      <td>1.983398</td>\n",
       "      <td>3.048828</td>\n",
       "      <td>1.983398</td>\n",
       "      <td>3.048828</td>\n",
       "      <td>1.983398</td>\n",
       "      <td>3.048828</td>\n",
       "      <td>1.983398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3780</th>\n",
       "      <td>-0.492676</td>\n",
       "      <td>-0.492676</td>\n",
       "      <td>-0.489502</td>\n",
       "      <td>-0.495605</td>\n",
       "      <td>0.001811</td>\n",
       "      <td>0.987793</td>\n",
       "      <td>0.000065</td>\n",
       "      <td>0.489502</td>\n",
       "      <td>0.495605</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.064270</td>\n",
       "      <td>3.856934</td>\n",
       "      <td>5.933594</td>\n",
       "      <td>2.632812</td>\n",
       "      <td>5.933594</td>\n",
       "      <td>2.632812</td>\n",
       "      <td>5.933594</td>\n",
       "      <td>2.632812</td>\n",
       "      <td>5.933594</td>\n",
       "      <td>2.632812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3781</th>\n",
       "      <td>0.574707</td>\n",
       "      <td>0.574219</td>\n",
       "      <td>0.587891</td>\n",
       "      <td>0.563965</td>\n",
       "      <td>0.006561</td>\n",
       "      <td>1.041992</td>\n",
       "      <td>0.000204</td>\n",
       "      <td>0.563965</td>\n",
       "      <td>0.587891</td>\n",
       "      <td>-2.806641</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.021530</td>\n",
       "      <td>5.414917</td>\n",
       "      <td>5.339844</td>\n",
       "      <td>7.160156</td>\n",
       "      <td>5.339844</td>\n",
       "      <td>7.160156</td>\n",
       "      <td>5.339844</td>\n",
       "      <td>7.160156</td>\n",
       "      <td>5.339844</td>\n",
       "      <td>7.160156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3782</th>\n",
       "      <td>0.459717</td>\n",
       "      <td>0.459717</td>\n",
       "      <td>0.460205</td>\n",
       "      <td>0.459229</td>\n",
       "      <td>0.000345</td>\n",
       "      <td>1.001953</td>\n",
       "      <td>0.000033</td>\n",
       "      <td>0.459229</td>\n",
       "      <td>0.460205</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.066345</td>\n",
       "      <td>3.328552</td>\n",
       "      <td>0.416260</td>\n",
       "      <td>2.158203</td>\n",
       "      <td>0.416260</td>\n",
       "      <td>2.158203</td>\n",
       "      <td>0.416260</td>\n",
       "      <td>2.158203</td>\n",
       "      <td>0.416260</td>\n",
       "      <td>2.158203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3783</th>\n",
       "      <td>0.476807</td>\n",
       "      <td>0.477051</td>\n",
       "      <td>0.477783</td>\n",
       "      <td>0.475098</td>\n",
       "      <td>0.000732</td>\n",
       "      <td>1.005859</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>0.475098</td>\n",
       "      <td>0.477783</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.765137</td>\n",
       "      <td>4.861328</td>\n",
       "      <td>3.123047</td>\n",
       "      <td>2.240234</td>\n",
       "      <td>3.123047</td>\n",
       "      <td>2.240234</td>\n",
       "      <td>3.123047</td>\n",
       "      <td>2.240234</td>\n",
       "      <td>3.123047</td>\n",
       "      <td>2.240234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3784</th>\n",
       "      <td>-0.985352</td>\n",
       "      <td>-0.985352</td>\n",
       "      <td>-0.984863</td>\n",
       "      <td>-0.985352</td>\n",
       "      <td>0.000244</td>\n",
       "      <td>0.999512</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>0.984863</td>\n",
       "      <td>0.985352</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.220337</td>\n",
       "      <td>4.111206</td>\n",
       "      <td>1.308594</td>\n",
       "      <td>6.316406</td>\n",
       "      <td>1.308594</td>\n",
       "      <td>6.316406</td>\n",
       "      <td>1.308594</td>\n",
       "      <td>6.316406</td>\n",
       "      <td>1.308594</td>\n",
       "      <td>6.316406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3785</th>\n",
       "      <td>-0.784180</td>\n",
       "      <td>-0.784180</td>\n",
       "      <td>-0.778809</td>\n",
       "      <td>-0.789062</td>\n",
       "      <td>0.003029</td>\n",
       "      <td>0.986816</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.778809</td>\n",
       "      <td>0.789062</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.274414</td>\n",
       "      <td>3.432617</td>\n",
       "      <td>2.193359</td>\n",
       "      <td>2.974609</td>\n",
       "      <td>2.193359</td>\n",
       "      <td>2.974609</td>\n",
       "      <td>2.193359</td>\n",
       "      <td>2.974609</td>\n",
       "      <td>2.193359</td>\n",
       "      <td>2.974609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3786</th>\n",
       "      <td>-0.883301</td>\n",
       "      <td>-0.883301</td>\n",
       "      <td>-0.882324</td>\n",
       "      <td>-0.884766</td>\n",
       "      <td>0.000810</td>\n",
       "      <td>0.997070</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>0.882324</td>\n",
       "      <td>0.884766</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.109314</td>\n",
       "      <td>2.882660</td>\n",
       "      <td>4.277344</td>\n",
       "      <td>3.291016</td>\n",
       "      <td>4.277344</td>\n",
       "      <td>3.291016</td>\n",
       "      <td>4.277344</td>\n",
       "      <td>3.291016</td>\n",
       "      <td>4.277344</td>\n",
       "      <td>3.291016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3787</th>\n",
       "      <td>-0.834473</td>\n",
       "      <td>-0.834473</td>\n",
       "      <td>-0.833496</td>\n",
       "      <td>-0.835938</td>\n",
       "      <td>0.000732</td>\n",
       "      <td>0.997070</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.833496</td>\n",
       "      <td>0.835938</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.071045</td>\n",
       "      <td>3.593018</td>\n",
       "      <td>4.781250</td>\n",
       "      <td>4.218750</td>\n",
       "      <td>4.781250</td>\n",
       "      <td>4.218750</td>\n",
       "      <td>4.781250</td>\n",
       "      <td>4.218750</td>\n",
       "      <td>4.781250</td>\n",
       "      <td>4.218750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3788</th>\n",
       "      <td>0.663574</td>\n",
       "      <td>0.663574</td>\n",
       "      <td>0.667480</td>\n",
       "      <td>0.659668</td>\n",
       "      <td>0.002211</td>\n",
       "      <td>1.011719</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.659668</td>\n",
       "      <td>0.667480</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.018143</td>\n",
       "      <td>2.746979</td>\n",
       "      <td>0.115051</td>\n",
       "      <td>2.097656</td>\n",
       "      <td>0.115051</td>\n",
       "      <td>2.097656</td>\n",
       "      <td>0.115051</td>\n",
       "      <td>2.097656</td>\n",
       "      <td>0.115051</td>\n",
       "      <td>2.097656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3789</th>\n",
       "      <td>-0.579102</td>\n",
       "      <td>-0.579102</td>\n",
       "      <td>-0.541016</td>\n",
       "      <td>-0.614746</td>\n",
       "      <td>0.021683</td>\n",
       "      <td>0.879883</td>\n",
       "      <td>0.000581</td>\n",
       "      <td>0.541016</td>\n",
       "      <td>0.614746</td>\n",
       "      <td>-1.211914</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.779297</td>\n",
       "      <td>2.478027</td>\n",
       "      <td>2.648438</td>\n",
       "      <td>3.279297</td>\n",
       "      <td>2.648438</td>\n",
       "      <td>3.279297</td>\n",
       "      <td>2.648438</td>\n",
       "      <td>3.279297</td>\n",
       "      <td>2.648438</td>\n",
       "      <td>3.279297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3790</th>\n",
       "      <td>0.710449</td>\n",
       "      <td>0.710449</td>\n",
       "      <td>0.711426</td>\n",
       "      <td>0.709473</td>\n",
       "      <td>0.000598</td>\n",
       "      <td>1.002930</td>\n",
       "      <td>0.000108</td>\n",
       "      <td>0.709473</td>\n",
       "      <td>0.711426</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>1.122070</td>\n",
       "      <td>8.678223</td>\n",
       "      <td>2.613281</td>\n",
       "      <td>5.527344</td>\n",
       "      <td>2.613281</td>\n",
       "      <td>5.527344</td>\n",
       "      <td>2.613281</td>\n",
       "      <td>5.527344</td>\n",
       "      <td>2.613281</td>\n",
       "      <td>5.527344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3791</th>\n",
