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eisuke0912eisuke0912
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change project 2
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Lines changed: 47 additions & 35 deletions

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‎project 2.ipynb‎

Lines changed: 47 additions & 35 deletions
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@@ -26,7 +26,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 1,
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"id": "383f4c4e",
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"metadata": {},
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"outputs": [
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"[478 rows x 6 columns]"
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]
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},
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"execution_count": 2,
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import plotly.io as pio\n",
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"pio.renderers.default = \"jupyterlab\"\n",
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"\n",
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"import pandas as pd\n",
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"\n",
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"# import first data set.\n",
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 2,
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"id": "0b211d5e",
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"metadata": {},
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"outputs": [
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 3,
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"id": "9c6f8357",
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"metadata": {},
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"outputs": [
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 14,
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"id": "ffe0a843",
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"metadata": {},
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"outputs": [
@@ -318,6 +321,7 @@
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" <th>sat_critical_reading_avg_score</th>\n",
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" <th>sat_math_avg_score</th>\n",
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" <th>sat_writing_avg_score</th>\n",
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" <th>total</th>\n",
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" <th>sat_total_score</th>\n",
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" </tr>\n",
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" </thead>\n",
@@ -331,6 +335,7 @@
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" <td>404.0</td>\n",
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" <td>363.0</td>\n",
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" <td>1122.0</td>\n",
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" <td>1122.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
@@ -341,6 +346,7 @@
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" <td>423.0</td>\n",
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" <td>366.0</td>\n",
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" <td>1172.0</td>\n",
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" <td>1172.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
@@ -351,6 +357,7 @@
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" <td>402.0</td>\n",
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" <td>370.0</td>\n",
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" <td>1149.0</td>\n",
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" <td>1149.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
@@ -361,6 +368,7 @@
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" <td>401.0</td>\n",
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" <td>359.0</td>\n",
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" <td>1174.0</td>\n",
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" <td>1174.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>433.0</td>\n",
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" <td>384.0</td>\n",
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" <td>1207.0</td>\n",
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" <td>1207.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>466</th>\n",
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" <td>358.0</td>\n",
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" <td>350.0</td>\n",
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" <td>1055.0</td>\n",
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" <td>1055.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>467</th>\n",
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" <td>317.0</td>\n",
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" <td>358.0</td>\n",
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" <td>1034.0</td>\n",
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" <td>1034.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>471</th>\n",
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" <td>444.0</td>\n",
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" <td>433.0</td>\n",
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" <td>1306.0</td>\n",
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" <td>1306.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>476</th>\n",
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" <td>400.0</td>\n",
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" <td>426.0</td>\n",
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" <td>1322.0</td>\n",
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" <td>1322.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>477</th>\n",
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" <td>370.0</td>\n",
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" <td>360.0</td>\n",
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" <td>1097.0</td>\n",
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" <td>1097.0</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>421 rows × 7 columns</p>\n",
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"<p>421 rows × 8 columns</p>\n",
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"</div>"
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],
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"text/plain": [
@@ -464,23 +479,23 @@
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"476 8 496.0 \n",
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"477 9 367.0 \n",
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"\n",
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" sat_math_avg_score sat_writing_avg_score sat_total_score \n",
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"0 404.0 363.0 1122.0 \n",
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"1 423.0 366.0 1172.0 \n",
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"2 402.0 370.0 1149.0 \n",
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"3 401.0 359.0 1174.0 \n",
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"4 433.0 384.0 1207.0 \n",
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".. ... ... ... \n",
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"466 358.0 350.0 1055.0 \n",
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"467 317.0 358.0 1034.0 \n",
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"471 444.0 433.0 1306.0 \n",
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"476 400.0 426.0 1322.0 \n",
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"477 370.0 360.0 1097.0 \n",
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" sat_math_avg_score sat_writing_avg_score total sat_total_score \n",
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"0 404.0 363.0 1122.0 1122.0 \n",
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"1 423.0 366.0 1172.0 1172.0 \n",
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"2 402.0 370.0 1149.0 1149.0 \n",
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"3 401.0 359.0 1174.0 1174.0 \n",
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"4 433.0 384.0 1207.0 1207.0 \n",
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".. ... ... ... ... \n",
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"466 358.0 350.0 1055.0 1055.0 \n",
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"467 317.0 358.0 1034.0 1034.0 \n",
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"471 444.0 433.0 1306.0 1306.0 \n",
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"476 400.0 426.0 1322.0 1322.0 \n",
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"477 370.0 360.0 1097.0 1097.0 \n",
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"\n",
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"[421 rows x 7 columns]"
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"[421 rows x 8 columns]"
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]
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},
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"execution_count": 5,
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 5,
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"id": "dfa972c0",
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"metadata": {},
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"outputs": [
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"[1000 rows x 38 columns]"
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]
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},
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"execution_count": 6,
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 6,
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"id": "283ea5f7",
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"metadata": {},
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"outputs": [
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"[151 rows x 38 columns]"
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]
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},
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"execution_count": 7,
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 27,
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"id": "ccd77861",
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"metadata": {},
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"outputs": [
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"[67 rows x 2 columns]"
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]
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},
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"execution_count": 8,
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"execution_count": 27,
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"metadata": {},
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"output_type": "execute_result"
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}
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": null,
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"id": "85e30f1c",
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"metadata": {},
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"outputs": [
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"<class 'pandas.core.frame.DataFrame'>\n",
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"RangeIndex: 67 entries, 0 to 66\n",
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"Data columns (total 2 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 sat_total_score 67 non-null float64\n",
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" 1 the percentage of students who receive free or reduced lunch 67 non-null float64\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 sat_total_score 67 non-null float64\n",
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" 1 frl_percent 67 non-null float64\n",
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"dtypes: float64(2)\n",
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"memory usage: 1.2 KB\n"
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]
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}
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],
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"source": [
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"import plotly.io as pio\n",
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"pio.renderers.default = \"jupyterlab\"\n",
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"\n",
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"import plotly.express as px\n",
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"figure = px.scatter(df_merge_sorted,\n",
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" x=\"the percentage of students who receive free or reduced lunch\",\n",
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],
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"metadata": {
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"kernelspec": {
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"display_name": "myenv",
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},

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