{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "7683de09-4b5b-46d3-bfc4-384b14c7768c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "# Prevent scientific notation in pandas output.\n",
    "pd.set_option('display.float_format', lambda x: '%.3f' % x)\n",
    "\n",
    "\n",
    "# Add the parent directory to sys.path\n",
    "sys.path.insert(0, os.path.abspath(os.path.join(os.getcwd(), '..')))\n",
    "\n",
    "\n",
    "from database import Database\n",
    "from model.ticker import Ticker\n",
    "\n",
    "\n",
    "DB_PATH = \"sqlite:///../finance.db\"\n",
    "\n",
    "\n",
    "db = Database(database_url=DB_PATH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4b691b1a-850c-4b70-8132-4cd7dde7fe97",
   "metadata": {},
   "outputs": [],
   "source": [
    "year = 2010\n",
    "year_2010 = f\"SELECT * FROM sma WHERE strftime('%Y', sma.date) = '{year}'\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d92bf552-b9f1-4b07-a15e-49b62e0ae546",
   "metadata": {},
   "outputs": [],
   "source": [
    "year = 2000\n",
    "year_2000 = f\"SELECT * FROM sma WHERE strftime('%Y', sma.date) = '{year}'\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "61aa9543-9e4c-4729-b832-b95c06de77ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "year = 2020\n",
    "year_2020 = f\"SELECT * FROM sma WHERE strftime('%Y', sma.date) = '{year}'\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "fc783f6d-1a10-49f4-be6b-350728535176",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2010 = pd.read_sql(year_2010, db.engine)\n",
    "df_2010['date'] = pd.to_datetime(df_2010['date'], format='%Y-%m-%d %H:%M:%S.%f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3289bf8b-c822-4c78-a68f-ebdacdbb8c0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2000 = pd.read_sql(year_2000, db.engine)\n",
    "df_2000['date'] = pd.to_datetime(df_2000['date'], format='%Y-%m-%d %H:%M:%S.%f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "02942a47-e742-47d4-aeb0-77ca4e0d1967",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2020 = pd.read_sql(year_2020, db.engine)\n",
    "df_2020['date'] = pd.to_datetime(df_2020['date'], format='%Y-%m-%d %H:%M:%S.%f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "f6e520da-ae1c-4c8b-8715-b7845bd30552",
   "metadata": {},
   "outputs": [],
   "source": [
    "symbol = 'HPAR-fake'\n",
    "\n",
    "hpar_2000 = df_2000[df_2000['symbol'] == symbol]\n",
    "hpar_2010 = df_2010[df_2010['symbol'] == symbol]\n",
    "hpar_2020 = df_2020[df_2020['symbol'] == symbol]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "941a0a7b-28ae-4ec4-8beb-23acb240a8b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>symbol</th>\n",
       "      <th>sma_5</th>\n",
       "      <th>sma_10</th>\n",
       "      <th>sma_20</th>\n",
       "      <th>sma_50</th>\n",
       "      <th>sma_100</th>\n",
       "      <th>sma_200</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2000-01-03</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2000-01-04</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2000-01-05</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2000-01-06</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2000-01-07</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>99.581</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>256</td>\n",
       "      <td>2000-12-25</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>59.474</td>\n",
       "      <td>59.585</td>\n",
       "      <td>60.467</td>\n",
       "      <td>63.515</td>\n",
       "      <td>67.022</td>\n",
       "      <td>73.605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>257</td>\n",
       "      <td>2000-12-26</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>59.345</td>\n",
       "      <td>59.454</td>\n",
       "      <td>60.366</td>\n",
       "      <td>63.277</td>\n",
       "      <td>66.897</td>\n",
       "      <td>73.417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>258</td>\n",
       "      <td>2000-12-27</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>59.264</td>\n",
       "      <td>59.338</td>\n",
       "      <td>60.278</td>\n",
       "      <td>63.063</td>\n",
       "      <td>66.769</td>\n",
       "      <td>73.238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>259</td>\n",