       "      <td>0.804199</td>\n",
       "      <td>0.804199</td>\n",
       "      <td>0.806152</td>\n",
       "      <td>0.802734</td>\n",
       "      <td>0.001036</td>\n",
       "      <td>1.003906</td>\n",
       "      <td>0.000092</td>\n",
       "      <td>0.802734</td>\n",
       "      <td>0.806152</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>inf</td>\n",
       "      <td>61.619873</td>\n",
       "      <td>2.886719</td>\n",
       "      <td>22.500000</td>\n",
       "      <td>2.886719</td>\n",
       "      <td>22.500000</td>\n",
       "      <td>2.886719</td>\n",
       "      <td>22.500000</td>\n",
       "      <td>2.886719</td>\n",
       "      <td>22.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3792</th>\n",
       "      <td>0.640625</td>\n",
       "      <td>0.640137</td>\n",
       "      <td>0.642578</td>\n",
       "      <td>0.638672</td>\n",
       "      <td>0.001145</td>\n",
       "      <td>1.005859</td>\n",
       "      <td>0.000031</td>\n",
       "      <td>0.638672</td>\n",
       "      <td>0.642578</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.142700</td>\n",
       "      <td>2.617126</td>\n",
       "      <td>2.457031</td>\n",
       "      <td>3.605469</td>\n",
       "      <td>2.457031</td>\n",
       "      <td>3.605469</td>\n",
       "      <td>2.457031</td>\n",
       "      <td>3.605469</td>\n",
       "      <td>2.457031</td>\n",
       "      <td>3.605469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3793</th>\n",
       "      <td>-0.977051</td>\n",
       "      <td>-0.977539</td>\n",
       "      <td>-0.975586</td>\n",
       "      <td>-0.978027</td>\n",
       "      <td>0.000732</td>\n",
       "      <td>0.997559</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>0.975586</td>\n",
       "      <td>0.978027</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.181396</td>\n",
       "      <td>3.117432</td>\n",
       "      <td>3.138672</td>\n",
       "      <td>2.347656</td>\n",
       "      <td>3.138672</td>\n",
       "      <td>2.347656</td>\n",
       "      <td>3.138672</td>\n",
       "      <td>2.347656</td>\n",
       "      <td>3.138672</td>\n",
       "      <td>2.347656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3794</th>\n",
       "      <td>0.765137</td>\n",
       "      <td>0.765625</td>\n",
       "      <td>0.774902</td>\n",
       "      <td>0.755371</td>\n",
       "      <td>0.005627</td>\n",
       "      <td>1.025391</td>\n",
       "      <td>0.000154</td>\n",
       "      <td>0.755371</td>\n",
       "      <td>0.774902</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.318115</td>\n",
       "      <td>5.485596</td>\n",
       "      <td>6.613281</td>\n",
       "      <td>0.970703</td>\n",
       "      <td>6.613281</td>\n",
       "      <td>0.970703</td>\n",
       "      <td>6.613281</td>\n",
       "      <td>0.970703</td>\n",
       "      <td>6.613281</td>\n",
       "      <td>0.970703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3795</th>\n",
       "      <td>-0.349365</td>\n",
       "      <td>-0.349121</td>\n",
       "      <td>-0.345215</td>\n",
       "      <td>-0.353027</td>\n",
       "      <td>0.002058</td>\n",
       "      <td>0.978027</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>0.345215</td>\n",
       "      <td>0.353027</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.535156</td>\n",
       "      <td>5.279510</td>\n",
       "      <td>1.666016</td>\n",
       "      <td>1.009766</td>\n",
       "      <td>1.666016</td>\n",
       "      <td>1.009766</td>\n",
       "      <td>1.666016</td>\n",
       "      <td>1.009766</td>\n",
       "      <td>1.666016</td>\n",
       "      <td>1.009766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3796</th>\n",
       "      <td>-0.756348</td>\n",
       "      <td>-0.755371</td>\n",
       "      <td>-0.746094</td>\n",
       "      <td>-0.770996</td>\n",
       "      <td>0.007133</td>\n",
       "      <td>0.967773</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.746094</td>\n",
       "      <td>0.770996</td>\n",
       "      <td>-1.933594</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.156372</td>\n",
       "      <td>2.261719</td>\n",
       "      <td>2.263672</td>\n",
       "      <td>2.373047</td>\n",
       "      <td>2.263672</td>\n",
       "      <td>2.373047</td>\n",
       "      <td>2.263672</td>\n",
       "      <td>2.373047</td>\n",
       "      <td>2.263672</td>\n",
       "      <td>2.373047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3797</th>\n",
       "      <td>-0.115356</td>\n",
       "      <td>-0.116760</td>\n",
       "      <td>-0.060394</td>\n",
       "      <td>-0.165405</td>\n",
       "      <td>0.030640</td>\n",
       "      <td>0.365234</td>\n",
       "      <td>0.000827</td>\n",
       "      <td>0.060394</td>\n",
       "      <td>0.165405</td>\n",
       "      <td>-1.193359</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.048187</td>\n",
       "      <td>2.982422</td>\n",
       "      <td>4.140625</td>\n",
       "      <td>3.074219</td>\n",
       "      <td>4.140625</td>\n",
       "      <td>3.074219</td>\n",
       "      <td>4.140625</td>\n",
       "      <td>3.074219</td>\n",
       "      <td>4.140625</td>\n",
       "      <td>3.074219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3798</th>\n",
       "      <td>-0.485840</td>\n",
       "      <td>-0.485352</td>\n",
       "      <td>-0.485107</td>\n",
       "      <td>-0.487305</td>\n",
       "      <td>0.000732</td>\n",
       "      <td>0.995605</td>\n",
       "      <td>0.000038</td>\n",
       "      <td>0.485107</td>\n",
       "      <td>0.487305</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.073425</td>\n",
       "      <td>3.718994</td>\n",
       "      <td>6.210938</td>\n",
       "      <td>3.748047</td>\n",
       "      <td>6.210938</td>\n",
       "      <td>3.748047</td>\n",
       "      <td>6.210938</td>\n",
       "      <td>3.748047</td>\n",
       "      <td>6.210938</td>\n",
       "      <td>3.748047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3799</th>\n",
       "      <td>-0.174683</td>\n",
       "      <td>-0.174316</td>\n",
       "      <td>-0.169800</td>\n",
       "      <td>-0.179199</td>\n",
       "      <td>0.002848</td>\n",
       "      <td>0.947754</td>\n",
       "      <td>0.000087</td>\n",
       "      <td>0.169800</td>\n",
       "      <td>0.179199</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.492188</td>\n",
       "      <td>4.726562</td>\n",
       "      <td>2.017578</td>\n",
       "      <td>4.562500</td>\n",
       "      <td>2.017578</td>\n",
       "      <td>4.562500</td>\n",
       "      <td>2.017578</td>\n",
       "      <td>4.562500</td>\n",
       "      <td>2.017578</td>\n",
       "      <td>4.562500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3800</th>\n",
       "      <td>-0.791504</td>\n",
       "      <td>-0.791992</td>\n",
       "      <td>-0.771973</td>\n",
       "      <td>-0.810547</td>\n",
       "      <td>0.011284</td>\n",
       "      <td>0.952637</td>\n",
       "      <td>0.000304</td>\n",
       "      <td>0.771973</td>\n",
       "      <td>0.810547</td>\n",
       "      <td>-1.343750</td>\n",
       "      <td>...</td>\n",
       "      <td>0.338379</td>\n",
       "      <td>3.418579</td>\n",
       "      <td>1.625977</td>\n",
       "      <td>3.628906</td>\n",
       "      <td>1.625977</td>\n",
       "      <td>3.628906</td>\n",
       "      <td>1.625977</td>\n",
       "      <td>3.628906</td>\n",
       "      <td>1.625977</td>\n",
       "      <td>3.628906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3801</th>\n",
       "      <td>0.806152</td>\n",
       "      <td>0.806152</td>\n",
       "      <td>0.806641</td>\n",
       "      <td>0.804688</td>\n",
       "      <td>0.000546</td>\n",
       "      <td>1.001953</td>\n",
       "      <td>0.000073</td>\n",
       "      <td>0.804688</td>\n",
       "      <td>0.806641</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.708008</td>\n",
       "      <td>6.780273</td>\n",
       "      <td>2.761719</td>\n",
       "      <td>1.979492</td>\n",
       "      <td>2.761719</td>\n",
       "      <td>1.979492</td>\n",
       "      <td>2.761719</td>\n",
       "      <td>1.979492</td>\n",
       "      <td>2.761719</td>\n",
       "      <td>1.979492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3802</th>\n",
       "      <td>-0.167847</td>\n",
       "      <td>-0.167480</td>\n",
       "      <td>-0.164795</td>\n",
       "      <td>-0.173096</td>\n",
