diff --git a/2-second-project/tdt/DataViz.ipynb b/2-second-project/tdt/DataViz.ipynb
index 5b62cce..63aa556 100644
--- a/2-second-project/tdt/DataViz.ipynb
+++ b/2-second-project/tdt/DataViz.ipynb
@@ -3,7 +3,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "9aa64ac0",
+   "id": "a33b4ae2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -16,7 +16,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "d312c8e1",
+   "id": "bfcb55c8",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -28,7 +28,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "c04ba7f6",
+   "id": "7bb04d71",
    "metadata": {
     "tags": []
    },
@@ -74,7 +74,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "45e23af8",
+   "id": "9adc333e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -89,7 +89,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "31a7d280",
+   "id": "dfc32785",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -104,7 +104,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "ec0dd3cb",
+   "id": "09a66223",
    "metadata": {},
    "outputs": [
     {
@@ -140,7 +140,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "2d11eb89",
+   "id": "07df007d",
    "metadata": {
     "tags": []
    },
@@ -594,7 +594,7 @@
   {
    "cell_type": "code",
    "execution_count": 81,
-   "id": "9ee5b898",
+   "id": "8d956063",
    "metadata": {
     "tags": []
    },
@@ -1052,8 +1052,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
-   "id": "083ba677",
+   "execution_count": 95,
+   "id": "97c3ba71",
    "metadata": {
     "tags": []
    },
@@ -1106,8 +1106,8 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>-0.089895</td>\n",
        "      <td>1.755665</td>\n",
        "      <td>0.234344</td>\n",
@@ -1130,8 +1130,8 @@
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>1</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>-0.089738</td>\n",
        "      <td>1.755732</td>\n",
        "      <td>0.234542</td>\n",
@@ -1154,8 +1154,8 @@
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>2</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>-0.089347</td>\n",
        "      <td>1.755780</td>\n",
        "      <td>0.234738</td>\n",
@@ -1178,8 +1178,8 @@
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>3</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>-0.088938</td>\n",
        "      <td>1.755686</td>\n",
        "      <td>0.234353</td>\n",
@@ -1202,8 +1202,8 @@
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>4</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>-0.088715</td>\n",
        "      <td>1.755643</td>\n",
        "      <td>0.234471</td>\n",
@@ -1250,8 +1250,8 @@
        "    <tr>\n",
        "      <th>2020</th>\n",
        "      <td>2020</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.067835</td>\n",
        "      <td>1.149886</td>\n",
        "      <td>0.087708</td>\n",
@@ -1274,8 +1274,8 @@
        "    <tr>\n",
        "      <th>2021</th>\n",
        "      <td>2021</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.076106</td>\n",
        "      <td>1.142307</td>\n",
        "      <td>0.086917</td>\n",
@@ -1298,8 +1298,8 @@
        "    <tr>\n",
        "      <th>2022</th>\n",
        "      <td>2022</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.085397</td>\n",
        "      <td>1.135880</td>\n",
        "      <td>0.086078</td>\n",
@@ -1322,8 +1322,8 @@
        "    <tr>\n",
        "      <th>2023</th>\n",
        "      <td>2023</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.096437</td>\n",
        "      <td>1.129293</td>\n",
        "      <td>0.084847</td>\n",
@@ -1346,8 +1346,8 @@
        "    <tr>\n",
        "      <th>2024</th>\n",
        "      <td>2024</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.106890</td>\n",
        "      <td>1.123694</td>\n",
        "      <td>0.084149</td>\n",
@@ -1374,17 +1374,17 @@
       ],
       "text/plain": [
        "      Unnamed: 0  LeftHandTrackingAccuracy  RightHandTrackingAccuracy  \\\n",
