diff --git a/L3_DataPreparation.ipynb b/L3_DataPreparation.ipynb
index 221e8a8..fb7d9a0 100644
--- a/L3_DataPreparation.ipynb
+++ b/L3_DataPreparation.ipynb
@@ -108,219 +108,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": null,
+   "id": "7b71f450",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path \n",
+    "from os import path as p\n",
+    "\n",
+    "BASE_FOLDER = Path(p.abspath(p.curdir))\n",
+    "DATA_FOLDER = BASE_FOLDER / \"dataset\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "id": "c0a85288-4f43-4732-98b1-1b9e3bc6eae5",
    "metadata": {},
    "outputs": [],
    "source": [
     "# Load data\n",
     "import pandas as pd\n",
-    "raw_data = pd.read_csv(\"https://raw.githubusercontent.com/OpenMined/PySyft/dev/notebooks/course3/dataset/L3_data.csv\")"
+    "\n",
+    "if DATA_FOLDER.exists():\n",
+    "    datafile_ref = DATA_FOLDER / \"L3_raw_data.csv\"\n",
+    "else:\n",
+    "    datafile_ref = \"https://raw.githubusercontent.com/OpenMined/PySyft/dev/notebooks/course3/dataset/L3_data.csv\"\n",
+    "\n",
+    "raw_data = pd.read_csv(datafile_ref)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": null,
    "id": "03a5c8e2-642c-4686-921c-51b9ca9ab89b",
    "metadata": {},
-   "outputs": [
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-      ]
-     },
-     "execution_count": 76,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "raw_data.head()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "09a5662b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "raw_data.shape"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8ee93c43-ee4f-4848-ba08-4a31b7366805",
@@ -328,26 +165,15 @@
    "source": [
     "In this dataset, each column corresponds to a <b> country</b>, each row corresponds to a new <b> month </b> where data was collected, and each value in this DataFrame corresponds to the number of COVID19 cases in the country at the start of that month. \n",
     "\n",
-    "So for instance, Country 0 had 1140 COVID cases at the start of when this data was collected (row 0), and only 451 when the data was last collected (row 53)."
+    "So for instance, Country 0 had `2280` COVID cases at the start of when this data was collected (`row 0`), and only `451` when the data was last collected (`row 53`)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": null,
    "id": "58d63f95-0b88-428d-94a9-58bb588aea0d",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(1140, 451)"
-      ]
-     },
-     "execution_count": 79,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "raw_data[\"0\"][0], raw_data[\"0\"][53]"
    ]
@@ -374,203 +200,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "0001c907-e0c5-4a3c-b4ab-c7562e06c638",
    "metadata": {},
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-       "<p>5 rows × 175 columns</p>\n",
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-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "raw_data.head()"
    ]
@@ -587,7 +220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "31f5b683-61cc-4390-b8bb-ed6e0dfae50b",
    "metadata": {},
    "outputs": [],
@@ -606,203 +239,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "5abf254c-7063-4d37-8b44-88964fa05d33",
    "metadata": {},
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-       "      <td>...</td>\n",
-       "      <td>515</td>\n",
-       "      <td>207</td>\n",
-       "      <td>722</td>\n",
-       "      <td>401</td>\n",
-       "      <td>234</td>\n",
-       "      <td>521</td>\n",
-       "      <td>284</td>\n",
-       "      <td>465</td>\n",
-       "      <td>522</td>\n",
-       "      <td>1176</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1140</td>\n",
-       "      <td>1113</td>\n",
-       "      <td>3099</td>\n",
-       "      <td>92</td>\n",
-       "      <td>621</td>\n",
-       "      <td>344</td>\n",
-       "      <td>283</td>\n",
-       "      <td>284</td>\n",
-       "      <td>1095</td>\n",
-       "      <td>44</td>\n",
-       "      <td>...</td>\n",
-       "      <td>515</td>\n",
-       "      <td>207</td>\n",
-       "      <td>722</td>\n",
-       "      <td>401</td>\n",
-       "      <td>234</td>\n",
-       "      <td>521</td>\n",
-       "      <td>284</td>\n",
-       "      <td>465</td>\n",
-       "      <td>522</td>\n",
-       "      <td>1176</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1211</td>\n",
-       "      <td>1378</td>\n",
-       "      <td>2821</td>\n",
-       "      <td>113</td>\n",
-       "      <td>575</td>\n",
-       "      <td>319</td>\n",
-       "      <td>267</td>\n",
-       "      <td>295</td>\n",
-       "      <td>1167</td>\n",
-       "      <td>52</td>\n",
-       "      <td>...</td>\n",
-       "      <td>577</td>\n",
-       "      <td>231</td>\n",
-       "      <td>655</td>\n",
-       "      <td>449</td>\n",
-       "      <td>224</td>\n",
-       "      <td>600</td>\n",
-       "      <td>224</td>\n",
-       "      <td>577</td>\n",
-       "      <td>492</td>\n",
-       "      <td>1258</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1238</td>\n",
-       "      <td>1587</td>\n",
-       "      <td>2356</td>\n",
-       "      <td>107</td>\n",
-       "      <td>520</td>\n",
-       "      <td>265</td>\n",
-       "      <td>296</td>\n",
-       "      <td>316</td>\n",
-       "      <td>1186</td>\n",
-       "      <td>42</td>\n",
-       "      <td>...</td>\n",
-       "      <td>473</td>\n",
-       "      <td>209</td>\n",
-       "      <td>620</td>\n",
-       "      <td>473</td>\n",
-       "      <td>231</td>\n",
-       "      <td>607</td>\n",
-       "      <td>275</td>\n",
-       "      <td>407</td>\n",
-       "      <td>421</td>\n",
-       "      <td>1109</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1093</td>\n",
-       "      <td>2075</td>\n",
-       "      <td>2964</td>\n",
-       "      <td>117</td>\n",
-       "      <td>578</td>\n",
-       "      <td>371</td>\n",
-       "      <td>359</td>\n",
-       "      <td>349</td>\n",
-       "      <td>1151</td>\n",
-       "      <td>48</td>\n",
-       "      <td>...</td>\n",
-       "      <td>550</td>\n",
-       "      <td>227</td>\n",
-       "      <td>648</td>\n",
-       "      <td>447</td>\n",
-       "      <td>232</td>\n",
-       "      <td>563</td>\n",
-       "      <td>188</td>\n",
-       "      <td>338</td>\n",
-       "      <td>432</td>\n",
-       "      <td>1148</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 175 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      0     1     2    3    4    5    6    7     8   9  ...  165  166  167  \\\n",
-       "0  1140  1113  3099   92  621  344  283  284  1095  44  ...  515  207  722   \n",
-       "1  1140  1113  3099   92  621  344  283  284  1095  44  ...  515  207  722   \n",
-       "2  1211  1378  2821  113  575  319  267  295  1167  52  ...  577  231  655   \n",
-       "3  1238  1587  2356  107  520  265  296  316  1186  42  ...  473  209  620   \n",
-       "4  1093  2075  2964  117  578  371  359  349  1151  48  ...  550  227  648   \n",
-       "\n",
-       "   168  169  170  171  172  173   174  \n",
-       "0  401  234  521  284  465  522  1176  \n",
-       "1  401  234  521  284  465  522  1176  \n",
-       "2  449  224  600  224  577  492  1258  \n",
-       "3  473  231  607  275  407  421  1109  \n",
-       "4  447  232  563  188  338  432  1148  \n",
-       "\n",
-       "[5 rows x 175 columns]"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# See the resultant data\n",
     "raw_data.head()"
@@ -820,1529 +260,57 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "d33b2214-8fe5-4787-8d56-5c5aa29acf54",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-       "\n",
-       "    .dataframe tbody tr th {\n",
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-       "      <td>113</td>\n",
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-       "      <td>319</td>\n",
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-       "      <td>295</td>\n",
-       "      <td>1167</td>\n",
-       "      <td>52</td>\n",
-       "      <td>...</td>\n",
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-       "      <td>224</td>\n",
-       "      <td>600</td>\n",
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-       "      <td>577</td>\n",
-       "      <td>492</td>\n",
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-       "      <th>3</th>\n",
-       "      <td>1238</td>\n",
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-       "      <td>42</td>\n",
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-       "      <td>209</td>\n",
-       "      <td>620</td>\n",
-       "      <td>473</td>\n",
-       "      <td>231</td>\n",
-       "      <td>607</td>\n",
-       "      <td>275</td>\n",
-       "      <td>407</td>\n",
-       "      <td>421</td>\n",
-       "      <td>1109</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1093</td>\n",
-       "      <td>2075</td>\n",
-       "      <td>2964</td>\n",
-       "      <td>117</td>\n",
-       "      <td>578</td>\n",
-       "      <td>371</td>\n",
-       "      <td>359</td>\n",
-       "      <td>349</td>\n",
-       "      <td>1151</td>\n",
-       "      <td>48</td>\n",
-       "      <td>...</td>\n",
-       "      <td>550</td>\n",
-       "      <td>227</td>\n",
-       "      <td>648</td>\n",
-       "      <td>447</td>\n",
-       "      <td>232</td>\n",
-       "      <td>563</td>\n",
-       "      <td>188</td>\n",
-       "      <td>338</td>\n",
-       "      <td>432</td>\n",
-       "      <td>1148</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>966</td>\n",
-       "      <td>2269</td>\n",
-       "      <td>3390</td>\n",
-       "      <td>135</td>\n",
-       "      <td>614</td>\n",
-       "      <td>432</td>\n",
-       "      <td>341</td>\n",
-       "      <td>428</td>\n",
-       "      <td>1107</td>\n",
-       "      <td>49</td>\n",
-       "      <td>...</td>\n",
-       "      <td>285</td>\n",
-       "      <td>189</td>\n",
-       "      <td>640</td>\n",
-       "      <td>398</td>\n",
-       "      <td>250</td>\n",
-       "      <td>535</td>\n",
-       "      <td>183</td>\n",
-       "      <td>382</td>\n",
-       "      <td>459</td>\n",
-       "      <td>1181</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>758</td>\n",
-       "      <td>2430</td>\n",
-       "      <td>3575</td>\n",
-       "      <td>178</td>\n",
-       "      <td>802</td>\n",
-       "      <td>511</td>\n",
-       "      <td>330</td>\n",
-       "      <td>552</td>\n",
-       "      <td>1046</td>\n",
-       "      <td>43</td>\n",
-       "      <td>...</td>\n",
-       "      <td>248</td>\n",