       "      <td>0.002630</td>\n",
       "      <td>0.952148</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.164795</td>\n",
       "      <td>0.173096</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.307861</td>\n",
       "      <td>3.896484</td>\n",
       "      <td>5.730469</td>\n",
       "      <td>3.503906</td>\n",
       "      <td>5.730469</td>\n",
       "      <td>3.503906</td>\n",
       "      <td>5.730469</td>\n",
       "      <td>3.503906</td>\n",
       "      <td>5.730469</td>\n",
       "      <td>3.503906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3803</th>\n",
       "      <td>-0.940918</td>\n",
       "      <td>-0.941406</td>\n",
       "      <td>-0.925293</td>\n",
       "      <td>-0.955078</td>\n",
       "      <td>0.008629</td>\n",
       "      <td>0.968750</td>\n",
       "      <td>0.000234</td>\n",
       "      <td>0.925293</td>\n",
       "      <td>0.955078</td>\n",
       "      <td>-1.563477</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.150513</td>\n",
       "      <td>2.787598</td>\n",
       "      <td>2.496094</td>\n",
       "      <td>2.652344</td>\n",
       "      <td>2.496094</td>\n",
       "      <td>2.652344</td>\n",
       "      <td>2.496094</td>\n",
       "      <td>2.652344</td>\n",
       "      <td>2.496094</td>\n",
       "      <td>2.652344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3804</th>\n",
       "      <td>-0.969727</td>\n",
       "      <td>-0.969727</td>\n",
       "      <td>-0.968750</td>\n",
       "      <td>-0.971191</td>\n",
       "      <td>0.000772</td>\n",
       "      <td>0.997559</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.968750</td>\n",
       "      <td>0.971191</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.288818</td>\n",
       "      <td>4.125488</td>\n",
       "      <td>3.875000</td>\n",
       "      <td>0.704102</td>\n",
       "      <td>3.875000</td>\n",
       "      <td>0.704102</td>\n",
       "      <td>3.875000</td>\n",
       "      <td>0.704102</td>\n",
       "      <td>3.875000</td>\n",
       "      <td>0.704102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3805</th>\n",
       "      <td>-0.228760</td>\n",
       "      <td>-0.229248</td>\n",
       "      <td>-0.226440</td>\n",
       "      <td>-0.229980</td>\n",
       "      <td>0.001064</td>\n",
       "      <td>0.984375</td>\n",
       "      <td>0.000061</td>\n",
       "      <td>0.226440</td>\n",
       "      <td>0.229980</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.533691</td>\n",
       "      <td>4.081543</td>\n",
       "      <td>1.999023</td>\n",
       "      <td>5.375000</td>\n",
       "      <td>1.999023</td>\n",
       "      <td>5.375000</td>\n",
       "      <td>1.999023</td>\n",
       "      <td>5.375000</td>\n",
       "      <td>1.999023</td>\n",
       "      <td>5.375000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3806</th>\n",
       "      <td>0.542480</td>\n",
       "      <td>0.542480</td>\n",
       "      <td>0.544434</td>\n",
       "      <td>0.540039</td>\n",
       "      <td>0.001196</td>\n",
       "      <td>1.007812</td>\n",
       "      <td>0.000038</td>\n",
       "      <td>0.540039</td>\n",
       "      <td>0.544434</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.165649</td>\n",
       "      <td>2.902344</td>\n",
       "      <td>2.927734</td>\n",
       "      <td>2.886719</td>\n",
       "      <td>2.927734</td>\n",
       "      <td>2.886719</td>\n",
       "      <td>2.927734</td>\n",
       "      <td>2.886719</td>\n",
       "      <td>2.927734</td>\n",
       "      <td>2.886719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3807</th>\n",
       "      <td>-0.416504</td>\n",
       "      <td>-0.416016</td>\n",
       "      <td>-0.391846</td>\n",
       "      <td>-0.442383</td>\n",
       "      <td>0.014824</td>\n",
       "      <td>0.885742</td>\n",
       "      <td>0.000398</td>\n",
       "      <td>0.391846</td>\n",
       "      <td>0.442383</td>\n",
       "      <td>-1.257812</td>\n",
       "      <td>...</td>\n",
       "      <td>1.049805</td>\n",
       "      <td>8.858887</td>\n",
       "      <td>4.421875</td>\n",
       "      <td>4.300781</td>\n",
       "      <td>4.421875</td>\n",
       "      <td>4.300781</td>\n",
       "      <td>4.421875</td>\n",
       "      <td>4.300781</td>\n",
       "      <td>4.421875</td>\n",
       "      <td>4.300781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3808</th>\n",
       "      <td>-0.264648</td>\n",
       "      <td>-0.265137</td>\n",
       "      <td>-0.256836</td>\n",
       "      <td>-0.271240</td>\n",
       "      <td>0.004345</td>\n",
       "      <td>0.946777</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.256836</td>\n",
       "      <td>0.271240</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.351807</td>\n",
       "      <td>6.120117</td>\n",
       "      <td>6.332031</td>\n",
       "      <td>7.218750</td>\n",
       "      <td>6.332031</td>\n",
       "      <td>7.218750</td>\n",
       "      <td>6.332031</td>\n",
       "      <td>7.218750</td>\n",
       "      <td>6.332031</td>\n",
       "      <td>7.218750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3809</th>\n",
       "      <td>0.627930</td>\n",
       "      <td>0.627441</td>\n",
       "      <td>0.629395</td>\n",
       "      <td>0.626953</td>\n",
       "      <td>0.000646</td>\n",
       "      <td>1.003906</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>0.626953</td>\n",
       "      <td>0.629395</td>\n",
       "      <td>-3.072266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.249390</td>\n",
       "      <td>3.339050</td>\n",
       "      <td>2.880859</td>\n",
       "      <td>4.351562</td>\n",
       "      <td>2.880859</td>\n",
       "      <td>4.351562</td>\n",
       "      <td>2.880859</td>\n",
       "      <td>4.351562</td>\n",
       "      <td>2.880859</td>\n",
       "      <td>4.351562</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3810 rows × 188 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           orientation_X_mean  orientation_X_median  orientation_X_max  \\\n",
       "series_id                                                                \n",
       "0                   -0.758789             -0.758301          -0.758301   \n",
       "1                   -0.958496             -0.958496          -0.958496   \n",
       "2                   -0.512207             -0.512207          -0.509277   \n",
       "3                   -0.938965             -0.938965          -0.938965   \n",
       "4                   -0.891113             -0.891113          -0.886719   \n",
       "5                    0.464600              0.464600           0.465332   \n",
       "6                   -0.402344             -0.402344          -0.398682   \n",
       "7                   -0.925781             -0.925781          -0.925781   \n",
       "8                    0.012039              0.010986           0.018250   \n",
       "9                    0.789062              0.790039           0.824707   \n",
       "10                   0.849121              0.849121           0.850098   \n",
       "11                   0.494873              0.495117           0.502930   \n",
       "12                   0.333984              0.334473           0.338379   \n",
       "13                   0.374268              0.374512           0.380371   \n",
       "14                  -0.504395             -0.503906          -0.502930   \n",
       "15                  -0.941895             -0.941895          -0.941406   \n",
       "16                  -0.959473             -0.959961          -0.958008   \n",
       "17                   0.440186              0.440430           0.443604   \n",
       "18                  -0.288818             -0.288330          -0.282227   \n",
       "19                   0.829102              0.829102           0.836914   \n",
       "20                   0.913086              0.913086           0.916504   \n",
       "21                   0.013313              0.013306           0.013481   \n",
       "22                  -0.961914             -0.961914          -0.961914   \n",
       "23                  -0.283936             -0.284180          -0.281006   \n",
       "24                   0.954102              0.954102           0.955078   \n",
       "25                   0.345459              0.345215           0.354980   \n",
       "26                  -0.819336             -0.819336          -0.812500   \n",
       "27                   0.636230              0.636230           0.652344   \n",
       "28                   0.940430              0.940430           0.940918   \n",