-       "0              0                       1.0                        1.0   \n",
-       "1              1                       1.0                        1.0   \n",
-       "2              2                       1.0                        1.0   \n",
-       "3              3                       1.0                        1.0   \n",
-       "4              4                       1.0                        1.0   \n",
+       "0              0                       0.0                        0.0   \n",
+       "1              1                       0.0                        0.0   \n",
+       "2              2                       0.0                        0.0   \n",
+       "3              3                       0.0                        0.0   \n",
+       "4              4                       0.0                        0.0   \n",
        "...          ...                       ...                        ...   \n",
-       "2020        2020                       1.0                        1.0   \n",
-       "2021        2021                       1.0                        1.0   \n",
-       "2022        2022                       1.0                        1.0   \n",
-       "2023        2023                       1.0                        1.0   \n",
-       "2024        2024                       1.0                        1.0   \n",
+       "2020        2020                       0.0                        0.0   \n",
+       "2021        2021                       0.0                        0.0   \n",
+       "2022        2022                       0.0                        0.0   \n",
+       "2023        2023                       0.0                        0.0   \n",
+       "2024        2024                       0.0                        0.0   \n",
        "\n",
        "      CenterEyeAnchor_pos_X  CenterEyeAnchor_pos_Y  CenterEyeAnchor_pos_Z  \\\n",
        "0                 -0.089895               1.755665               0.234344   \n",
@@ -1493,7 +1493,7 @@
        "[2025 rows x 339 columns]"
       ]
      },
-     "execution_count": 82,
+     "execution_count": 95,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1512,31 +1512,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
-   "id": "00edea73",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# d_entry = c_entry.where(c_entry['LeftHandTrackingAccuracy'] == c_entry['RightHandTrackingAccuracy']).dropna().reset_index(drop=True)\n",
-    "# a = entry.copy()\n",
-    "# a['data'] = d_entry.drop(droptable, axis=1)\n",
-    "# print(a['data'].shape)\n",
-    "# print(a['data'].dtypes)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 84,
-   "id": "547f63d2",
+   "execution_count": 96,
+   "id": "7ab1aa62",
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(2025, 339)\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
        "<BatchDataset shapes: ((None, None, 2100), (None,)), types: (tf.float64, tf.int32)>"
       ]
      },
-     "execution_count": 84,
+     "execution_count": 96,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1547,8 +1540,8 @@
     "\n",
     "def slicing(entry):\n",
     "    stride = 150\n",
-    "    \n",
-    "    entry['data'] = pad_sequences(entry['data'].to_numpy().T,\n",
+    "    print(entry['data'].to_numpy().shape)\n",
+    "    entry['data'] = pad_sequences(entry['data'].to_numpy(),\n",
     "                          maxlen=(int(entry['data'].shape[0]/stride)+1)*stride,\n",
     "                          dtype='float64',\n",
     "                          padding='pre', truncating='post'\n",
@@ -1570,8 +1563,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
-   "id": "620c529b",
+   "execution_count": 97,
+   "id": "8827bbab",
    "metadata": {},
    "outputs": [
     {
@@ -1579,19 +1572,112 @@
      "output_type": "stream",
      "text": [
       "tf.Tensor(\n",
-      "[[[ 0.000000e+00  0.000000e+00  0.000000e+00 ...  2.022000e+03\n",
-      "    2.023000e+03  2.024000e+03]\n",
-      "  [ 0.000000e+00  0.000000e+00  0.000000e+00 ...  1.000000e+00\n",