-       "      <td>167</td>\n",
-       "      <td>608</td>\n",
-       "      <td>471</td>\n",
-       "      <td>266</td>\n",
-       "      <td>570</td>\n",
-       "      <td>130</td>\n",
-       "      <td>360</td>\n",
-       "      <td>495</td>\n",
-       "      <td>1173</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>858</td>\n",
-       "      <td>2709</td>\n",
-       "      <td>4260</td>\n",
-       "      <td>180</td>\n",
-       "      <td>696</td>\n",
-       "      <td>455</td>\n",
-       "      <td>347</td>\n",
-       "      <td>488</td>\n",
-       "      <td>1014</td>\n",
-       "      <td>42</td>\n",
-       "      <td>...</td>\n",
-       "      <td>260</td>\n",
-       "      <td>194</td>\n",
-       "      <td>529</td>\n",
-       "      <td>464</td>\n",
-       "      <td>258</td>\n",
-       "      <td>458</td>\n",
-       "      <td>100</td>\n",
-       "      <td>288</td>\n",
-       "      <td>424</td>\n",
-       "      <td>1197</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>877</td>\n",
-       "      <td>2556</td>\n",
-       "      <td>4860</td>\n",
-       "      <td>178</td>\n",
-       "      <td>747</td>\n",
-       "      <td>309</td>\n",
-       "      <td>458</td>\n",
-       "      <td>457</td>\n",
-       "      <td>1000</td>\n",
-       "      <td>46</td>\n",
-       "      <td>...</td>\n",
-       "      <td>247</td>\n",
-       "      <td>190</td>\n",
-       "      <td>412</td>\n",
-       "      <td>436</td>\n",
-       "      <td>250</td>\n",
-       "      <td>411</td>\n",
-       "      <td>107</td>\n",
-       "      <td>450</td>\n",
-       "      <td>440</td>\n",
-       "      <td>1193</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>925</td>\n",
-       "      <td>2765</td>\n",
-       "      <td>4145</td>\n",
-       "      <td>251</td>\n",
-       "      <td>770</td>\n",
-       "      <td>283</td>\n",
-       "      <td>462</td>\n",
-       "      <td>495</td>\n",
-       "      <td>1131</td>\n",
-       "      <td>46</td>\n",
-       "      <td>...</td>\n",
-       "      <td>349</td>\n",
-       "      <td>177</td>\n",
-       "      <td>371</td>\n",
-       "      <td>434</td>\n",
-       "      <td>205</td>\n",
-       "      <td>419</td>\n",
-       "      <td>114</td>\n",
-       "      <td>509</td>\n",
-       "      <td>458</td>\n",
-       "      <td>1224</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>629</td>\n",
-       "      <td>3071</td>\n",
-       "      <td>5022</td>\n",
-       "      <td>259</td>\n",
-       "      <td>775</td>\n",
-       "      <td>287</td>\n",
-       "      <td>507</td>\n",
-       "      <td>438</td>\n",
-       "      <td>1207</td>\n",
-       "      <td>62</td>\n",
-       "      <td>...</td>\n",
-       "      <td>228</td>\n",
-       "      <td>197</td>\n",
-       "      <td>418</td>\n",
-       "      <td>512</td>\n",
-       "      <td>206</td>\n",
-       "      <td>348</td>\n",
-       "      <td>75</td>\n",
-       "      <td>490</td>\n",
-       "      <td>486</td>\n",
-       "      <td>1337</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>806</td>\n",
-       "      <td>3147</td>\n",
-       "      <td>5101</td>\n",
-       "      <td>295</td>\n",
-       "      <td>845</td>\n",
-       "      <td>266</td>\n",
-       "      <td>585</td>\n",
-       "      <td>433</td>\n",
-       "      <td>1259</td>\n",
-       "      <td>60</td>\n",
-       "      <td>...</td>\n",
-       "      <td>378</td>\n",
-       "      <td>221</td>\n",
-       "      <td>436</td>\n",
-       "      <td>499</td>\n",
-       "      <td>213</td>\n",
-       "      <td>337</td>\n",
-       "      <td>24</td>\n",
-       "      <td>566</td>\n",
-       "      <td>448</td>\n",
-       "      <td>1057</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>895</td>\n",
-       "      <td>3740</td>\n",
-       "      <td>5833</td>\n",
-       "      <td>294</td>\n",
-       "      <td>843</td>\n",
-       "      <td>308</td>\n",
-       "      <td>606</td>\n",
-       "      <td>451</td>\n",
-       "      <td>1567</td>\n",
-       "      <td>64</td>\n",
-       "      <td>...</td>\n",
-       "      <td>397</td>\n",
-       "      <td>211</td>\n",
-       "      <td>428</td>\n",
-       "      <td>506</td>\n",
-       "      <td>211</td>\n",
-       "      <td>321</td>\n",
-       "      <td>18</td>\n",
-       "      <td>609</td>\n",
-       "      <td>336</td>\n",
-       "      <td>1173</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>818</td>\n",
-       "      <td>3559</td>\n",
-       "      <td>7090</td>\n",
-       "      <td>342</td>\n",
-       "      <td>680</td>\n",
-       "      <td>278</td>\n",
-       "      <td>662</td>\n",
-       "      <td>468</td>\n",
-       "      <td>1612</td>\n",
-       "      <td>63</td>\n",
-       "      <td>...</td>\n",
-       "      <td>406</td>\n",
-       "      <td>217</td>\n",
-       "      <td>459</td>\n",
-       "      <td>553</td>\n",
-       "      <td>196</td>\n",
-       "      <td>349</td>\n",
-       "      <td>20</td>\n",
-       "      <td>690</td>\n",
-       "      <td>360</td>\n",
-       "      <td>956</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>735</td>\n",
-       "      <td>4470</td>\n",
-       "      <td>6549</td>\n",
-       "      <td>337</td>\n",
-       "      <td>622</td>\n",
-       "      <td>370</td>\n",
-       "      <td>702</td>\n",
-       "      <td>583</td>\n",
-       "      <td>1702</td>\n",
-       "      <td>70</td>\n",
-       "      <td>...</td>\n",
-       "      <td>294</td>\n",
-       "      <td>220</td>\n",
-       "      <td>400</td>\n",
-       "      <td>544</td>\n",
-       "      <td>214</td>\n",
-       "      <td>340</td>\n",
-       "      <td>21</td>\n",
-       "      <td>792</td>\n",
-       "      <td>354</td>\n",
-       "      <td>703</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>661</td>\n",
-       "      <td>3814</td>\n",
-       "      <td>5180</td>\n",
-       "      <td>361</td>\n",
-       "      <td>707</td>\n",
-       "      <td>364</td>\n",
-       "      <td>775</td>\n",
-       "      <td>720</td>\n",
-       "      <td>1620</td>\n",
-       "      <td>71</td>\n",
-       "      <td>...</td>\n",
-       "      <td>265</td>\n",
-       "      <td>158</td>\n",
-       "      <td>402</td>\n",
-       "      <td>503</td>\n",
-       "      <td>160</td>\n",
-       "      <td>380</td>\n",
-       "      <td>14</td>\n",
-       "      <td>603</td>\n",
-       "      <td>364</td>\n",
-       "      <td>965</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>629</td>\n",
-       "      <td>3665</td>\n",
-       "      <td>4548</td>\n",
-       "      <td>324</td>\n",
-       "      <td>790</td>\n",
-       "      <td>425</td>\n",
-       "      <td>694</td>\n",
-       "      <td>725</td>\n",
-       "      <td>1403</td>\n",
-       "      <td>56</td>\n",
-       "      <td>...</td>\n",
-       "      <td>332</td>\n",
-       "      <td>136</td>\n",
-       "      <td>330</td>\n",
-       "      <td>730</td>\n",
-       "      <td>198</td>\n",
-       "      <td>383</td>\n",
-       "      <td>14</td>\n",
-       "      <td>634</td>\n",
-       "      <td>361</td>\n",
-       "      <td>1264</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>632</td>\n",
-       "      <td>4217</td>\n",
-       "      <td>4414</td>\n",
-       "      <td>386</td>\n",
-       "      <td>760</td>\n",
-       "      <td>365</td>\n",
-       "      <td>709</td>\n",
-       "      <td>741</td>\n",
-       "      <td>1432</td>\n",
-       "      <td>41</td>\n",
-       "      <td>...</td>\n",
-       "      <td>312</td>\n",
-       "      <td>149</td>\n",
-       "      <td>341</td>\n",
-       "      <td>909</td>\n",
-       "      <td>122</td>\n",
-       "      <td>452</td>\n",
-       "      <td>15</td>\n",
-       "      <td>318</td>\n",
-       "      <td>369</td>\n",
-       "      <td>917</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>622</td>\n",
-       "      <td>6409</td>\n",
-       "      <td>5078</td>\n",
-       "      <td>420</td>\n",
-       "      <td>799</td>\n",
-       "      <td>351</td>\n",
-       "      <td>743</td>\n",
-       "      <td>847</td>\n",
-       "      <td>1567</td>\n",
-       "      <td>36</td>\n",
-       "      <td>...</td>\n",
-       "      <td>333</td>\n",
-       "      <td>136</td>\n",
-       "      <td>350</td>\n",
-       "      <td>1014</td>\n",
-       "      <td>161</td>\n",
-       "      <td>389</td>\n",
-       "      <td>18</td>\n",
-       "      <td>219</td>\n",
-       "      <td>397</td>\n",
-       "      <td>896</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>589</td>\n",
-       "      <td>6073</td>\n",
-       "      <td>6003</td>\n",
-       "      <td>509</td>\n",
-       "      <td>1021</td>\n",
-       "      <td>381</td>\n",
-       "      <td>777</td>\n",
-       "      <td>756</td>\n",
-       "      <td>2056</td>\n",
-       "      <td>23</td>\n",
-       "      <td>...</td>\n",
-       "      <td>586</td>\n",
-       "      <td>143</td>\n",
-       "      <td>360</td>\n",
-       "      <td>1062</td>\n",
-       "      <td>159</td>\n",
-       "      <td>452</td>\n",
-       "      <td>23</td>\n",
-       "      <td>268</td>\n",
-       "      <td>323</td>\n",
-       "      <td>764</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>604</td>\n",
-       "      <td>5948</td>\n",
-       "      <td>3024</td>\n",
-       "      <td>461</td>\n",
-       "      <td>1018</td>\n",
-       "      <td>311</td>\n",
-       "      <td>866</td>\n",
-       "      <td>724</td>\n",
-       "      <td>1860</td>\n",
-       "      <td>18</td>\n",
-       "      <td>...</td>\n",
-       "      <td>525</td>\n",
-       "      <td>147</td>\n",
-       "      <td>402</td>\n",
-       "      <td>1006</td>\n",
-       "      <td>153</td>\n",
-       "      <td>433</td>\n",
-       "      <td>21</td>\n",
-       "      <td>271</td>\n",
-       "      <td>360</td>\n",
-       "      <td>759</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>21</th>\n",
-       "      <td>527</td>\n",
-       "      <td>5790</td>\n",
-       "      <td>3037</td>\n",
-       "      <td>427</td>\n",
-       "      <td>1017</td>\n",
-       "      <td>253</td>\n",
-       "      <td>905</td>\n",
-       "      <td>878</td>\n",
-       "      <td>1689</td>\n",
-       "      <td>19</td>\n",
-       "      <td>...</td>\n",
-       "      <td>541</td>\n",
-       "      <td>165</td>\n",
-       "      <td>434</td>\n",
-       "      <td>1182</td>\n",
-       "      <td>137</td>\n",
-       "      <td>497</td>\n",
-       "      <td>17</td>\n",