       "29                   0.013443              0.013313           0.014542   \n",
       "...                       ...                   ...                ...   \n",
       "3780                -0.492676             -0.492676          -0.489502   \n",
       "3781                 0.574707              0.574219           0.587891   \n",
       "3782                 0.459717              0.459717           0.460205   \n",
       "3783                 0.476807              0.477051           0.477783   \n",
       "3784                -0.985352             -0.985352          -0.984863   \n",
       "3785                -0.784180             -0.784180          -0.778809   \n",
       "3786                -0.883301             -0.883301          -0.882324   \n",
       "3787                -0.834473             -0.834473          -0.833496   \n",
       "3788                 0.663574              0.663574           0.667480   \n",
       "3789                -0.579102             -0.579102          -0.541016   \n",
       "3790                 0.710449              0.710449           0.711426   \n",
       "3791                 0.804199              0.804199           0.806152   \n",
       "3792                 0.640625              0.640137           0.642578   \n",
       "3793                -0.977051             -0.977539          -0.975586   \n",
       "3794                 0.765137              0.765625           0.774902   \n",
       "3795                -0.349365             -0.349121          -0.345215   \n",
       "3796                -0.756348             -0.755371          -0.746094   \n",
       "3797                -0.115356             -0.116760          -0.060394   \n",
       "3798                -0.485840             -0.485352          -0.485107   \n",
       "3799                -0.174683             -0.174316          -0.169800   \n",
       "3800                -0.791504             -0.791992          -0.771973   \n",
       "3801                 0.806152              0.806152           0.806641   \n",
       "3802                -0.167847             -0.167480          -0.164795   \n",
       "3803                -0.940918             -0.941406          -0.925293   \n",
       "3804                -0.969727             -0.969727          -0.968750   \n",
       "3805                -0.228760             -0.229248          -0.226440   \n",
       "3806                 0.542480              0.542480           0.544434   \n",
       "3807                -0.416504             -0.416016          -0.391846   \n",
       "3808                -0.264648             -0.265137          -0.256836   \n",
       "3809                 0.627930              0.627441           0.629395   \n",
       "\n",
       "           orientation_X_min  orientation_X_std  orientation_X_maxtoMin  \\\n",
       "series_id                                                                 \n",
       "0                  -0.759766           0.000423                0.998047   \n",
       "1                  -0.958984           0.000244                0.999512   \n",
       "2                  -0.514160           0.001359                0.990723   \n",
       "3                  -0.939453           0.000244                0.999512   \n",
       "4                  -0.896973           0.002970                0.988770   \n",
       "5                   0.464111           0.000345                1.002930   \n",
       "6                  -0.405762           0.002129                0.982422   \n",
       "7                  -0.926270           0.000244                0.999512   \n",
       "8                   0.009155           0.002930                1.993164   \n",
       "9                   0.750977           0.021576                1.098633   \n",
       "10                  0.847168           0.000880                1.003906   \n",
       "11                  0.487305           0.004520                1.032227   \n",
       "12                  0.329346           0.002514                1.027344   \n",
       "13                  0.367188           0.003822                1.036133   \n",
       "14                 -0.505371           0.000598                0.995117   \n",
       "15                 -0.942871           0.000345                0.998535   \n",
       "16                 -0.961426           0.000732                0.996582   \n",
       "17                  0.434814           0.002729                1.020508   \n",
       "18                 -0.295898           0.003914                0.953613   \n",
       "19                  0.821289           0.004456                1.018555   \n",
       "20                  0.908691           0.002155                1.008789   \n",
       "21                  0.013222           0.000000                1.019531   \n",
       "22                 -0.962402           0.000000                0.999512   \n",
       "23                 -0.285400           0.001315                0.984375   \n",
       "24                  0.952637           0.000772                1.002930   \n",
       "25                  0.337402           0.005085                1.051758   \n",
       "26                 -0.826172           0.003944                0.983398   \n",
       "27                  0.621582           0.008995                1.049805   \n",
       "28                  0.939941           0.000345                1.000977   \n",
       "29                  0.012367           0.000690                1.175781   \n",
       "...                      ...                ...                     ...   \n",
       "3780               -0.495605           0.001811                0.987793   \n",
       "3781                0.563965           0.006561                1.041992   \n",
       "3782                0.459229           0.000345                1.001953   \n",
       "3783                0.475098           0.000732                1.005859   \n",
       "3784               -0.985352           0.000244                0.999512   \n",
       "3785               -0.789062           0.003029                0.986816   \n",
       "3786               -0.884766           0.000810                0.997070   \n",
       "3787               -0.835938           0.000732                0.997070   \n",
       "3788                0.659668           0.002211                1.011719   \n",
       "3789               -0.614746           0.021683                0.879883   \n",
       "3790                0.709473           0.000598                1.002930   \n",
       "3791                0.802734           0.001036                1.003906   \n",
       "3792                0.638672           0.001145                1.005859   \n",
       "3793               -0.978027           0.000732                0.997559   \n",
       "3794                0.755371           0.005627                1.025391   \n",
       "3795               -0.353027           0.002058                0.978027   \n",
       "3796               -0.770996           0.007133                0.967773   \n",
       "3797               -0.165405           0.030640                0.365234   \n",
       "3798               -0.487305           0.000732                0.995605   \n",
       "3799               -0.179199           0.002848                0.947754   \n",
       "3800               -0.810547           0.011284                0.952637   \n",
       "3801                0.804688           0.000546                1.001953   \n",
       "3802               -0.173096           0.002630                0.952148   \n",
       "3803               -0.955078           0.008629                0.968750   \n",
       "3804               -0.971191           0.000772                0.997559   \n",
       "3805               -0.229980           0.001064                0.984375   \n",
       "3806                0.540039           0.001196                1.007812   \n",
       "3807               -0.442383           0.014824                0.885742   \n",
       "3808               -0.271240           0.004345                0.946777   \n",
       "3809                0.626953           0.000646                1.003906   \n",
       "\n",
       "           orientation_X_mean_abs_chg  orientation_X_abs_min  \\\n",
       "series_id                                                      \n",
       "0                            0.000012               0.758301   \n",
       "1                            0.000019               0.958496   \n",
       "2                            0.000038               0.509277   \n",
       "3                            0.000012               0.938965   \n",