-      "    1.000000e+00  1.000000e+00]\n",
-      "  [ 0.000000e+00  0.000000e+00  0.000000e+00 ...  1.000000e+00\n",
-      "    1.000000e+00  1.000000e+00]\n",
+      "[[[  0.       0.       0.     ... 310.8786 343.5717 185.1874]\n",
+      "  [  0.       0.       0.     ... 311.1056 343.7456 185.6717]\n",
+      "  [  0.       0.       0.     ... 311.2307 343.7971 185.9125]\n",
       "  ...\n",
-      "  [ 0.000000e+00  0.000000e+00  0.000000e+00 ...  1.247579e+00\n",
-      "    1.257665e+00  1.273240e+00]\n",
-      "  [ 0.000000e+00  0.000000e+00  0.000000e+00 ...  6.340001e-01\n",
-      "    6.261733e-01  6.128760e-01]\n",
-      "  [ 0.000000e+00  0.000000e+00  0.000000e+00 ... -8.997461e-02\n",
-      "   -8.650930e-02 -8.193973e-02]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "  [  0.       0.       0.     ... 334.9102 105.7513 287.5223]\n",
+      "  [  0.       0.       0.     ... 334.6709 104.5253 287.9581]\n",
+      "  [  0.       0.       0.     ... 334.5766 103.5059 288.4085]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.        0.        0.      ... 337.3954  115.2253  239.2146 ]\n",
+      "  [  0.        0.        0.      ... 337.7683  115.3956  240.4796 ]\n",
+      "  [  0.        0.        0.      ... 338.0132  115.4679  241.2587 ]\n",
+      "  ...\n",
+      "  [  0.        0.        0.      ... 332.9107   41.93251 124.3949 ]\n",
+      "  [  0.        0.        0.      ... 333.1059   40.51485 124.8919 ]\n",
+      "  [  0.        0.        0.      ... 332.9174   39.48595 125.2935 ]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.       0.       0.     ... 334.441  102.5691 288.6859]\n",
+      "  [  0.       0.       0.     ... 334.4541 101.1844 290.0429]\n",
+      "  [  0.       0.       0.     ... 334.5445 100.4508 291.0764]\n",
+      "  ...\n",
+      "  [  0.       0.       0.     ... 342.0367 322.5176 287.4604]\n",
+      "  [  0.       0.       0.     ... 341.5087 322.9041 288.0399]\n",
+      "  [  0.       0.       0.     ... 341.0814 323.1584 288.53  ]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.        0.        0.      ... 332.7831   38.47573 125.6316 ]\n",
+      "  [  0.        0.        0.      ... 332.4827   36.4628  126.487  ]\n",
+      "  [  0.        0.        0.      ... 332.2903   35.13992 127.0712 ]\n",
+      "  ...\n",
+      "  [  0.        0.        0.      ... 358.9955   91.98264 223.499  ]\n",
+      "  [  0.        0.        0.      ... 358.6208   91.1073  225.3601 ]\n",
+      "  [  0.        0.        0.      ... 358.354    90.26964 227.1508 ]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.        0.        0.      ... 340.7549  323.3292  289.6002 ]\n",
+      "  [  0.        0.        0.      ... 340.5391  323.4655  290.4398 ]\n",
+      "  [  0.        0.        0.      ... 340.3628  323.5816  291.6447 ]\n",
+      "  ...\n",
+      "  [  0.        0.        0.      ... 334.6424  149.6268   96.6635 ]\n",
+      "  [  0.        0.        0.      ... 335.1271  151.0876   96.39161]\n",
+      "  [  0.        0.        0.      ... 335.5759  152.4971   96.23958]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.        0.        0.      ... 358.0558   89.08697 228.282  ]\n",
+      "  [  0.        0.        0.      ... 357.9095   88.468   228.3914 ]\n",
+      "  [  0.        0.        0.      ... 357.7622   87.76212 228.7186 ]\n",
+      "  ...\n",
+      "  [  0.        0.        0.      ... 350.4678  191.8058  293.6591 ]\n",
+      "  [  0.        0.        0.      ... 349.4155  191.758   290.0341 ]\n",
+      "  [  0.        0.        0.      ... 348.4454  191.7047  286.47   ]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.         0.         0.       ... 336.1516   154.5288    95.77281 ]\n",
+      "  [  0.         0.         0.       ... 336.4283   155.5994    95.43106 ]\n",
+      "  [  0.         0.         0.       ... 336.7111   156.6993    95.16699 ]\n",
+      "  ...\n",
+      "  [  0.         0.         0.       ...   1.877451 189.7006   176.2247  ]\n",