-       "      <td>299</td>\n",
-       "      <td>353</td>\n",
-       "      <td>880</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>22</th>\n",
-       "      <td>498</td>\n",
-       "      <td>5565</td>\n",
-       "      <td>2936</td>\n",
-       "      <td>478</td>\n",
-       "      <td>1036</td>\n",
-       "      <td>341</td>\n",
-       "      <td>801</td>\n",
-       "      <td>791</td>\n",
-       "      <td>1897</td>\n",
-       "      <td>19</td>\n",
-       "      <td>...</td>\n",
-       "      <td>586</td>\n",
-       "      <td>143</td>\n",
-       "      <td>381</td>\n",
-       "      <td>1112</td>\n",
-       "      <td>74</td>\n",
-       "      <td>556</td>\n",
-       "      <td>15</td>\n",
-       "      <td>349</td>\n",
-       "      <td>411</td>\n",
-       "      <td>1140</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>483</td>\n",
-       "      <td>6992</td>\n",
-       "      <td>2568</td>\n",
-       "      <td>475</td>\n",
-       "      <td>1099</td>\n",
-       "      <td>372</td>\n",
-       "      <td>848</td>\n",
-       "      <td>689</td>\n",
-       "      <td>1864</td>\n",
-       "      <td>21</td>\n",
-       "      <td>...</td>\n",
-       "      <td>491</td>\n",
-       "      <td>148</td>\n",
-       "      <td>426</td>\n",
-       "      <td>1214</td>\n",
-       "      <td>67</td>\n",
-       "      <td>397</td>\n",
-       "      <td>17</td>\n",
-       "      <td>451</td>\n",
-       "      <td>392</td>\n",
-       "      <td>1203</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>478</td>\n",
-       "      <td>7560</td>\n",
-       "      <td>2056</td>\n",
-       "      <td>449</td>\n",
-       "      <td>1061</td>\n",
-       "      <td>255</td>\n",
-       "      <td>773</td>\n",
-       "      <td>571</td>\n",
-       "      <td>2339</td>\n",
-       "      <td>24</td>\n",
-       "      <td>...</td>\n",
-       "      <td>405</td>\n",
-       "      <td>147</td>\n",
-       "      <td>417</td>\n",
-       "      <td>1434</td>\n",
-       "      <td>53</td>\n",
-       "      <td>417</td>\n",
-       "      <td>23</td>\n",
-       "      <td>537</td>\n",
-       "      <td>365</td>\n",
-       "      <td>1131</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>519</td>\n",
-       "      <td>9143</td>\n",
-       "      <td>1917</td>\n",
-       "      <td>459</td>\n",
-       "      <td>1125</td>\n",
-       "      <td>244</td>\n",
-       "      <td>719</td>\n",
-       "      <td>734</td>\n",
-       "      <td>2737</td>\n",
-       "      <td>25</td>\n",
-       "      <td>...</td>\n",
-       "      <td>398</td>\n",
-       "      <td>136</td>\n",
-       "      <td>335</td>\n",
-       "      <td>1468</td>\n",
-       "      <td>56</td>\n",
-       "      <td>458</td>\n",
-       "      <td>23</td>\n",
-       "      <td>533</td>\n",
-       "      <td>360</td>\n",
-       "      <td>1178</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>26</th>\n",
-       "      <td>471</td>\n",
-       "      <td>8515</td>\n",
-       "      <td>2455</td>\n",
-       "      <td>472</td>\n",
-       "      <td>906</td>\n",
-       "      <td>237</td>\n",
-       "      <td>689</td>\n",
-       "      <td>713</td>\n",
-       "      <td>3123</td>\n",
-       "      <td>26</td>\n",
-       "      <td>...</td>\n",
-       "      <td>380</td>\n",
-       "      <td>125</td>\n",
-       "      <td>331</td>\n",
-       "      <td>1604</td>\n",
-       "      <td>52</td>\n",
-       "      <td>519</td>\n",
-       "      <td>21</td>\n",
-       "      <td>497</td>\n",
-       "      <td>378</td>\n",
-       "      <td>1085</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>472</td>\n",
-       "      <td>8535</td>\n",
-       "      <td>2273</td>\n",
-       "      <td>533</td>\n",
-       "      <td>937</td>\n",
-       "      <td>263</td>\n",
-       "      <td>681</td>\n",
-       "      <td>730</td>\n",
-       "      <td>3452</td>\n",
-       "      <td>28</td>\n",
-       "      <td>...</td>\n",
-       "      <td>414</td>\n",
-       "      <td>128</td>\n",
-       "      <td>353</td>\n",
-       "      <td>1745</td>\n",
-       "      <td>58</td>\n",
-       "      <td>458</td>\n",
-       "      <td>20</td>\n",
-       "      <td>412</td>\n",
-       "      <td>367</td>\n",
-       "      <td>1336</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>482</td>\n",
-       "      <td>9314</td>\n",
-       "      <td>2290</td>\n",
-       "      <td>657</td>\n",
-       "      <td>941</td>\n",
-       "      <td>234</td>\n",
-       "      <td>576</td>\n",
-       "      <td>715</td>\n",
-       "      <td>2865</td>\n",
-       "      <td>28</td>\n",
-       "      <td>...</td>\n",
-       "      <td>307</td>\n",
-       "      <td>136</td>\n",
-       "      <td>317</td>\n",
-       "      <td>1579</td>\n",
-       "      <td>50</td>\n",
-       "      <td>485</td>\n",
-       "      <td>19</td>\n",
-       "      <td>396</td>\n",
-       "      <td>388</td>\n",
-       "      <td>1590</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>367</td>\n",
-       "      <td>11850</td>\n",
-       "      <td>2488</td>\n",
-       "      <td>603</td>\n",
-       "      <td>921</td>\n",
-       "      <td>199</td>\n",
-       "      <td>641</td>\n",
-       "      <td>626</td>\n",
-       "      <td>2814</td>\n",
-       "      <td>26</td>\n",
-       "      <td>...</td>\n",
-       "      <td>416</td>\n",
-       "      <td>136</td>\n",
-       "      <td>359</td>\n",
-       "      <td>1643</td>\n",
-       "      <td>61</td>\n",
-       "      <td>494</td>\n",
-       "      <td>17</td>\n",
-       "      <td>374</td>\n",
-       "      <td>373</td>\n",
-       "      <td>1628</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>30</th>\n",
-       "      <td>376</td>\n",
-       "      <td>13020</td>\n",
-       "      <td>2349</td>\n",
-       "      <td>552</td>\n",
-       "      <td>877</td>\n",
-       "      <td>151</td>\n",
-       "      <td>567</td>\n",
-       "      <td>617</td>\n",
-       "      <td>3018</td>\n",
-       "      <td>23</td>\n",
-       "      <td>...</td>\n",
-       "      <td>240</td>\n",
-       "      <td>138</td>\n",
-       "      <td>326</td>\n",
-       "      <td>1368</td>\n",
-       "      <td>62</td>\n",
-       "      <td>516</td>\n",
-       "      <td>17</td>\n",
-       "      <td>383</td>\n",
-       "      <td>375</td>\n",
-       "      <td>1508</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>31</th>\n",
-       "      <td>336</td>\n",
-       "      <td>14235</td>\n",
-       "      <td>3180</td>\n",
-       "      <td>552</td>\n",
-       "      <td>824</td>\n",
-       "      <td>146</td>\n",
-       "      <td>656</td>\n",
-       "      <td>580</td>\n",
-       "      <td>2930</td>\n",
-       "      <td>22</td>\n",
-       "      <td>...</td>\n",
-       "      <td>249</td>\n",
-       "      <td>131</td>\n",
-       "      <td>310</td>\n",
-       "      <td>1370</td>\n",
-       "      <td>49</td>\n",
-       "      <td>567</td>\n",
-       "      <td>10</td>\n",
-       "      <td>409</td>\n",
-       "      <td>459</td>\n",
-       "      <td>1376</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>32</th>\n",
-       "      <td>267</td>\n",
-       "      <td>13853</td>\n",
-       "      <td>4212</td>\n",
-       "      <td>601</td>\n",
-       "      <td>757</td>\n",
-       "      <td>158</td>\n",
-       "      <td>582</td>\n",
-       "      <td>539</td>\n",
-       "      <td>2666</td>\n",
-       "      <td>20</td>\n",
-       "      <td>...</td>\n",
-       "      <td>256</td>\n",
-       "      <td>125</td>\n",
-       "      <td>290</td>\n",
-       "      <td>1216</td>\n",
-       "      <td>47</td>\n",
-       "      <td>633</td>\n",
-       "      <td>9</td>\n",
-       "      <td>565</td>\n",
-       "      <td>475</td>\n",
-       "      <td>913</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>33</th>\n",
-       "      <td>328</td>\n",
-       "      <td>13833</td>\n",
-       "      <td>3753</td>\n",
-       "      <td>652</td>\n",
-       "      <td>581</td>\n",
-       "      <td>114</td>\n",
-       "      <td>656</td>\n",
-       "      <td>507</td>\n",
-       "      <td>2357</td>\n",
-       "      <td>18</td>\n",
-       "      <td>...</td>\n",
-       "      <td>208</td>\n",
-       "      <td>115</td>\n",
-       "      <td>240</td>\n",
-       "      <td>1193</td>\n",
-       "      <td>41</td>\n",
-       "      <td>592</td>\n",
-       "      <td>9</td>\n",
-       "      <td>621</td>\n",
-       "      <td>496</td>\n",
-       "      <td>1049</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>34</th>\n",
-       "      <td>416</td>\n",
-       "      <td>12753</td>\n",
-       "      <td>3749</td>\n",
-       "      <td>635</td>\n",
-       "      <td>566</td>\n",
-       "      <td>141</td>\n",
-       "      <td>655</td>\n",
-       "      <td>537</td>\n",
-       "      <td>3021</td>\n",
-       "      <td>21</td>\n",
-       "      <td>...</td>\n",
-       "      <td>172</td>\n",
-       "      <td>109</td>\n",
-       "      <td>216</td>\n",
-       "      <td>1324</td>\n",
-       "      <td>35</td>\n",
-       "      <td>607</td>\n",
-       "      <td>6</td>\n",
-       "      <td>658</td>\n",
-       "      <td>423</td>\n",
-       "      <td>1028</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>35</th>\n",
-       "      <td>456</td>\n",
-       "      <td>13324</td>\n",
-       "      <td>3433</td>\n",
-       "      <td>583</td>\n",
-       "      <td>628</td>\n",
-       "      <td>138</td>\n",
-       "      <td>542</td>\n",
-       "      <td>611</td>\n",
-       "      <td>3230</td>\n",
-       "      <td>23</td>\n",
-       "      <td>...</td>\n",
-       "      <td>195</td>\n",
-       "      <td>116</td>\n",
-       "      <td>201</td>\n",
-       "      <td>1810</td>\n",
-       "      <td>35</td>\n",
-       "      <td>610</td>\n",
-       "      <td>4</td>\n",
-       "      <td>613</td>\n",
-       "      <td>480</td>\n",
-       "      <td>953</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>36</th>\n",
-       "      <td>434</td>\n",
-       "      <td>16070</td>\n",
-       "      <td>3117</td>\n",
-       "      <td>537</td>\n",
-       "      <td>607</td>\n",
-       "      <td>122</td>\n",
-       "      <td>485</td>\n",
-       "      <td>653</td>\n",
-       "      <td>3934</td>\n",
-       "      <td>17</td>\n",
-       "      <td>...</td>\n",
-       "      <td>236</td>\n",
-       "      <td>124</td>\n",
-       "      <td>198</td>\n",
-       "      <td>1728</td>\n",
-       "      <td>38</td>\n",