       "      <td>2000-12-28</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>59.412</td>\n",
       "      <td>59.436</td>\n",
       "      <td>60.205</td>\n",
       "      <td>62.887</td>\n",
       "      <td>66.644</td>\n",
       "      <td>73.064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>260</td>\n",
       "      <td>2000-12-29</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>59.502</td>\n",
       "      <td>59.465</td>\n",
       "      <td>60.078</td>\n",
       "      <td>62.721</td>\n",
       "      <td>66.512</td>\n",
       "      <td>72.893</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>260 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id       date     symbol  sma_5  sma_10  sma_20  sma_50  sma_100  \\\n",
       "0      1 2000-01-03  HPAR-fake    NaN     NaN     NaN     NaN      NaN   \n",
       "1      2 2000-01-04  HPAR-fake    NaN     NaN     NaN     NaN      NaN   \n",
       "2      3 2000-01-05  HPAR-fake    NaN     NaN     NaN     NaN      NaN   \n",
       "3      4 2000-01-06  HPAR-fake    NaN     NaN     NaN     NaN      NaN   \n",
       "4      5 2000-01-07  HPAR-fake 99.581     NaN     NaN     NaN      NaN   \n",
       "..   ...        ...        ...    ...     ...     ...     ...      ...   \n",
       "255  256 2000-12-25  HPAR-fake 59.474  59.585  60.467  63.515   67.022   \n",
       "256  257 2000-12-26  HPAR-fake 59.345  59.454  60.366  63.277   66.897   \n",
       "257  258 2000-12-27  HPAR-fake 59.264  59.338  60.278  63.063   66.769   \n",
       "258  259 2000-12-28  HPAR-fake 59.412  59.436  60.205  62.887   66.644   \n",
       "259  260 2000-12-29  HPAR-fake 59.502  59.465  60.078  62.721   66.512   \n",
       "\n",
       "     sma_200  \n",
       "0        NaN  \n",
       "1        NaN  \n",
       "2        NaN  \n",
       "3        NaN  \n",
       "4        NaN  \n",
       "..       ...  \n",
       "255   73.605  \n",
       "256   73.417  \n",
       "257   73.238  \n",
       "258   73.064  \n",
       "259   72.893  \n",
       "\n",
       "[260 rows x 9 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hpar_2000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b50bf391-5ad1-431d-8aef-ca628224900c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>symbol</th>\n",
       "      <th>sma_5</th>\n",
       "      <th>sma_10</th>\n",
       "      <th>sma_20</th>\n",
       "      <th>sma_50</th>\n",
       "      <th>sma_100</th>\n",
       "      <th>sma_200</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2610</td>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>51.884</td>\n",
       "      <td>52.313</td>\n",
       "      <td>52.161</td>\n",
       "      <td>53.432</td>\n",
       "      <td>51.925</td>\n",
       "      <td>53.475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2611</td>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>51.872</td>\n",
       "      <td>52.260</td>\n",
       "      <td>52.077</td>\n",
       "      <td>53.417</td>\n",
       "      <td>51.946</td>\n",
       "      <td>53.449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2612</td>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>51.959</td>\n",
       "      <td>52.312</td>\n",
       "      <td>52.072</td>\n",
       "      <td>53.405</td>\n",
       "      <td>51.973</td>\n",
       "      <td>53.428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2613</td>\n",
       "      <td>2010-01-06</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>52.078</td>\n",
       "      <td>52.271</td>\n",
       "      <td>52.069</td>\n",
       "      <td>53.409</td>\n",
       "      <td>52.005</td>\n",
       "      <td>53.407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2614</td>\n",
       "      <td>2010-01-07</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>52.306</td>\n",
       "      <td>52.229</td>\n",
       "      <td>52.119</td>\n",
       "      <td>53.403</td>\n",
       "      <td>52.030</td>\n",
       "      <td>53.391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>2866</td>\n",
       "      <td>2010-12-27</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>49.988</td>\n",
       "      <td>50.002</td>\n",
       "      <td>48.291</td>\n",
       "      <td>46.279</td>\n",