       "4                            0.000081               0.886719   \n",
       "5                            0.000042               0.464111   \n",
       "6                            0.000056               0.398682   \n",
       "7                            0.000042               0.925781   \n",
       "8                            0.000073               0.009155   \n",
       "9                            0.000581               0.750977   \n",
       "10                           0.000023               0.847168   \n",
       "11                           0.000123               0.487305   \n",
       "12                           0.000125               0.329346   \n",
       "13                           0.000104               0.367188   \n",
       "14                           0.000065               0.502930   \n",
       "15                           0.000027               0.941406   \n",
       "16                           0.000081               0.958008   \n",
       "17                           0.000069               0.434814   \n",
       "18                           0.000108               0.282227   \n",
       "19                           0.000123               0.821289   \n",
       "20                           0.000062               0.908691   \n",
       "21                           0.000005               0.013222   \n",
       "22                           0.000004               0.961914   \n",
       "23                           0.000054               0.281006   \n",
       "24                           0.000019               0.952637   \n",
       "25                           0.000138               0.337402   \n",
       "26                           0.000108               0.812500   \n",
       "27                           0.000242               0.621582   \n",
       "28                           0.000035               0.939941   \n",
       "29                           0.000021               0.012367   \n",
       "...                               ...                    ...   \n",
       "3780                         0.000065               0.489502   \n",
       "3781                         0.000204               0.563965   \n",
       "3782                         0.000033               0.459229   \n",
       "3783                         0.000050               0.475098   \n",
       "3784                         0.000012               0.984863   \n",
       "3785                         0.000081               0.778809   \n",
       "3786                         0.000019               0.882324   \n",
       "3787                         0.000035               0.833496   \n",
       "3788                         0.000108               0.659668   \n",
       "3789                         0.000581               0.541016   \n",
       "3790                         0.000108               0.709473   \n",
       "3791                         0.000092               0.802734   \n",
       "3792                         0.000031               0.638672   \n",
       "3793                         0.000019               0.975586   \n",
       "3794                         0.000154               0.755371   \n",
       "3795                         0.000069               0.345215   \n",
       "3796                         0.000196               0.746094   \n",
       "3797                         0.000827               0.060394   \n",
       "3798                         0.000038               0.485107   \n",
       "3799                         0.000087               0.169800   \n",
       "3800                         0.000304               0.771973   \n",
       "3801                         0.000073               0.804688   \n",
       "3802                         0.000081               0.164795   \n",
       "3803                         0.000234               0.925293   \n",
       "3804                         0.000035               0.968750   \n",
       "3805                         0.000061               0.226440   \n",
       "3806                         0.000038               0.540039   \n",
       "3807                         0.000398               0.391846   \n",
       "3808                         0.000121               0.256836   \n",
       "3809                         0.000050               0.626953   \n",
       "\n",
       "           orientation_X_abs_max  orientation_X_kurtosis  ...  \\\n",
       "series_id                                                 ...   \n",
       "0                       0.759766               -3.072266  ...   \n",
       "1                       0.958984               -3.072266  ...   \n",
       "2                       0.514160               -3.072266  ...   \n",
       "3                       0.939453               -3.072266  ...   \n",
       "4                       0.896973               -3.072266  ...   \n",
       "5                       0.465332               -3.072266  ...   \n",
       "6                       0.405762               -3.072266  ...   \n",
       "7                       0.926270               -3.072266  ...   \n",
       "8                       0.018250               -3.072266  ...   \n",
       "9                       0.824707               -1.207031  ...   \n",
       "10                      0.850098               -3.072266  ...   \n",
       "11                      0.502930               -3.072266  ...   \n",
       "12                      0.338379               -3.072266  ...   \n",
       "13                      0.380371               -3.072266  ...   \n",
       "14                      0.505371               -3.072266  ...   \n",
       "15                      0.942871               -3.072266  ...   \n",
       "16                      0.961426               -3.072266  ...   \n",
       "17                      0.443604               -3.072266  ...   \n",
       "18                      0.295898               -3.072266  ...   \n",
       "19                      0.836914               -3.072266  ...   \n",
       "20                      0.916504               -3.072266  ...   \n",
       "21                      0.013481                0.000000  ...   \n",
       "22                      0.962402               -3.072266  ...   \n",
       "23                      0.285400               -3.072266  ...   \n",
       "24                      0.955078               -3.072266  ...   \n",
       "25                      0.354980               -3.072266  ...   \n",
       "26                      0.826172               -3.072266  ...   \n",
       "27                      0.652344               -1.494141  ...   \n",
       "28                      0.940918               -3.072266  ...   \n",
       "29                      0.014542               -3.072266  ...   \n",
       "...                          ...                     ...  ...   \n",
       "3780                    0.495605               -3.072266  ...   \n",
       "3781                    0.587891               -2.806641  ...   \n",
       "3782                    0.460205               -3.072266  ...   \n",
       "3783                    0.477783               -3.072266  ...   \n",
       "3784                    0.985352               -3.072266  ...   \n",
       "3785                    0.789062               -3.072266  ...   \n",
       "3786                    0.884766               -3.072266  ...   \n",
       "3787                    0.835938               -3.072266  ...   \n",
       "3788                    0.667480               -3.072266  ...   \n",
       "3789                    0.614746               -1.211914  ...   \n",
       "3790                    0.711426               -3.072266  ...   \n",
       "3791                    0.806152               -3.072266  ...   \n",
       "3792                    0.642578               -3.072266  ...   \n",
       "3793                    0.978027               -3.072266  ...   \n",
       "3794                    0.774902               -3.072266  ...   \n",
       "3795                    0.353027               -3.072266  ...   \n",
       "3796                    0.770996               -1.933594  ...   \n",
       "3797                    0.165405               -1.193359  ...   \n",
       "3798                    0.487305               -3.072266  ...   \n",
       "3799                    0.179199               -3.072266  ...   \n",
       "3800                    0.810547               -1.343750  ...   \n",
       "3801                    0.806641               -3.072266  ...   \n",
       "3802                    0.173096               -3.072266  ...   \n",
       "3803                    0.955078               -1.563477  ...   \n",