-       "      <td>595</td>\n",
-       "      <td>4</td>\n",
-       "      <td>409</td>\n",
-       "      <td>531</td>\n",
-       "      <td>942</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>37</th>\n",
-       "      <td>363</td>\n",
-       "      <td>15712</td>\n",
-       "      <td>2100</td>\n",
-       "      <td>515</td>\n",
-       "      <td>645</td>\n",
-       "      <td>94</td>\n",
-       "      <td>550</td>\n",
-       "      <td>600</td>\n",
-       "      <td>4286</td>\n",
-       "      <td>16</td>\n",
-       "      <td>...</td>\n",
-       "      <td>214</td>\n",
-       "      <td>108</td>\n",
-       "      <td>139</td>\n",
-       "      <td>1739</td>\n",
-       "      <td>46</td>\n",
-       "      <td>587</td>\n",
-       "      <td>5</td>\n",
-       "      <td>372</td>\n",
-       "      <td>493</td>\n",
-       "      <td>1084</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>38</th>\n",
-       "      <td>379</td>\n",
-       "      <td>15150</td>\n",
-       "      <td>2193</td>\n",
-       "      <td>513</td>\n",
-       "      <td>575</td>\n",
-       "      <td>80</td>\n",
-       "      <td>575</td>\n",
-       "      <td>711</td>\n",
-       "      <td>5007</td>\n",
-       "      <td>11</td>\n",
-       "      <td>...</td>\n",
-       "      <td>208</td>\n",
-       "      <td>98</td>\n",
-       "      <td>149</td>\n",
-       "      <td>1743</td>\n",
-       "      <td>47</td>\n",
-       "      <td>598</td>\n",
-       "      <td>6</td>\n",
-       "      <td>416</td>\n",
-       "      <td>545</td>\n",
-       "      <td>872</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>39</th>\n",
-       "      <td>375</td>\n",
-       "      <td>15444</td>\n",
-       "      <td>2196</td>\n",
-       "      <td>638</td>\n",
-       "      <td>500</td>\n",
-       "      <td>101</td>\n",
-       "      <td>570</td>\n",
-       "      <td>734</td>\n",
-       "      <td>4987</td>\n",
-       "      <td>11</td>\n",
-       "      <td>...</td>\n",
-       "      <td>196</td>\n",
-       "      <td>91</td>\n",
-       "      <td>159</td>\n",
-       "      <td>2161</td>\n",
-       "      <td>62</td>\n",
-       "      <td>562</td>\n",
-       "      <td>3</td>\n",
-       "      <td>360</td>\n",
-       "      <td>563</td>\n",
-       "      <td>1029</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>40</th>\n",
-       "      <td>322</td>\n",
-       "      <td>14844</td>\n",
-       "      <td>1556</td>\n",
-       "      <td>749</td>\n",
-       "      <td>463</td>\n",
-       "      <td>107</td>\n",
-       "      <td>444</td>\n",
-       "      <td>832</td>\n",
-       "      <td>5342</td>\n",
-       "      <td>11</td>\n",
-       "      <td>...</td>\n",
-       "      <td>146</td>\n",
-       "      <td>91</td>\n",
-       "      <td>178</td>\n",
-       "      <td>2151</td>\n",
-       "      <td>80</td>\n",
-       "      <td>612</td>\n",
-       "      <td>3</td>\n",
-       "      <td>392</td>\n",
-       "      <td>566</td>\n",
-       "      <td>1253</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>41</th>\n",
-       "      <td>321</td>\n",
-       "      <td>15415</td>\n",
-       "      <td>1408</td>\n",
-       "      <td>687</td>\n",
-       "      <td>415</td>\n",
-       "      <td>108</td>\n",
-       "      <td>505</td>\n",
-       "      <td>843</td>\n",
-       "      <td>6060</td>\n",
-       "      <td>12</td>\n",
-       "      <td>...</td>\n",
-       "      <td>156</td>\n",
-       "      <td>75</td>\n",
-       "      <td>151</td>\n",
-       "      <td>2260</td>\n",
-       "      <td>95</td>\n",
-       "      <td>689</td>\n",
-       "      <td>3</td>\n",
-       "      <td>405</td>\n",
-       "      <td>639</td>\n",
-       "      <td>1613</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>42</th>\n",
-       "      <td>235</td>\n",
-       "      <td>15880</td>\n",
-       "      <td>1731</td>\n",
-       "      <td>692</td>\n",
-       "      <td>366</td>\n",
-       "      <td>115</td>\n",
-       "      <td>600</td>\n",
-       "      <td>785</td>\n",
-       "      <td>6771</td>\n",
-       "      <td>11</td>\n",
-       "      <td>...</td>\n",
-       "      <td>181</td>\n",
-       "      <td>69</td>\n",
-       "      <td>147</td>\n",
-       "      <td>2680</td>\n",
-       "      <td>95</td>\n",
-       "      <td>633</td>\n",
-       "      <td>3</td>\n",
-       "      <td>341</td>\n",
-       "      <td>606</td>\n",
-       "      <td>1546</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>43</th>\n",
-       "      <td>275</td>\n",
-       "      <td>16807</td>\n",
-       "      <td>1531</td>\n",
-       "      <td>1016</td>\n",
-       "      <td>382</td>\n",
-       "      <td>112</td>\n",
-       "      <td>701</td>\n",
-       "      <td>726</td>\n",
-       "      <td>7317</td>\n",
-       "      <td>13</td>\n",
-       "      <td>...</td>\n",
-       "      <td>166</td>\n",
-       "      <td>59</td>\n",
-       "      <td>161</td>\n",
-       "      <td>2601</td>\n",
-       "      <td>77</td>\n",
-       "      <td>716</td>\n",
-       "      <td>3</td>\n",
-       "      <td>306</td>\n",
-       "      <td>562</td>\n",
-       "      <td>1348</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>44</th>\n",
-       "      <td>257</td>\n",
-       "      <td>22958</td>\n",
-       "      <td>1259</td>\n",
-       "      <td>1244</td>\n",
-       "      <td>451</td>\n",
-       "      <td>123</td>\n",
-       "      <td>658</td>\n",
-       "      <td>821</td>\n",
-       "      <td>8195</td>\n",
-       "      <td>16</td>\n",
-       "      <td>...</td>\n",
-       "      <td>243</td>\n",
-       "      <td>62</td>\n",
-       "      <td>177</td>\n",
-       "      <td>3026</td>\n",
-       "      <td>67</td>\n",
-       "      <td>658</td>\n",
-       "      <td>4</td>\n",
-       "      <td>305</td>\n",
-       "      <td>574</td>\n",
-       "      <td>1278</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>45</th>\n",
-       "      <td>267</td>\n",
-       "      <td>27940</td>\n",
-       "      <td>1254</td>\n",
-       "      <td>1233</td>\n",
-       "      <td>420</td>\n",
-       "      <td>86</td>\n",
-       "      <td>683</td>\n",
-       "      <td>750</td>\n",
-       "      <td>8609</td>\n",
-       "      <td>13</td>\n",
-       "      <td>...</td>\n",
-       "      <td>182</td>\n",
-       "      <td>61</td>\n",
-       "      <td>204</td>\n",
-       "      <td>3571</td>\n",
-       "      <td>72</td>\n",
-       "      <td>717</td>\n",
-       "      <td>4</td>\n",
-       "      <td>295</td>\n",
-       "      <td>604</td>\n",
-       "      <td>1189</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>46</th>\n",
-       "      <td>255</td>\n",
-       "      <td>37563</td>\n",
-       "      <td>1784</td>\n",
-       "      <td>1885</td>\n",
-       "      <td>349</td>\n",
-       "      <td>88</td>\n",
-       "      <td>717</td>\n",
-       "      <td>758</td>\n",
-       "      <td>11550</td>\n",
-       "      <td>15</td>\n",
-       "      <td>...</td>\n",
-       "      <td>194</td>\n",
-       "      <td>58</td>\n",
-       "      <td>206</td>\n",
-       "      <td>4277</td>\n",
-       "      <td>69</td>\n",
-       "      <td>811</td>\n",
-       "      <td>7</td>\n",
-       "      <td>332</td>\n",
-       "      <td>663</td>\n",
-       "      <td>1006</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>47</th>\n",
-       "      <td>256</td>\n",
-       "      <td>37519</td>\n",
-       "      <td>1580</td>\n",
-       "      <td>2213</td>\n",
-       "      <td>372</td>\n",
-       "      <td>74</td>\n",
-       "      <td>607</td>\n",
-       "      <td>822</td>\n",
-       "      <td>12837</td>\n",
-       "      <td>15</td>\n",
-       "      <td>...</td>\n",
-       "      <td>190</td>\n",
-       "      <td>52</td>\n",
-       "      <td>205</td>\n",
-       "      <td>4014</td>\n",
-       "      <td>57</td>\n",
-       "      <td>803</td>\n",
-       "      <td>9</td>\n",
-       "      <td>366</td>\n",
-       "      <td>653</td>\n",
-       "      <td>1049</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>48</th>\n",
-       "      <td>258</td>\n",
-       "      <td>41175</td>\n",
-       "      <td>1694</td>\n",
-       "      <td>2263</td>\n",
-       "      <td>319</td>\n",
-       "      <td>59</td>\n",
-       "      <td>618</td>\n",
-       "      <td>805</td>\n",
-       "      <td>13653</td>\n",
-       "      <td>15</td>\n",
-       "      <td>...</td>\n",
-       "      <td>186</td>\n",
-       "      <td>50</td>\n",
-       "      <td>173</td>\n",
-       "      <td>3924</td>\n",
-       "      <td>57</td>\n",
-       "      <td>738</td>\n",
-       "      <td>11</td>\n",
-       "      <td>377</td>\n",
-       "      <td>597</td>\n",
-       "      <td>1040</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>49</th>\n",
-       "      <td>233</td>\n",
-       "      <td>42582</td>\n",
-       "      <td>1890</td>\n",
-       "      <td>2226</td>\n",
-       "      <td>281</td>\n",
-       "      <td>55</td>\n",
-       "      <td>685</td>\n",
-       "      <td>839</td>\n",
-       "      <td>13762</td>\n",
-       "      <td>15</td>\n",
-       "      <td>...</td>\n",
-       "      <td>183</td>\n",
-       "      <td>47</td>\n",
-       "      <td>191</td>\n",
-       "      <td>4454</td>\n",
-       "      <td>34</td>\n",
-       "      <td>695</td>\n",
-       "      <td>12</td>\n",
-       "      <td>435</td>\n",
-       "      <td>748</td>\n",
-       "      <td>1233</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50</th>\n",
-       "      <td>298</td>\n",
-       "      <td>38888</td>\n",
-       "      <td>1670</td>\n",
-       "      <td>2214</td>\n",
-       "      <td>295</td>\n",
-       "      <td>42</td>\n",
-       "      <td>737</td>\n",
-       "      <td>901</td>\n",
-       "      <td>15347</td>\n",
-       "      <td>16</td>\n",
-       "      <td>...</td>\n",
-       "      <td>163</td>\n",
-       "      <td>55</td>\n",
-       "      <td>182</td>\n",
-       "      <td>4307</td>\n",
-       "      <td>37</td>\n",
-       "      <td>720</td>\n",
-       "      <td>11</td>\n",
-       "      <td>446</td>\n",
-       "      <td>667</td>\n",
-       "      <td>813</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>51</th>\n",
-       "      <td>322</td>\n",
-       "      <td>43746</td>\n",
-       "      <td>1835</td>\n",
-       "      <td>2518</td>\n",
-       "      <td>290</td>\n",
-       "      <td>33</td>\n",
-       "      <td>655</td>\n",
-       "      <td>883</td>\n",
-       "      <td>18333</td>\n",