       "      <td>45.890</td>\n",
       "      <td>47.166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>2867</td>\n",
       "      <td>2010-12-28</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>49.941</td>\n",
       "      <td>50.039</td>\n",
       "      <td>48.499</td>\n",
       "      <td>46.411</td>\n",
       "      <td>45.926</td>\n",
       "      <td>47.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>2868</td>\n",
       "      <td>2010-12-29</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>49.998</td>\n",
       "      <td>50.082</td>\n",
       "      <td>48.723</td>\n",
       "      <td>46.551</td>\n",
       "      <td>45.963</td>\n",
       "      <td>47.166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>2869</td>\n",
       "      <td>2010-12-30</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>50.082</td>\n",
       "      <td>50.165</td>\n",
       "      <td>48.949</td>\n",
       "      <td>46.695</td>\n",
       "      <td>46.005</td>\n",
       "      <td>47.170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>2870</td>\n",
       "      <td>2010-12-31</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>50.299</td>\n",
       "      <td>50.207</td>\n",
       "      <td>49.212</td>\n",
       "      <td>46.852</td>\n",
       "      <td>46.059</td>\n",
       "      <td>47.180</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>261 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id       date     symbol  sma_5  sma_10  sma_20  sma_50  sma_100  \\\n",
       "0    2610 2010-01-01  HPAR-fake 51.884  52.313  52.161  53.432   51.925   \n",
       "1    2611 2010-01-04  HPAR-fake 51.872  52.260  52.077  53.417   51.946   \n",
       "2    2612 2010-01-05  HPAR-fake 51.959  52.312  52.072  53.405   51.973   \n",
       "3    2613 2010-01-06  HPAR-fake 52.078  52.271  52.069  53.409   52.005   \n",
       "4    2614 2010-01-07  HPAR-fake 52.306  52.229  52.119  53.403   52.030   \n",
       "..    ...        ...        ...    ...     ...     ...     ...      ...   \n",
       "256  2866 2010-12-27  HPAR-fake 49.988  50.002  48.291  46.279   45.890   \n",
       "257  2867 2010-12-28  HPAR-fake 49.941  50.039  48.499  46.411   45.926   \n",
       "258  2868 2010-12-29  HPAR-fake 49.998  50.082  48.723  46.551   45.963   \n",
       "259  2869 2010-12-30  HPAR-fake 50.082  50.165  48.949  46.695   46.005   \n",
       "260  2870 2010-12-31  HPAR-fake 50.299  50.207  49.212  46.852   46.059   \n",
       "\n",
       "     sma_200  \n",
       "0     53.475  \n",
       "1     53.449  \n",
       "2     53.428  \n",
       "3     53.407  \n",
       "4     53.391  \n",
       "..       ...  \n",
       "256   47.166  \n",
       "257   47.165  \n",
       "258   47.166  \n",
       "259   47.170  \n",
       "260   47.180  \n",
       "\n",
       "[261 rows x 9 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hpar_2010"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "0d9f025f-91b5-493e-a401-ea11e5e6755b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5218</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>51.882</td>\n",
       "      <td>52.465</td>\n",
       "      <td>52.040</td>\n",
       "      <td>50.035</td>\n",
       "      <td>50.018</td>\n",
       "      <td>51.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5219</td>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>51.558</td>\n",
       "      <td>52.415</td>\n",
       "      <td>52.081</td>\n",
       "      <td>50.111</td>\n",
       "      <td>50.063</td>\n",
       "      <td>51.197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5220</td>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>51.527</td>\n",
       "      <td>52.330</td>\n",
       "      <td>52.115</td>\n",
       "      <td>50.209</td>\n",
       "      <td>50.117</td>\n",
       "      <td>51.147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5221</td>\n",
       "      <td>2020-01-06</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>51.618</td>\n",
       "      <td>52.193</td>\n",
       "      <td>52.117</td>\n",
       "      <td>50.298</td>\n",
       "      <td>50.171</td>\n",
       "      <td>51.102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5222</td>\n",