       "3804                    0.971191               -3.072266  ...   \n",
       "3805                    0.229980               -3.072266  ...   \n",
       "3806                    0.544434               -3.072266  ...   \n",
       "3807                    0.442383               -1.257812  ...   \n",
       "3808                    0.271240               -3.072266  ...   \n",
       "3809                    0.629395               -3.072266  ...   \n",
       "\n",
       "           z_planar_linr_acc_skewness  z_planar_linr_acc_abs_avg  \\\n",
       "series_id                                                          \n",
       "0                           -0.295654                   2.837158   \n",
       "1                            0.109497                   3.401215   \n",
       "2                           -0.008812                   3.178711   \n",
       "3                            0.500977                   6.083130   \n",
       "4                           -0.520020                   2.586792   \n",
       "5                            0.343262                   4.263306   \n",
       "6                            0.053986                   2.586914   \n",
       "7                            0.624023                   5.661865   \n",
       "8                           -0.140991                   2.389648   \n",
       "9                            0.195312                   4.376953   \n",
       "10                           0.173340                   3.347168   \n",
       "11                           0.801758                   4.684204   \n",
       "12                          -0.294189                   3.912231   \n",
       "13                           0.196777                   3.135742   \n",
       "14                           1.115234                   8.377579   \n",
       "15                          -0.071777                   3.953430   \n",
       "16                           0.512207                  10.738770   \n",
       "17                           0.191284                   3.021973   \n",
       "18                          -0.000175                   4.200928   \n",
       "19                          -0.422119                   3.030273   \n",
       "20                           0.028412                   3.472412   \n",
       "21                           0.675781                   2.923828   \n",
       "22                          -0.260254                   2.919922   \n",
       "23                           0.063232                   3.687622   \n",
       "24                           0.022354                   3.032227   \n",
       "25                           0.427979                   3.218750   \n",
       "26                           0.708496                   3.332031   \n",
       "27                          -0.045502                   2.750488   \n",
       "28                           0.432617                   4.556030   \n",
       "29                           0.065186                   3.023926   \n",
       "...                               ...                        ...   \n",
       "3780                         0.064270                   3.856934   \n",
       "3781                        -0.021530                   5.414917   \n",
       "3782                        -0.066345                   3.328552   \n",
       "3783                         0.765137                   4.861328   \n",
       "3784                         0.220337                   4.111206   \n",
       "3785                         0.274414                   3.432617   \n",
       "3786                        -0.109314                   2.882660   \n",
       "3787                         0.071045                   3.593018   \n",
       "3788                         0.018143                   2.746979   \n",
       "3789                        -0.779297                   2.478027   \n",
       "3790                         1.122070                   8.678223   \n",
       "3791                              inf                  61.619873   \n",
       "3792                         0.142700                   2.617126   \n",
       "3793                         0.181396                   3.117432   \n",
       "3794                         0.318115                   5.485596   \n",
       "3795                         0.535156                   5.279510   \n",
       "3796                        -0.156372                   2.261719   \n",
       "3797                        -0.048187                   2.982422   \n",
       "3798                         0.073425                   3.718994   \n",
       "3799                         0.492188                   4.726562   \n",
       "3800                         0.338379                   3.418579   \n",
       "3801                         0.708008                   6.780273   \n",
       "3802                         0.307861                   3.896484   \n",
       "3803                        -0.150513                   2.787598   \n",
       "3804                         0.288818                   4.125488   \n",
       "3805                         0.533691                   4.081543   \n",
       "3806                        -0.165649                   2.902344   \n",
       "3807                         1.049805                   8.858887   \n",
       "3808                         0.351807                   6.120117   \n",
       "3809                         0.249390                   3.339050   \n",
       "\n",
       "           orientation_X_first  orientation_X_last  orientation_Y_first  \\\n",
       "series_id                                                                 \n",
       "0                     2.232422            0.964844             2.232422   \n",
       "1                     3.136719            2.072266             3.136719   \n",
       "2                     3.628906            3.466797             3.628906   \n",
       "3                     1.804688            2.570312             1.804688   \n",
       "4                     3.132812            2.775391             3.132812   \n",
       "5                     3.312500            6.117188             3.312500   \n",
       "6                     3.294922            2.343750             3.294922   \n",
       "7                     6.355469            2.447266             6.355469   \n",
       "8                     2.150391            2.042969             2.150391   \n",
       "9                     8.492188            5.492188             8.492188   \n",
       "10                    2.427734            3.025391             2.427734   \n",
       "11                    3.535156            2.636719             3.535156   \n",
       "12                    5.105469            4.960938             5.105469   \n",
       "13                    2.837891            2.181641             2.837891   \n",
       "14                    3.576172            8.218750             3.576172   \n",
       "15                    4.179688            2.992188             4.179688   \n",
       "16                    7.359375            4.679688             7.359375   \n",
       "17                    2.611328            1.994141             2.611328   \n",
       "18                    1.773438            3.347656             1.773438   \n",
       "19                    3.892578            2.720703             3.892578   \n",
       "20                    2.796875            3.818359             2.796875   \n",
       "21                    2.851562            2.912109             2.851562   \n",
       "22                    2.931641            2.933594             2.931641   \n",
       "23                    3.281250            2.673828             3.281250   \n",
       "24                    3.472656            3.171875             3.472656   \n",
       "25                    2.343750            2.935547             2.343750   \n",
       "26                    2.462891            2.585938             2.462891   \n",
       "27                    2.109375            2.957031             2.109375   \n",
       "28                    2.375000            4.183594             2.375000   \n",
       "29                    3.048828            1.983398             3.048828   \n",
       "...                        ...                 ...                  ...   \n",
       "3780                  5.933594            2.632812             5.933594   \n",
       "3781                  5.339844            7.160156             5.339844   \n",
       "3782                  0.416260            2.158203             0.416260   \n",
       "3783                  3.123047            2.240234             3.123047   \n",