-       "      <td>16</td>\n",
-       "      <td>...</td>\n",
-       "      <td>179</td>\n",
-       "      <td>60</td>\n",
-       "      <td>183</td>\n",
-       "      <td>4403</td>\n",
-       "      <td>28</td>\n",
-       "      <td>862</td>\n",
-       "      <td>11</td>\n",
-       "      <td>594</td>\n",
-       "      <td>670</td>\n",
-       "      <td>861</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>52</th>\n",
-       "      <td>390</td>\n",
-       "      <td>46537</td>\n",
-       "      <td>1735</td>\n",
-       "      <td>2463</td>\n",
-       "      <td>270</td>\n",
-       "      <td>30</td>\n",
-       "      <td>599</td>\n",
-       "      <td>994</td>\n",
-       "      <td>22980</td>\n",
-       "      <td>18</td>\n",
-       "      <td>...</td>\n",
-       "      <td>196</td>\n",
-       "      <td>56</td>\n",
-       "      <td>182</td>\n",
-       "      <td>3768</td>\n",
-       "      <td>29</td>\n",
-       "      <td>716</td>\n",
-       "      <td>6</td>\n",
-       "      <td>517</td>\n",
-       "      <td>723</td>\n",
-       "      <td>962</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>53</th>\n",
-       "      <td>451</td>\n",
-       "      <td>44942</td>\n",
-       "      <td>1829</td>\n",
-       "      <td>2785</td>\n",
-       "      <td>272</td>\n",
-       "      <td>42</td>\n",
-       "      <td>646</td>\n",
-       "      <td>1085</td>\n",
-       "      <td>20596</td>\n",
-       "      <td>21</td>\n",
-       "      <td>...</td>\n",
-       "      <td>177</td>\n",
-       "      <td>57</td>\n",
-       "      <td>138</td>\n",
-       "      <td>2945</td>\n",
-       "      <td>33</td>\n",
-       "      <td>723</td>\n",
-       "      <td>5</td>\n",
-       "      <td>565</td>\n",
-       "      <td>806</td>\n",
-       "      <td>1073</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>53 rows × 175 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "       0      1     2     3     4    5    6     7      8   9  ...  165  166  \\\n",
-       "1   1140   1113  3099    92   621  344  283   284   1095  44  ...  515  207   \n",
-       "2   1211   1378  2821   113   575  319  267   295   1167  52  ...  577  231   \n",
-       "3   1238   1587  2356   107   520  265  296   316   1186  42  ...  473  209   \n",
-       "4   1093   2075  2964   117   578  371  359   349   1151  48  ...  550  227   \n",
-       "5    966   2269  3390   135   614  432  341   428   1107  49  ...  285  189   \n",
-       "6    758   2430  3575   178   802  511  330   552   1046  43  ...  248  167   \n",
-       "7    858   2709  4260   180   696  455  347   488   1014  42  ...  260  194   \n",
-       "8    877   2556  4860   178   747  309  458   457   1000  46  ...  247  190   \n",
-       "9    925   2765  4145   251   770  283  462   495   1131  46  ...  349  177   \n",
-       "10   629   3071  5022   259   775  287  507   438   1207  62  ...  228  197   \n",
-       "11   806   3147  5101   295   845  266  585   433   1259  60  ...  378  221   \n",
-       "12   895   3740  5833   294   843  308  606   451   1567  64  ...  397  211   \n",
-       "13   818   3559  7090   342   680  278  662   468   1612  63  ...  406  217   \n",
-       "14   735   4470  6549   337   622  370  702   583   1702  70  ...  294  220   \n",
-       "15   661   3814  5180   361   707  364  775   720   1620  71  ...  265  158   \n",
-       "16   629   3665  4548   324   790  425  694   725   1403  56  ...  332  136   \n",
-       "17   632   4217  4414   386   760  365  709   741   1432  41  ...  312  149   \n",
-       "18   622   6409  5078   420   799  351  743   847   1567  36  ...  333  136   \n",
-       "19   589   6073  6003   509  1021  381  777   756   2056  23  ...  586  143   \n",
-       "20   604   5948  3024   461  1018  311  866   724   1860  18  ...  525  147   \n",
-       "21   527   5790  3037   427  1017  253  905   878   1689  19  ...  541  165   \n",
-       "22   498   5565  2936   478  1036  341  801   791   1897  19  ...  586  143   \n",
-       "23   483   6992  2568   475  1099  372  848   689   1864  21  ...  491  148   \n",
-       "24   478   7560  2056   449  1061  255  773   571   2339  24  ...  405  147   \n",
-       "25   519   9143  1917   459  1125  244  719   734   2737  25  ...  398  136   \n",
-       "26   471   8515  2455   472   906  237  689   713   3123  26  ...  380  125   \n",
-       "27   472   8535  2273   533   937  263  681   730   3452  28  ...  414  128   \n",
-       "28   482   9314  2290   657   941  234  576   715   2865  28  ...  307  136   \n",
-       "29   367  11850  2488   603   921  199  641   626   2814  26  ...  416  136   \n",
-       "30   376  13020  2349   552   877  151  567   617   3018  23  ...  240  138   \n",
-       "31   336  14235  3180   552   824  146  656   580   2930  22  ...  249  131   \n",
-       "32   267  13853  4212   601   757  158  582   539   2666  20  ...  256  125   \n",
-       "33   328  13833  3753   652   581  114  656   507   2357  18  ...  208  115   \n",
-       "34   416  12753  3749   635   566  141  655   537   3021  21  ...  172  109   \n",
-       "35   456  13324  3433   583   628  138  542   611   3230  23  ...  195  116   \n",
-       "36   434  16070  3117   537   607  122  485   653   3934  17  ...  236  124   \n",
-       "37   363  15712  2100   515   645   94  550   600   4286  16  ...  214  108   \n",
-       "38   379  15150  2193   513   575   80  575   711   5007  11  ...  208   98   \n",
-       "39   375  15444  2196   638   500  101  570   734   4987  11  ...  196   91   \n",
-       "40   322  14844  1556   749   463  107  444   832   5342  11  ...  146   91   \n",
-       "41   321  15415  1408   687   415  108  505   843   6060  12  ...  156   75   \n",
-       "42   235  15880  1731   692   366  115  600   785   6771  11  ...  181   69   \n",
-       "43   275  16807  1531  1016   382  112  701   726   7317  13  ...  166   59   \n",
-       "44   257  22958  1259  1244   451  123  658   821   8195  16  ...  243   62   \n",
-       "45   267  27940  1254  1233   420   86  683   750   8609  13  ...  182   61   \n",
-       "46   255  37563  1784  1885   349   88  717   758  11550  15  ...  194   58   \n",
-       "47   256  37519  1580  2213   372   74  607   822  12837  15  ...  190   52   \n",
-       "48   258  41175  1694  2263   319   59  618   805  13653  15  ...  186   50   \n",
-       "49   233  42582  1890  2226   281   55  685   839  13762  15  ...  183   47   \n",
-       "50   298  38888  1670  2214   295   42  737   901  15347  16  ...  163   55   \n",
-       "51   322  43746  1835  2518   290   33  655   883  18333  16  ...  179   60   \n",
-       "52   390  46537  1735  2463   270   30  599   994  22980  18  ...  196   56   \n",
-       "53   451  44942  1829  2785   272   42  646  1085  20596  21  ...  177   57   \n",
-       "\n",
-       "    167   168  169  170  171  172  173   174  \n",
-       "1   722   401  234  521  284  465  522  1176  \n",
-       "2   655   449  224  600  224  577  492  1258  \n",
-       "3   620   473  231  607  275  407  421  1109  \n",
-       "4   648   447  232  563  188  338  432  1148  \n",
-       "5   640   398  250  535  183  382  459  1181  \n",
-       "6   608   471  266  570  130  360  495  1173  \n",
-       "7   529   464  258  458  100  288  424  1197  \n",
-       "8   412   436  250  411  107  450  440  1193  \n",
-       "9   371   434  205  419  114  509  458  1224  \n",
-       "10  418   512  206  348   75  490  486  1337  \n",
-       "11  436   499  213  337   24  566  448  1057  \n",
-       "12  428   506  211  321   18  609  336  1173  \n",
-       "13  459   553  196  349   20  690  360   956  \n",
-       "14  400   544  214  340   21  792  354   703  \n",
-       "15  402   503  160  380   14  603  364   965  \n",
-       "16  330   730  198  383   14  634  361  1264  \n",
-       "17  341   909  122  452   15  318  369   917  \n",
-       "18  350  1014  161  389   18  219  397   896  \n",
-       "19  360  1062  159  452   23  268  323   764  \n",
-       "20  402  1006  153  433   21  271  360   759  \n",
-       "21  434  1182  137  497   17  299  353   880  \n",
-       "22  381  1112   74  556   15  349  411  1140  \n",
-       "23  426  1214   67  397   17  451  392  1203  \n",
-       "24  417  1434   53  417   23  537  365  1131  \n",
-       "25  335  1468   56  458   23  533  360  1178  \n",
-       "26  331  1604   52  519   21  497  378  1085  \n",
-       "27  353  1745   58  458   20  412  367  1336  \n",
-       "28  317  1579   50  485   19  396  388  1590  \n",
-       "29  359  1643   61  494   17  374  373  1628  \n",
-       "30  326  1368   62  516   17  383  375  1508  \n",
-       "31  310  1370   49  567   10  409  459  1376  \n",
-       "32  290  1216   47  633    9  565  475   913  \n",
-       "33  240  1193   41  592    9  621  496  1049  \n",
-       "34  216  1324   35  607    6  658  423  1028  \n",
-       "35  201  1810   35  610    4  613  480   953  \n",
-       "36  198  1728   38  595    4  409  531   942  \n",
-       "37  139  1739   46  587    5  372  493  1084  \n",
-       "38  149  1743   47  598    6  416  545   872  \n",
-       "39  159  2161   62  562    3  360  563  1029  \n",
-       "40  178  2151   80  612    3  392  566  1253  \n",
-       "41  151  2260   95  689    3  405  639  1613  \n",
-       "42  147  2680   95  633    3  341  606  1546  \n",
-       "43  161  2601   77  716    3  306  562  1348  \n",
-       "44  177  3026   67  658    4  305  574  1278  \n",
-       "45  204  3571   72  717    4  295  604  1189  \n",
-       "46  206  4277   69  811    7  332  663  1006  \n",
-       "47  205  4014   57  803    9  366  653  1049  \n",
-       "48  173  3924   57  738   11  377  597  1040  \n",
-       "49  191  4454   34  695   12  435  748  1233  \n",
-       "50  182  4307   37  720   11  446  667   813  \n",
-       "51  183  4403   28  862   11  594  670   861  \n",
-       "52  182  3768   29  716    6  517  723   962  \n",
-       "53  138  2945   33  723    5  565  806  1073  \n",
-       "\n",
-       "[53 rows x 175 columns]"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Remove duplicated row\n",
-    "raw_data.drop([0])"
+    "raw_data.drop([0], inplace=True)"
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "8326c068-5e4a-40cf-ba7b-3e707469a1a3",
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6d6741b8",
    "metadata": {},
+   "outputs": [],
    "source": [
-    "At this point, we might decide to visualize our dataset and see if there are any obvious outliers or anomalies. Let's look at the first country!"