       "      <td>2020-01-07</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>51.828</td>\n",
       "      <td>52.109</td>\n",
       "      <td>52.120</td>\n",
       "      <td>50.398</td>\n",
       "      <td>50.237</td>\n",
       "      <td>51.065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>5475</td>\n",
       "      <td>2020-12-25</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>63.722</td>\n",
       "      <td>62.907</td>\n",
       "      <td>64.027</td>\n",
       "      <td>65.468</td>\n",
       "      <td>62.996</td>\n",
       "      <td>61.716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>5476</td>\n",
       "      <td>2020-12-28</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>64.075</td>\n",
       "      <td>62.987</td>\n",
       "      <td>63.950</td>\n",
       "      <td>65.420</td>\n",
       "      <td>63.055</td>\n",
       "      <td>61.731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>5477</td>\n",
       "      <td>2020-12-29</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>64.307</td>\n",
       "      <td>63.241</td>\n",
       "      <td>63.903</td>\n",
       "      <td>65.383</td>\n",
       "      <td>63.123</td>\n",
       "      <td>61.752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>5478</td>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>64.618</td>\n",
       "      <td>63.615</td>\n",
       "      <td>63.860</td>\n",
       "      <td>65.360</td>\n",
       "      <td>63.187</td>\n",
       "      <td>61.767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>5479</td>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>HPAR-fake</td>\n",
       "      <td>64.922</td>\n",
       "      <td>64.063</td>\n",
       "      <td>63.843</td>\n",
       "      <td>65.348</td>\n",
       "      <td>63.255</td>\n",
       "      <td>61.776</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>262 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id       date     symbol  sma_5  sma_10  sma_20  sma_50  sma_100  \\\n",
       "0    5218 2020-01-01  HPAR-fake 51.882  52.465  52.040  50.035   50.018   \n",
       "1    5219 2020-01-02  HPAR-fake 51.558  52.415  52.081  50.111   50.063   \n",
       "2    5220 2020-01-03  HPAR-fake 51.527  52.330  52.115  50.209   50.117   \n",
       "3    5221 2020-01-06  HPAR-fake 51.618  52.193  52.117  50.298   50.171   \n",
       "4    5222 2020-01-07  HPAR-fake 51.828  52.109  52.120  50.398   50.237   \n",
       "..    ...        ...        ...    ...     ...     ...     ...      ...   \n",
       "257  5475 2020-12-25  HPAR-fake 63.722  62.907  64.027  65.468   62.996   \n",
       "258  5476 2020-12-28  HPAR-fake 64.075  62.987  63.950  65.420   63.055   \n",
       "259  5477 2020-12-29  HPAR-fake 64.307  63.241  63.903  65.383   63.123   \n",
       "260  5478 2020-12-30  HPAR-fake 64.618  63.615  63.860  65.360   63.187   \n",
       "261  5479 2020-12-31  HPAR-fake 64.922  64.063  63.843  65.348   63.255   \n",
       "\n",
       "     sma_200  \n",
       "0     51.250  \n",
       "1     51.197  \n",
       "2     51.147  \n",
       "3     51.102  \n",
       "4     51.065  \n",
       "..       ...  \n",
       "257   61.716  \n",
       "258   61.731  \n",
       "259   61.752  \n",
       "260   61.767  \n",
       "261   61.776  \n",
       "\n",
       "[262 rows x 9 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hpar_2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "8b8a0dc6-76cf-4d55-bef7-fe79d5eb2c9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the SMAs\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "plt.plot(hpar_2020.index, hpar_2020['sma_200'], label=\"sma_200_days\")\n",
    "plt.plot(hpar_2020.index, hpar_2020['sma_50'], label=\"sma_50_days\")\n",
    "plt.plot(hpar_2020.index, hpar_2020['sma_5'], label=\"sma_5_days\")\n",
    "\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('SMA Value')\n",
    "plt.title(f'5, 50, 200 Day Moving Averages For {symbol}')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "121c9d78-0271-4924-9c02-bab9877c4c5b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "674d457f-50a0-4788-b326-56966ec870a3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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