       "3784                  1.308594            6.316406             1.308594   \n",
       "3785                  2.193359            2.974609             2.193359   \n",
       "3786                  4.277344            3.291016             4.277344   \n",
       "3787                  4.781250            4.218750             4.781250   \n",
       "3788                  0.115051            2.097656             0.115051   \n",
       "3789                  2.648438            3.279297             2.648438   \n",
       "3790                  2.613281            5.527344             2.613281   \n",
       "3791                  2.886719           22.500000             2.886719   \n",
       "3792                  2.457031            3.605469             2.457031   \n",
       "3793                  3.138672            2.347656             3.138672   \n",
       "3794                  6.613281            0.970703             6.613281   \n",
       "3795                  1.666016            1.009766             1.666016   \n",
       "3796                  2.263672            2.373047             2.263672   \n",
       "3797                  4.140625            3.074219             4.140625   \n",
       "3798                  6.210938            3.748047             6.210938   \n",
       "3799                  2.017578            4.562500             2.017578   \n",
       "3800                  1.625977            3.628906             1.625977   \n",
       "3801                  2.761719            1.979492             2.761719   \n",
       "3802                  5.730469            3.503906             5.730469   \n",
       "3803                  2.496094            2.652344             2.496094   \n",
       "3804                  3.875000            0.704102             3.875000   \n",
       "3805                  1.999023            5.375000             1.999023   \n",
       "3806                  2.927734            2.886719             2.927734   \n",
       "3807                  4.421875            4.300781             4.421875   \n",
       "3808                  6.332031            7.218750             6.332031   \n",
       "3809                  2.880859            4.351562             2.880859   \n",
       "\n",
       "           orientation_Y_last  orientation_Z_first  orientation_Z_last  \\\n",
       "series_id                                                                \n",
       "0                    0.964844             2.232422            0.964844   \n",
       "1                    2.072266             3.136719            2.072266   \n",
       "2                    3.466797             3.628906            3.466797   \n",
       "3                    2.570312             1.804688            2.570312   \n",
       "4                    2.775391             3.132812            2.775391   \n",
       "5                    6.117188             3.312500            6.117188   \n",
       "6                    2.343750             3.294922            2.343750   \n",
       "7                    2.447266             6.355469            2.447266   \n",
       "8                    2.042969             2.150391            2.042969   \n",
       "9                    5.492188             8.492188            5.492188   \n",
       "10                   3.025391             2.427734            3.025391   \n",
       "11                   2.636719             3.535156            2.636719   \n",
       "12                   4.960938             5.105469            4.960938   \n",
       "13                   2.181641             2.837891            2.181641   \n",
       "14                   8.218750             3.576172            8.218750   \n",
       "15                   2.992188             4.179688            2.992188   \n",
       "16                   4.679688             7.359375            4.679688   \n",
       "17                   1.994141             2.611328            1.994141   \n",
       "18                   3.347656             1.773438            3.347656   \n",
       "19                   2.720703             3.892578            2.720703   \n",
       "20                   3.818359             2.796875            3.818359   \n",
       "21                   2.912109             2.851562            2.912109   \n",
       "22                   2.933594             2.931641            2.933594   \n",
       "23                   2.673828             3.281250            2.673828   \n",
       "24                   3.171875             3.472656            3.171875   \n",
       "25                   2.935547             2.343750            2.935547   \n",
       "26                   2.585938             2.462891            2.585938   \n",
       "27                   2.957031             2.109375            2.957031   \n",
       "28                   4.183594             2.375000            4.183594   \n",
       "29                   1.983398             3.048828            1.983398   \n",
       "...                       ...                  ...                 ...   \n",
       "3780                 2.632812             5.933594            2.632812   \n",
       "3781                 7.160156             5.339844            7.160156   \n",
       "3782                 2.158203             0.416260            2.158203   \n",
       "3783                 2.240234             3.123047            2.240234   \n",
       "3784                 6.316406             1.308594            6.316406   \n",
       "3785                 2.974609             2.193359            2.974609   \n",
       "3786                 3.291016             4.277344            3.291016   \n",
       "3787                 4.218750             4.781250            4.218750   \n",
       "3788                 2.097656             0.115051            2.097656   \n",
       "3789                 3.279297             2.648438            3.279297   \n",
       "3790                 5.527344             2.613281            5.527344   \n",
       "3791                22.500000             2.886719           22.500000   \n",
       "3792                 3.605469             2.457031            3.605469   \n",
       "3793                 2.347656             3.138672            2.347656   \n",
       "3794                 0.970703             6.613281            0.970703   \n",
       "3795                 1.009766             1.666016            1.009766   \n",
       "3796                 2.373047             2.263672            2.373047   \n",
       "3797                 3.074219             4.140625            3.074219   \n",
       "3798                 3.748047             6.210938            3.748047   \n",
       "3799                 4.562500             2.017578            4.562500   \n",
       "3800                 3.628906             1.625977            3.628906   \n",
       "3801                 1.979492             2.761719            1.979492   \n",
       "3802                 3.503906             5.730469            3.503906   \n",
       "3803                 2.652344             2.496094            2.652344   \n",
       "3804                 0.704102             3.875000            0.704102   \n",
       "3805                 5.375000             1.999023            5.375000   \n",
       "3806                 2.886719             2.927734            2.886719   \n",
       "3807                 4.300781             4.421875            4.300781   \n",
       "3808                 7.218750             6.332031            7.218750   \n",
       "3809                 4.351562             2.880859            4.351562   \n",
       "\n",
       "           orientation_W_first  orientation_W_last  \n",
       "series_id                                           \n",
       "0                     2.232422            0.964844  \n",
       "1                     3.136719            2.072266  \n",
       "2                     3.628906            3.466797  \n",
       "3                     1.804688            2.570312  \n",
       "4                     3.132812            2.775391  \n",
       "5                     3.312500            6.117188  \n",
       "6                     3.294922            2.343750  \n",
       "7                     6.355469            2.447266  \n",
       "8                     2.150391            2.042969  \n",
       "9                     8.492188            5.492188  \n",
       "10                    2.427734            3.025391  \n",
       "11                    3.535156            2.636719  \n",
       "12                    5.105469            4.960938  \n",
       "13                    2.837891            2.181641  \n",