+    "raw_data.shape"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 51,
-   "id": "ddd7fef2-7ca3-440c-8bbd-6e17690f0db7",
+   "cell_type": "markdown",
+   "id": "8326c068-5e4a-40cf-ba7b-3e707469a1a3",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fd89e7ea7f0>]"
-      ]
-     },
-     "execution_count": 51,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
    "source": [
-    "import matplotlib.pyplot as plt\n",
-    "plt.plot(raw_data.T[24], \"r-*\")"
+    "At this point, we might decide to visualize our dataset and see if there are any obvious outliers or anomalies. Let's look at the first country!"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
-   "id": "ed96e05f-68c7-4390-8571-6c481fe5818f",
+   "execution_count": null,
+   "id": "ddd7fef2-7ca3-440c-8bbd-6e17690f0db7",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "54"
-      ]
-     },
-     "execution_count": 46,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "raw_data.T[0].shape[0]"
+    "import matplotlib.pyplot as plt\n",
+    "plt.plot(raw_data.T.iloc[0], \"r-*\")\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": null,
    "id": "bb0378da-80cd-43e4-bb0e-1778b132785e",
    "metadata": {},
    "outputs": [],
    "source": [
+    "import numpy as np \n",
+    "\n",
     "def plot_extrapolated_country(idx):\n",
-    "    x = list(range(54))\n",
-    "    y = raw_data.T[idx]\n",
+    "    x = list(range(53))\n",
+    "    y = raw_data.T.iloc[idx]\n",
     "    \n",
     "    plt.plot(y)\n",
     "    \n",
@@ -2359,49 +327,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": null,
    "id": "f252c345-c5e2-4f00-83c1-5f24f5992656",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plot_extrapolated_country(129)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": null,
    "id": "9c67efe9-764f-4ce0-9c71-a5519e949885",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "129"
-      ]
-     },
-     "execution_count": 49,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "thingies = []\n",
     "for i in range(raw_data.T.shape[0]):\n",
-    "    x = range(54)\n",
-    "    y = raw_data.T[i]\n",
+    "    x = range(53)\n",
+    "    y = raw_data.T.iloc[i]\n",
     "    slope, intercept = np.polyfit(x, y, 1)\n",
     "    thingies.append(slope) #raw_data.T[i, -1] - raw_data.T[i, 0])\n",
     "    \n",
@@ -2410,35 +354,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": null,
    "id": "0fdaf6f8-d371-43fe-a064-f5a7a14073a0",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<AxesSubplot:>"
-      ]
-     },
-     "execution_count": 80,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "pd.DataFrame(raw_data).plot(legend=False)"
+    "pd.DataFrame(raw_data).plot(legend=False)\n",
+    "plt.show()"
    ]
   },
   {
@@ -2446,7 +368,9 @@
    "id": "c34d0da1-0e3e-4aaf-b26a-744e9a5c9dac",
    "metadata": {},
    "source": [
-    "This seems alright, and doesn't seem to have any clear outliers or anomalies. We could do this for other countries, and maybe even employ other visualization methods such as clustering or PCA, depending on the type of data we're working with."
+    "This seems alright, and doesn't seem to have any clear outliers or anomalies. \n",
+    "\n",
+    "We could do this for other countries, and maybe even employ other visualization methods such as clustering or PCA, depending on the type of data we're working with."
    ]
   },
   {
@@ -2512,19 +436,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "id": "ddeb8d90-2dac-4637-a938-485d1548f94e",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "raw_data is of type: <class 'pandas.core.frame.DataFrame'>\n",
-      "raw_data is of type: <class 'numpy.ndarray'>\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Convert a Pandas Dataframe to NumPy array\n",
     "print(f'raw_data is of type: {type(raw_data)}')\n",
@@ -2534,19 +449,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "a69125e4-579e-4b1c-a2bf-d72040d58d45",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "test_data is of type: <class 'torch.Tensor'>\n",
-      "test_data is of type: <class 'numpy.ndarray'>\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Convert a PyTorch Tensor to a NumPy array\n",
     "import torch\n",
@@ -2566,7 +472,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "id": "90c1d0f3-e33b-4985-a9ac-0d0626a18792",
    "metadata": {},
    "outputs": [],
@@ -2585,19 +491,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "id": "805c2b1a-8a1f-47c3-8de2-4fafab86a2ef",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "random_data is of dtype: float64\n",
-      "random_data is now of type: int32\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "random_data = np.random.random((5, 5)) * 10\n",
     "print(f'random_data is of dtype: {random_data.dtype}')\n",
@@ -2679,7 +576,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
+   "id": "d8f0cd3d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "raw_data.T[0].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "id": "7c765d97-e091-4351-a0d4-420fb1121c32",
    "metadata": {},
    "outputs": [],
@@ -2687,7 +594,7 @@
     "import syft as sy\n",
     "\n",
     "# select all of Country 0's data\n",
-    "country0_data = raw_data[1:, :]\n",
+    "country0_data = raw_data.T[0]\n",
     "\n",
     "# Specify it to be a np.int32 dtype\n",
     "country0_data = country0_data.astype(np.int32)\n",
@@ -2713,14 +620,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": null,
+   "id": "bc60923b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "raw_data.shape[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "id": "0f741fe4-5adf-4406-8727-18af72477dbe",
    "metadata": {},
    "outputs": [],
    "source": [
     "dataset = {\"Country 0\" : data}\n",
     "entities = []\n",
-    "for i in range(raw_data.shape[-1]):\n",
+    "for i in range(1, raw_data.shape[-1]):\n",
     "    country_name = f\"Country {i}\"\n",
     "    \n",
     "    # Create a new Entity correspoinding to the country and add it to the list\n",
@@ -2728,7 +645,9 @@
     "    entities.append(new_entity)\n",
     "    \n",
     "    # Add it to the Dataset Dictionary\n",
-    "    dataset[country_name] = sy.Tensor(raw_data[:, i].astype(np.int32)).private(min_val=0, max_val=150000, entities=new_entity)"
+    "    entry = sy.Tensor(raw_data[:, i].astype(np.int32)).private(min_val=0, max_val=150000, \n",
+    "                                                               entities=new_entity)\n",
+    "    dataset[country_name] = entry"
    ]
   },
   {
@@ -2743,39 +662,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "id": "c3d7642b-00f2-486a-80d8-9fee4a41bdae",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Connecting to http://localhost:8081... done! \t Logging into new_phil_node... done!\n",
-      "Loading dataset... checking dataset name for uniqueness.......\n",
-      "\n",
-      "WARNING - Dataset Name Conflict: A dataset named 'COVID19 Cases in 175 countries' already exists.\n",
-      "\n"
-     ]
-    },
-    {
-     "name": "stdin",
-     "output_type": "stream",
-     "text": [
-      "Do you want to upload this dataset anyway? (y/n) y\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "Loading dataset... uploading... SUCCESS!                                                                                                                                      \n",
-      "\n",
-      "Run <your client variable>.datasets to see your new dataset loaded into your machine!\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Login to Domain Node\n",
     "domain_node = sy.login(email=\"info@openmined.org\", password=\"changethis\", port=8081)\n",
@@ -2800,144 +690,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "id": "a397bf1c-c32e-4dbd-a53d-d5464b37c412",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<style>\n",
-       "                #myInput {\n",
-       "                  background-position: 10px 12px; /* Position the search icon */\n",
-       "                  background-repeat: no-repeat; /* Do not repeat the icon image */\n",
-       "                  background-color: #bbb;\n",
-       "                  width: 98%; /* Full-width */\n",
-       "                  font-size: 14px; /* Increase font-size */\n",
-       "                  padding: 12px 20px 12px 40px; /* Add some padding */\n",
-       "                  border: 1px solid #ddd; /* Add a grey border */\n",
-       "                  margin-bottom: 12px; /* Add some space below the input */\n",
-       "                }\n",
-       "\n",
-       "                #myTable {\n",
-       "                  border-collapse: collapse; /* Collapse borders */\n",
-       "                  width: 100%; /* Full-width */\n",
-       "                  border: 1px solid #ddd; /* Add a grey border */\n",
-       "                  font-size: 14px; /* Increase font-size */\n",
-       "                }\n",
-       "\n",
-       "                #myTable th, #myTable td {\n",
-       "                  text-align: left; /* Left-align text */\n",
-       "                  padding: 10px; /* Add padding */\n",
-       "                }\n",
-       "\n",
-       "                #myTable tr {\n",
-       "                  /* Add a bottom border to all table rows */\n",
-       "                  border-bottom: 1px solid #ddd;\n",
-       "                }\n",
-       "\n",