+      "  [  0.         0.         0.       ...   2.298272 189.6146   174.1894  ]\n",
+      "  [  0.         0.         0.       ...   2.357256 189.587    173.9407  ]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.        0.        0.      ... 347.4656  193.364   277.8619 ]\n",
+      "  [  0.        0.        0.      ... 347.1607  194.9414  272.1756 ]\n",
+      "  [  0.        0.        0.      ... 346.816   196.2879  266.7031 ]\n",
+      "  ...\n",
+      "  [  0.        0.        0.      ... 328.2634  195.3502   53.96029]\n",
+      "  [  0.        0.        0.      ... 328.1786  200.2938   56.4752 ]\n",
+      "  [  0.        0.        0.      ... 328.5285  204.5934   59.88613]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.         0.         0.       ...   2.574736 189.5766   172.9151  ]\n",
+      "  [  0.         0.         0.       ...   2.947406 189.6876   171.4222  ]\n",
+      "  [  0.         0.         0.       ...   3.538999 190.0329   169.4787  ]\n",
+      "  ...\n",
+      "  [  0.         0.         0.       ... 339.8397   195.9552   144.3933  ]\n",
+      "  [  0.         0.         0.       ... 339.8964   192.4409   148.1278  ]\n",
+      "  [  0.         0.         0.       ... 340.1847   190.5611   150.9379  ]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.        0.        0.      ... 328.807   209.356    64.13982]\n",
+      "  [  0.        0.        0.      ... 329.1744  219.1686   82.03358]\n",
+      "  [  0.        0.        0.      ... 328.9293  224.907    95.42315]\n",
+      "  ...\n",
+      "  [  0.        0.        0.      ... 311.8901  182.3479  207.4501 ]\n",
+      "  [  0.        0.        0.      ... 296.0581   43.59404 291.2405 ]\n",
+      "  [  0.        0.        0.      ... 296.0581   43.59404 291.2405 ]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.       0.       0.     ... 340.4522 188.5802 153.4675]\n",
+      "  [  0.       0.       0.     ... 342.0439 186.2218 158.3235]\n",
+      "  [  0.       0.       0.     ... 343.4704 184.4892 161.9352]\n",
+      "  ...\n",
+      "  [  0.       0.       0.     ... 336.0501 100.8427 308.4322]\n",
+      "  [  0.       0.       0.     ... 336.5646 102.0053 307.9174]\n",
+      "  [  0.       0.       0.     ... 336.9454 102.9008 307.495 ]]], shape=(1, 300, 2100), dtype=float64)\n",
+      "tf.Tensor([7], shape=(1,), dtype=int32)\n",
+      "tf.Tensor(\n",
+      "[[[  0.        0.        0.      ... 296.0581   43.59404 291.2405 ]\n",
+      "  [  0.        0.        0.      ... 318.9684  302.7743  264.226  ]\n",
+      "  [  0.        0.        0.      ... 318.9684  302.7743  264.226  ]\n",
+      "  ...\n",
+      "  [  0.        0.        0.      ... 321.3094   67.3396  295.069  ]\n",
+      "  [  0.        0.        0.      ... 321.406    66.64935 293.5298 ]\n",
+      "  [  0.        0.        0.      ... 321.696    65.39925 291.8149 ]]], shape=(1, 300, 2100), dtype=float64)\n",
       "tf.Tensor([7], shape=(1,), dtype=int32)\n"
      ]
     }
@@ -1605,7 +1691,7 @@
   {
    "cell_type": "code",
    "execution_count": 126,
-   "id": "4e755031",
+   "id": "bcec87a9",
    "metadata": {},
    "outputs": [
     {
@@ -1640,7 +1726,7 @@
   {
    "cell_type": "code",
    "execution_count": 98,
-   "id": "d4207627",
+   "id": "fb10decc",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1652,7 +1738,7 @@
   {
    "cell_type": "code",
    "execution_count": 110,
-   "id": "e068b158",
+   "id": "08ae9f52",
    "metadata": {},
    "outputs": [
     {
@@ -1690,7 +1776,7 @@
   {
    "cell_type": "code",
    "execution_count": 111,
-   "id": "84260e81",
+   "id": "57fee43e",
    "metadata": {},
    "outputs": [
     {
@@ -1730,7 +1816,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "c4cbcf14",
+   "id": "69bd85a5",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1748,7 +1834,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3f5d854e",
+   "id": "522518bc",
    "metadata": {},
    "outputs": [],
    "source": [