       "14                    3.576172            8.218750  \n",
       "15                    4.179688            2.992188  \n",
       "16                    7.359375            4.679688  \n",
       "17                    2.611328            1.994141  \n",
       "18                    1.773438            3.347656  \n",
       "19                    3.892578            2.720703  \n",
       "20                    2.796875            3.818359  \n",
       "21                    2.851562            2.912109  \n",
       "22                    2.931641            2.933594  \n",
       "23                    3.281250            2.673828  \n",
       "24                    3.472656            3.171875  \n",
       "25                    2.343750            2.935547  \n",
       "26                    2.462891            2.585938  \n",
       "27                    2.109375            2.957031  \n",
       "28                    2.375000            4.183594  \n",
       "29                    3.048828            1.983398  \n",
       "...                        ...                 ...  \n",
       "3780                  5.933594            2.632812  \n",
       "3781                  5.339844            7.160156  \n",
       "3782                  0.416260            2.158203  \n",
       "3783                  3.123047            2.240234  \n",
       "3784                  1.308594            6.316406  \n",
       "3785                  2.193359            2.974609  \n",
       "3786                  4.277344            3.291016  \n",
       "3787                  4.781250            4.218750  \n",
       "3788                  0.115051            2.097656  \n",
       "3789                  2.648438            3.279297  \n",
       "3790                  2.613281            5.527344  \n",
       "3791                  2.886719           22.500000  \n",
       "3792                  2.457031            3.605469  \n",
       "3793                  3.138672            2.347656  \n",
       "3794                  6.613281            0.970703  \n",
       "3795                  1.666016            1.009766  \n",
       "3796                  2.263672            2.373047  \n",
       "3797                  4.140625            3.074219  \n",
       "3798                  6.210938            3.748047  \n",
       "3799                  2.017578            4.562500  \n",
       "3800                  1.625977            3.628906  \n",
       "3801                  2.761719            1.979492  \n",
       "3802                  5.730469            3.503906  \n",
       "3803                  2.496094            2.652344  \n",
       "3804                  3.875000            0.704102  \n",
       "3805                  1.999023            5.375000  \n",
       "3806                  2.927734            2.886719  \n",
       "3807                  4.421875            4.300781  \n",
       "3808                  6.332031            7.218750  \n",
       "3809                  2.880859            4.351562  \n",
       "\n",
       "[3810 rows x 188 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.drop(columns=[])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.fillna(0,inplace=True)\n",
    "train.replace(-np.inf,0,inplace=True)\n",
    "train.replace(np.inf,0,inplace=True)\n",
    "test.fillna(0,inplace=True)\n",
    "test.replace(-np.inf,0,inplace=True)\n",
    "test.replace(np.inf,0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3468, 188) (3468,) (363, 188) (363,)\n"
     ]
    }
   ],
   "source": [
    "x_train = train.iloc[trn_df.index]\n",
    "y_train = label['surface'].iloc[trn_df.index]\n",
    "\n",
    "x_val = train.iloc[val_df.index]\n",
    "y_val = label['surface'].iloc[val_df.index]\n",
    "\n",
    "print(x_train.shape, y_train.shape, x_val.shape, y_val.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def lb_dist(model):\n",
    "    model.fit(x_train, y_train)\n",
    "    print(\"Train Acc :: \", accuracy_score(y_train, model.predict(x_train)))\n",
    "    print(\"Valid Acc :: \", accuracy_score(y_val, model.predict(x_val)))\n",
    "    print(\"CV Accuracy :: \", cross_val_score(rand, train, label['surface'], cv=5).mean())\n",
    "\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
       "            max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "            min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "            min_samples_leaf=1, min_samples_split=2,\n",
       "            min_weight_fraction_leaf=0.0, n_estimators=200, n_jobs=None,\n",
       "            oob_score=False, random_state=1337, verbose=0,\n",
       "            warm_start=False)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rand = RandomForestClassifier(n_estimators=200, random_state=1337)\n",
    "rand.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train_y_grouped = pd.read_csv('y_train_with_groups.csv')\n",
    "df_train_y_grouped['series_id']=df_train_y_grouped['Unnamed: 0']\n",
    "df_train_y_grouped =df_train_y_grouped.drop(columns='Unnamed: 0')\n",
    "df_train_y_grouped.set_index(inplace=True, keys=df_train_y_grouped['series_id'])\n",
    "df_train_y_grouped.drop(columns=['series_id'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train_y_grouped.sort_values(by=['run_id', 'run_pos'], inplace=True)\n",
    "gp = df_train_y_grouped.groupby('run_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_preds=np.zeros((train.shape[0],1))\n",
    "for runid in range(len(df_train_y_grouped['run_id'].unique())):\n",
    "    train_preds[df_train_y_grouped[df_train_y_grouped['run_id']==runid].index,0]=mode(\n",
    "        rand.predict(train)[df_train_y_grouped[df_train_y_grouped['run_id']==runid].index])[0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.696969696969697\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
       "            max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "            min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "            min_samples_leaf=1, min_samples_split=2,\n",
       "            min_weight_fraction_leaf=0.0, n_estimators=200, n_jobs=None,\n",
       "            oob_score=False, random_state=1337, verbose=0,\n",
       "            warm_start=False)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(accuracy_score(y_val,train_preds[x_val.index]))\n",
    "rand.fit(train, label['surface'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Int64Index([  45,  619,  814, 1598, 1945,  480,  695, 1279,  621, 1648,\n",
       "            ...\n",
       "             380, 2343, 2755, 3636,  474, 1322, 1446, 2476, 2736,  832],\n",
       "           dtype='int64', name='series_id', length=162)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test_y_grouped = pd.read_csv(\"df_test_y_grouped.csv\")\n",
    "df_test_y_grouped['series_id']=df_test_y_grouped['Unnamed: 0']\n",
    "df_test_y_grouped=df_test_y_grouped.drop(columns='Unnamed: 0')\n",
    "df_test_y_grouped.set_index(inplace=True, keys=df_test_y_grouped['series_id'])\n",
    "df_test_y_grouped.drop(columns=['series_id'], inplace=True)\n",
    "df_test_y_grouped[df_test_y_grouped['run_id']==0].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_test_y_grouped.sort_values(by=['run_id', 'run_pos'], inplace=True)\n",
    "gp_test = df_test_y_grouped.groupby('run_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n",
      "c:\\users\\mert\\anaconda3\\envs\\ml_env\\lib\\site-packages\\pandas\\core\\indexing.py:190: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    }
   ],
   "source": [
    "for runid in range(len(df_test_y_grouped['run_id'].unique())):\n",
    "    sub['surface'].iloc[df_test_y_grouped[df_test_y_grouped['run_id']==runid].index]=mode(\n",
    "        rand.predict(test)[df_test_y_grouped[df_test_y_grouped['run_id']==runid].index])[0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "sub['surface']=le.inverse_transform(sub['surface'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
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       "      <td>2</td>\n",
       "      <td>tiled</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>carpet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>soft_tiles</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   series_id                 surface\n",
       "0          0  hard_tiles_large_space\n",
       "1          1                concrete\n",
       "2          2                   tiled\n",
       "3          3                  carpet\n",
       "4          4              soft_tiles"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub.to_csv('bmg_sub.csv', index=False)\n",
    "sub.head()"
   ]
  }
 ],
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