-       "                #myTable tr.header, #myTable tr:hover {\n",
-       "                  /* Add a grey background color to the table header and on hover */\n",
-       "                  background-color: #777;\n",
-       "                }\n",
-       "                </style>\n",
-       "\n",
-       "                <input type=\"text\" id=\"myInput\" onkeyup=\"myFunction()\" placeholder=\"Search for datasets..\">\n",
-       "\n",
-       "                <table id=\"myTable\">\n",
-       "                  <tr class=\"header\">\n",
-       "                    <th style=\"width:30px\">Idx</th>\n",
-       "                    <th style=\"width:20%;\">Name</th>\n",
-       "                    <th style=\"width:35%;\">Description</th>\n",
-       "                    <th style=\"width:20%;\">Assets</th>\n",
-       "                    <th style=\"width:300px;\">Id</th>\n",
-       "                  </tr>\n",
-       "                \n",
-       "\n",
-       "          <tr>\n",
-       "            <td>[0]</td>\n",
-       "            <td>COVID Synthetic Weekly Cases</td>\n",
-       "            <td>Synthetically-generated COVID weekly case dataset</td>\n",
-       "            <td>[\"0\"] -> Tensor<br /><br />[\"1\"] -> Tensor<br /><br />[\"2\"] -> Tensor<br /><br />[\"3\"] -> Tensor<br /><br />[\"4\"] -> Tensor<br /><br />[\"5\"] -> Tensor<br /><br />[\"6\"] -> Tensor<br /><br />[\"7\"] -> Tensor<br /><br />[\"8\"] -> Tensor<br /><br />[\"9\"] -> Tensor<br /><br /></td>\n",
-       "            <td>cb441fdc-aefa-4a44-8f1e-fe61c4e0eb3a</td>\n",
-       "          </tr>\n",
-       "\n",
-       "          <tr>\n",
-       "            <td>[1]</td>\n",
-       "            <td>COVID Synthetic Weekly Cases v6</td>\n",
-       "            <td>Synthetically-generated COVID weekly case dataset</td>\n",
-       "            <td>[\"weeklyCases\"] -> Tensor<br /><br />[\"nextWeekCases\"] -> Tensor<br /><br /></td>\n",
-       "            <td>8d1e7ac7-a562-4f05-805f-9f6cac0a0d54</td>\n",
-       "          </tr>\n",
-       "\n",
-       "          <tr>\n",
-       "            <td>[2]</td>\n",
-       "            <td>COVID Synthetic Weekly Cases v7</td>\n",
-       "            <td>Synthetically-generated COVID weekly case dataset</td>\n",
-       "            <td>[\"weeklyCases\"] -> Tensor<br /><br /></td>\n",
-       "            <td>32ea0eaf-5c47-4b27-8d2b-7a899e227dcc</td>\n",
-       "          </tr>\n",
-       "\n",
-       "          <tr>\n",
-       "            <td>[3]</td>\n",
-       "            <td>COVID19 Cases in 175 countries</td>\n",
-       "            <td>Weekly data for an entire year</td>\n",
-       "            <td>[\"Country 0\"] -> Tensor<br /><br />[\"Country 1\"] -> Tensor<br /><br />[\"Country 2\"] -> Tensor<br /><br />[\"Country 3\"] -> Tensor<br /><br />[\"Country 4\"] -> Tensor<br /><br />[\"Country 5\"] -> Tensor<br /><br />[\"Country 6\"] -> Tensor<br /><br />[\"Country 7\"] -> Tensor<br /><br />[\"Country 8\"] -> Tensor<br /><br />[\"Country 9\"] -> Tensor<br /><br />[\"Country 10\"] -> Tensor<br /><br />[\"Country 11\"] -> Tensor<br /><br />[\"Country 12\"] -> Tensor<br /><br />[\"Country 13\"] -> Tensor<br /><br />[\"Country 14\"] -> Tensor<br /><br />[\"Country 15\"] -> Tensor<br /><br />[\"Country 16\"] -> Tensor<br /><br />[\"Country 17\"] -> Tensor<br /><br />[\"Country 18\"] -> Tensor<br /><br />[\"Country 19\"] -> Tensor<br /><br />[\"Country 20\"] -> Tensor<br /><br />[\"Country 21\"] -> Tensor<br /><br />[\"Country 22\"] -> Tensor<br /><br />[\"Country 23\"] -> Tensor<br /><br />[\"Country 24\"] -> Tensor<br /><br />[\"Country 25\"] -> Tensor<br /><br />[\"Country 26\"] -> Tensor<br /><br />[\"Country 27\"] -> Tensor<br /><br />[\"Country 28\"] -> Tensor<br /><br />[\"Country 29\"] -> Tensor<br /><br />[\"Country 30\"] -> Tensor<br /><br />[\"Country 31\"] -> Tensor<br /><br />[\"Country 32\"] -> Tensor<br /><br />[\"Country 33\"] -> Tensor<br /><br />[\"Country 34\"] -> Tensor<br /><br />[\"Country 35\"] -> Tensor<br /><br />[\"Country 36\"] -> Tensor<br /><br />[\"Country 37\"] -> Tensor<br /><br />[\"Country 38\"] -> Tensor<br /><br />[\"Country 39\"] -> Tensor<br /><br />[\"Country 40\"] -> Tensor<br /><br />[\"Country 41\"] -> Tensor<br /><br />[\"Country 42\"] -> Tensor<br /><br />[\"Country 43\"] -> Tensor<br /><br />[\"Country 44\"] -> Tensor<br /><br />[\"Country 45\"] -> Tensor<br /><br />[\"Country 46\"] -> Tensor<br /><br />[\"Country 47\"] -> Tensor<br /><br />[\"Country 48\"] -> Tensor<br /><br />[\"Country 49\"] -> Tensor<br /><br />[\"Country 50\"] -> Tensor<br /><br />[\"Country 51\"] -> Tensor<br /><br />[\"Country 52\"] -> Tensor<br /><br />[\"Country 53\"] -> Tensor<br /><br />[\"Country 54\"] -> Tensor<br /><br />[\"Country 55\"] -> Tensor<br /><br />[\"Country 56\"] -> Tensor<br /><br />[\"Country 57\"] -> Tensor<br /><br />[\"Country 58\"] -> Tensor<br /><br />[\"Country 59\"] -> Tensor<br /><br />[\"Country 60\"] -> Tensor<br /><br />[\"Country 61\"] -> Tensor<br /><br />[\"Country 62\"] -> Tensor<br /><br />[\"Country 63\"] -> Tensor<br /><br />[\"Country 64\"] -> Tensor<br /><br />[\"Country 65\"] -> Tensor<br /><br />[\"Country 66\"] -> Tensor<br /><br />[\"Country 67\"] -> Tensor<br /><br />[\"Country 68\"] -> Tensor<br /><br />[\"Country 69\"] -> Tensor<br /><br />[\"Country 70\"] -> Tensor<br /><br />[\"Country 71\"] -> Tensor<br /><br />[\"Country 72\"] -> Tensor<br /><br />[\"Country 73\"] -> Tensor<br /><br />[\"Country 74\"] -> Tensor<br /><br />[\"Country 75\"] -> Tensor<br /><br />[\"Country 76\"] -> Tensor<br /><br />[\"Country 77\"] -> Tensor<br /><br />[\"Country 78\"] -> Tensor<br /><br />[\"Country 79\"] -> Tensor<br /><br />[\"Country 80\"] -> Tensor<br /><br />[\"Country 81\"] -> Tensor<br /><br />[\"Country 82\"] -> Tensor<br /><br />[\"Country 83\"] -> Tensor<br /><br />[\"Country 84\"] -> Tensor<br /><br />[\"Country 85\"] -> Tensor<br /><br />[\"Country 86\"] -> Tensor<br /><br />[\"Country 87\"] -> Tensor<br /><br />[\"Country 88\"] -> Tensor<br /><br />[\"Country 89\"] -> Tensor<br /><br />[\"Country 90\"] -> Tensor<br /><br />[\"Country 91\"] -> Tensor<br /><br />[\"Country 92\"] -> Tensor<br /><br />[\"Country 93\"] -> Tensor<br /><br />[\"Country 94\"] -> Tensor<br /><br />[\"Country 95\"] -> Tensor<br /><br />[\"Country 96\"] -> Tensor<br /><br />[\"Country 97\"] -> Tensor<br /><br />[\"Country 98\"] -> Tensor<br /><br />[\"Country 99\"] -> Tensor<br /><br />[\"Country 100\"] -> Tensor<br /><br />[\"Country 101\"] -> Tensor<br /><br />[\"Country 102\"] -> Tensor<br /><br />[\"Country 103\"] -> Tensor<br /><br />[\"Country 104\"] -> Tensor<br /><br />[\"Country 105\"] -> Tensor<br /><br />[\"Country 106\"] -> Tensor<br /><br />[\"Country 107\"] -> Tensor<br /><br />[\"Country 108\"] -> Tensor<br /><br />[\"Country 109\"] -> Tensor<br /><br />[\"Country 110\"] -> Tensor<br /><br />[\"Country 111\"] -> Tensor<br /><br />[\"Country 112\"] -> Tensor<br /><br />[\"Country 113\"] -> Tensor<br /><br />[\"Country 114\"] -> Tensor<br /><br />[\"Country 115\"] -> Tensor<br /><br />[\"Country 116\"] -> Tensor<br /><br />[\"Country 117\"] -> Tensor<br /><br />[\"Country 118\"] -> Tensor<br /><br />[\"Country 119\"] -> Tensor<br /><br />[\"Country 120\"] -> Tensor<br /><br />[\"Country 121\"] -> Tensor<br /><br />[\"Country 122\"] -> Tensor<br /><br />[\"Country 123\"] -> Tensor<br /><br />[\"Country 124\"] -> Tensor<br /><br />[\"Country 125\"] -> Tensor<br /><br />[\"Country 126\"] -> Tensor<br /><br />[\"Country 127\"] -> Tensor<br /><br />[\"Country 128\"] -> Tensor<br /><br />[\"Country 129\"] -> Tensor<br /><br />[\"Country 130\"] -> Tensor<br /><br />[\"Country 131\"] -> Tensor<br /><br />[\"Country 132\"] -> Tensor<br /><br />[\"Country 133\"] -> Tensor<br /><br />[\"Country 134\"] -> Tensor<br /><br />[\"Country 135\"] -> Tensor<br /><br />[\"Country 136\"] -> Tensor<br /><br />[\"Country 137\"] -> Tensor<br /><br />[\"Country 138\"] -> Tensor<br /><br />[\"Country 139\"] -> Tensor<br /><br />[\"Country 140\"] -> Tensor<br /><br />[\"Country 141\"] -> Tensor<br /><br />[\"Country 142\"] -> Tensor<br /><br />[\"Country 143\"] -> Tensor<br /><br />[\"Country 144\"] -> Tensor<br /><br />[\"Country 145\"] -> Tensor<br /><br />[\"Country 146\"] -> Tensor<br /><br />[\"Country 147\"] -> Tensor<br /><br />[\"Country 148\"] -> Tensor<br /><br />[\"Country 149\"] -> Tensor<br /><br />[\"Country 150\"] -> Tensor<br /><br />[\"Country 151\"] -> Tensor<br /><br />[\"Country 152\"] -> Tensor<br /><br />[\"Country 153\"] -> Tensor<br /><br />[\"Country 154\"] -> Tensor<br /><br />[\"Country 155\"] -> Tensor<br /><br />[\"Country 156\"] -> Tensor<br /><br />[\"Country 157\"] -> Tensor<br /><br />[\"Country 158\"] -> Tensor<br /><br />[\"Country 159\"] -> Tensor<br /><br />[\"Country 160\"] -> Tensor<br /><br />[\"Country 161\"] -> Tensor<br /><br />[\"Country 162\"] -> Tensor<br /><br />[\"Country 163\"] -> Tensor<br /><br />[\"Country 164\"] -> Tensor<br /><br />[\"Country 165\"] -> Tensor<br /><br />[\"Country 166\"] -> Tensor<br /><br />[\"Country 167\"] -> Tensor<br /><br />[\"Country 168\"] -> Tensor<br /><br />[\"Country 169\"] -> Tensor<br /><br />[\"Country 170\"] -> Tensor<br /><br />[\"Country 171\"] -> Tensor<br /><br />[\"Country 172\"] -> Tensor<br /><br />[\"Country 173\"] -> Tensor<br /><br />[\"Country 174\"] -> Tensor<br /><br /></td>\n",
-       "            <td>c0f71066-0ca1-4062-a356-bf5793ab9070</td>\n",
-       "          </tr>\n",
-       "\n",
-       "          <tr>\n",
-       "            <td>[4]</td>\n",
-       "            <td>COVID19 Cases in 175 countries</td>\n",
-       "            <td>Weekly data for an entire year</td>\n",
-       "            <td>[\"Country 0\"] -> Tensor<br /><br />[\"Country 1\"] -> Tensor<br /><br />[\"Country 2\"] -> Tensor<br /><br />[\"Country 3\"] -> Tensor<br /><br />[\"Country 4\"] -> Tensor<br /><br />[\"Country 5\"] -> Tensor<br /><br />[\"Country 6\"] -> Tensor<br /><br />[\"Country 7\"] -> Tensor<br /><br />[\"Country 8\"] -> Tensor<br /><br />[\"Country 9\"] -> Tensor<br /><br />[\"Country 10\"] -> Tensor<br /><br />[\"Country 11\"] -> Tensor<br /><br />[\"Country 12\"] -> Tensor<br /><br />[\"Country 13\"] -> Tensor<br /><br />[\"Country 14\"] -> Tensor<br /><br />[\"Country 15\"] -> Tensor<br /><br />[\"Country 16\"] -> Tensor<br /><br />[\"Country 17\"] -> Tensor<br /><br />[\"Country 18\"] -> Tensor<br /><br />[\"Country 19\"] -> Tensor<br /><br />[\"Country 20\"] -> Tensor<br /><br />[\"Country 21\"] -> Tensor<br /><br />[\"Country 22\"] -> Tensor<br /><br />[\"Country 23\"] -> Tensor<br /><br />[\"Country 24\"] -> Tensor<br /><br />[\"Country 25\"] -> Tensor<br /><br />[\"Country 26\"] -> Tensor<br /><br />[\"Country 27\"] -> Tensor<br /><br />[\"Country 28\"] -> Tensor<br /><br />[\"Country 29\"] -> Tensor<br /><br />[\"Country 30\"] -> Tensor<br /><br />[\"Country 31\"] -> Tensor<br /><br />[\"Country 32\"] -> Tensor<br /><br />[\"Country 33\"] -> Tensor<br /><br />[\"Country 34\"] -> Tensor<br /><br />[\"Country 35\"] -> Tensor<br /><br />[\"Country 36\"] -> Tensor<br /><br />[\"Country 37\"] -> Tensor<br /><br />[\"Country 38\"] -> Tensor<br /><br />[\"Country 39\"] -> Tensor<br /><br />[\"Country 40\"] -> Tensor<br /><br />[\"Country 41\"] -> Tensor<br /><br />[\"Country 42\"] -> Tensor<br /><br />[\"Country 43\"] -> Tensor<br /><br />[\"Country 44\"] -> Tensor<br /><br />[\"Country 45\"] -> Tensor<br /><br />[\"Country 46\"] -> Tensor<br /><br />[\"Country 47\"] -> Tensor<br /><br />[\"Country 48\"] -> Tensor<br /><br />[\"Country 49\"] -> Tensor<br /><br />[\"Country 50\"] -> Tensor<br /><br />[\"Country 51\"] -> Tensor<br /><br />[\"Country 52\"] -> Tensor<br /><br />[\"Country 53\"] -> Tensor<br /><br />[\"Country 54\"] -> Tensor<br /><br />[\"Country 55\"] -> Tensor<br /><br />[\"Country 56\"] -> Tensor<br /><br />[\"Country 57\"] -> Tensor<br /><br />[\"Country 58\"] -> Tensor<br /><br />[\"Country 59\"] -> Tensor<br /><br />[\"Country 60\"] -> Tensor<br /><br />[\"Country 61\"] -> Tensor<br /><br />[\"Country 62\"] -> Tensor<br /><br />[\"Country 63\"] -> Tensor<br /><br />[\"Country 64\"] -> Tensor<br /><br />[\"Country 65\"] -> Tensor<br /><br />[\"Country 66\"] -> Tensor<br /><br />[\"Country 67\"] -> Tensor<br /><br />[\"Country 68\"] -> Tensor<br /><br />[\"Country 69\"] -> Tensor<br /><br />[\"Country 70\"] -> Tensor<br /><br />[\"Country 71\"] -> Tensor<br /><br />[\"Country 72\"] -> Tensor<br /><br />[\"Country 73\"] -> Tensor<br /><br />[\"Country 74\"] -> Tensor<br /><br />[\"Country 75\"] -> Tensor<br /><br />[\"Country 76\"] -> Tensor<br /><br />[\"Country 77\"] -> Tensor<br /><br />[\"Country 78\"] -> Tensor<br /><br />[\"Country 79\"] -> Tensor<br /><br />[\"Country 80\"] -> Tensor<br /><br />[\"Country 81\"] -> Tensor<br /><br />[\"Country 82\"] -> Tensor<br /><br />[\"Country 83\"] -> Tensor<br /><br />[\"Country 84\"] -> Tensor<br /><br />[\"Country 85\"] -> Tensor<br /><br />[\"Country 86\"] -> Tensor<br /><br />[\"Country 87\"] -> Tensor<br /><br />[\"Country 88\"] -> Tensor<br /><br />[\"Country 89\"] -> Tensor<br /><br />[\"Country 90\"] -> Tensor<br /><br />[\"Country 91\"] -> Tensor<br /><br />[\"Country 92\"] -> Tensor<br /><br />[\"Country 93\"] -> Tensor<br /><br />[\"Country 94\"] -> Tensor<br /><br />[\"Country 95\"] -> Tensor<br /><br />[\"Country 96\"] -> Tensor<br /><br />[\"Country 97\"] -> Tensor<br /><br />[\"Country 98\"] -> Tensor<br /><br />[\"Country 99\"] -> Tensor<br /><br />[\"Country 100\"] -> Tensor<br /><br />[\"Country 101\"] -> Tensor<br /><br />[\"Country 102\"] -> Tensor<br /><br />[\"Country 103\"] -> Tensor<br /><br />[\"Country 104\"] -> Tensor<br /><br />[\"Country 105\"] -> Tensor<br /><br />[\"Country 106\"] -> Tensor<br /><br />[\"Country 107\"] -> Tensor<br /><br />[\"Country 108\"] -> Tensor<br /><br />[\"Country 109\"] -> Tensor<br /><br />[\"Country 110\"] -> Tensor<br /><br />[\"Country 111\"] -> Tensor<br /><br />[\"Country 112\"] -> Tensor<br /><br />[\"Country 113\"] -> Tensor<br /><br />[\"Country 114\"] -> Tensor<br /><br />[\"Country 115\"] -> Tensor<br /><br />[\"Country 116\"] -> Tensor<br /><br />[\"Country 117\"] -> Tensor<br /><br />[\"Country 118\"] -> Tensor<br /><br />[\"Country 119\"] -> Tensor<br /><br />[\"Country 120\"] -> Tensor<br /><br />[\"Country 121\"] -> Tensor<br /><br />[\"Country 122\"] -> Tensor<br /><br />[\"Country 123\"] -> Tensor<br /><br />[\"Country 124\"] -> Tensor<br /><br />[\"Country 125\"] -> Tensor<br /><br />[\"Country 126\"] -> Tensor<br /><br />[\"Country 127\"] -> Tensor<br /><br />[\"Country 128\"] -> Tensor<br /><br />[\"Country 129\"] -> Tensor<br /><br />[\"Country 130\"] -> Tensor<br /><br />[\"Country 131\"] -> Tensor<br /><br />[\"Country 132\"] -> Tensor<br /><br />[\"Country 133\"] -> Tensor<br /><br />[\"Country 134\"] -> Tensor<br /><br />[\"Country 135\"] -> Tensor<br /><br />[\"Country 136\"] -> Tensor<br /><br />[\"Country 137\"] -> Tensor<br /><br />[\"Country 138\"] -> Tensor<br /><br />[\"Country 139\"] -> Tensor<br /><br />[\"Country 140\"] -> Tensor<br /><br />[\"Country 141\"] -> Tensor<br /><br />[\"Country 142\"] -> Tensor<br /><br />[\"Country 143\"] -> Tensor<br /><br />[\"Country 144\"] -> Tensor<br /><br />[\"Country 145\"] -> Tensor<br /><br />[\"Country 146\"] -> Tensor<br /><br />[\"Country 147\"] -> Tensor<br /><br />[\"Country 148\"] -> Tensor<br /><br />[\"Country 149\"] -> Tensor<br /><br />[\"Country 150\"] -> Tensor<br /><br />[\"Country 151\"] -> Tensor<br /><br />[\"Country 152\"] -> Tensor<br /><br />[\"Country 153\"] -> Tensor<br /><br />[\"Country 154\"] -> Tensor<br /><br />[\"Country 155\"] -> Tensor<br /><br />[\"Country 156\"] -> Tensor<br /><br />[\"Country 157\"] -> Tensor<br /><br />[\"Country 158\"] -> Tensor<br /><br />[\"Country 159\"] -> Tensor<br /><br />[\"Country 160\"] -> Tensor<br /><br />[\"Country 161\"] -> Tensor<br /><br />[\"Country 162\"] -> Tensor<br /><br />[\"Country 163\"] -> Tensor<br /><br />[\"Country 164\"] -> Tensor<br /><br />[\"Country 165\"] -> Tensor<br /><br />[\"Country 166\"] -> Tensor<br /><br />[\"Country 167\"] -> Tensor<br /><br />[\"Country 168\"] -> Tensor<br /><br />[\"Country 169\"] -> Tensor<br /><br />[\"Country 170\"] -> Tensor<br /><br />[\"Country 171\"] -> Tensor<br /><br />[\"Country 172\"] -> Tensor<br /><br />[\"Country 173\"] -> Tensor<br /><br />[\"Country 174\"] -> Tensor<br /><br /></td>\n",
-       "            <td>f1e37695-43f1-4d44-9242-b0d62391e406</td>\n",
-       "          </tr>\n",
-       "        </table>\n",
-       "\n",
-       "        <script>\n",
-       "        function myFunction() {\n",
-       "          // Declare variables\n",
-       "          var input, filter, table, tr, td, i, txtValue;\n",
-       "          input = document.getElementById(\"myInput\");\n",
-       "          filter = input.value.toUpperCase();\n",
-       "          table = document.getElementById(\"myTable\");\n",
-       "          tr = table.getElementsByTagName(\"tr\");\n",
-       "\n",
-       "          // Loop through all table rows, and hide those who don't match the search query\n",
-       "          for (i = 0; i < tr.length; i++) {\n",
-       "            name_td = tr[i].getElementsByTagName(\"td\")[1];\n",
-       "            desc_td = tr[i].getElementsByTagName(\"td\")[2];\n",
-       "            asset_td = tr[i].getElementsByTagName(\"td\")[3];\n",
-       "            id_td = tr[i].getElementsByTagName(\"td\")[4];\n",
-       "            if (name_td || desc_td || asset_td || id_td) {\n",
-       "              name_txtValue = name_td.textContent || name_td.innerText;\n",
-       "              desc_txtValue = desc_td.textContent || name_td.innerText;\n",
-       "              asset_txtValue = asset_td.textContent || name_td.innerText;\n",
-       "              id_txtValue = id_td.textContent || name_td.innerText;\n",
-       "              name_bool = name_txtValue.toUpperCase().indexOf(filter) > -1;\n",
-       "              desc_bool = desc_txtValue.toUpperCase().indexOf(filter) > -1;\n",
-       "              asset_bool = asset_txtValue.toUpperCase().indexOf(filter) > -1;\n",
-       "              id_bool = id_txtValue.toUpperCase().indexOf(filter) > -1;\n",
-       "              if (name_bool || desc_bool || asset_bool || id_bool) {\n",
-       "                tr[i].style.display = \"\";\n",
-       "              } else {\n",
-       "                tr[i].style.display = \"none\";\n",
-       "              }\n",
-       "            }\n",
-       "          }\n",
-       "        }\n",
-       "        </script>"
-      ],
-      "text/plain": [
-       "<syft.core.node.common.client_manager.dataset_api.DatasetRequestAPI at 0x7fd89c445400>"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "domain_node.datasets"
    ]