dip-finder.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import datetime as dt\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# plt.style.use('seaborn-v0_8-pastel')\n",
    "# plt.style.use('seaborn-v0_8-whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from query_stocks import load_ticker_symbols, query_stock_prices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AAPL', 'ACN', 'ADBE', 'AMAT', 'AMD', 'AMZN', 'BAH', 'COF', 'CRM', 'CRWD', 'CTAS', 'EFIV', 'EFX', 'ESGV', 'FICO', 'GOOGL', 'INTU', 'META', 'MGK', 'MSFT', 'NFLX', 'NOW', 'NVDA', 'PANW', 'SCHD', 'SPGI', 'VOO', 'XLK']\n"
     ]
    }
   ],
   "source": [
    "ticker_symbols = load_ticker_symbols(filename=\"stock-list.txt\")\n",
    "ticker_symbols.sort()\n",
    "print(ticker_symbols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%%**********************]  28 of 28 completed\n"
     ]
    }
   ],
   "source": [
    "price_df = query_stock_prices(tickers=ticker_symbols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>ACN</th>\n",
       "      <th>ADBE</th>\n",
       "      <th>AMAT</th>\n",
       "      <th>AMD</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>BAH</th>\n",
       "      <th>COF</th>\n",
       "      <th>CRM</th>\n",
       "      <th>CRWD</th>\n",
       "      <th>CTAS</th>\n",
       "      <th>EFIV</th>\n",
       "      <th>EFX</th>\n",
       "      <th>ESGV</th>\n",
       "      <th>FICO</th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>INTU</th>\n",
       "      <th>META</th>\n",
       "      <th>MGK</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>NFLX</th>\n",
       "      <th>NOW</th>\n",
       "      <th>NVDA</th>\n",
       "      <th>PANW</th>\n",
       "      <th>SCHD</th>\n",
       "      <th>SPGI</th>\n",
       "      <th>VOO</th>\n",
       "      <th>XLK</th>\n",
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       "    <tr>\n",
       "      <th>Date</th>\n",
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       "      <th>2024-10-02</th>\n",
       "      <td>226.779999</td>\n",
       "      <td>356.290009</td>\n",
       "      <td>505.809998</td>\n",
       "      <td>201.149994</td>\n",
       "      <td>159.779999</td>\n",
       "      <td>184.759995</td>\n",
       "      <td>161.309998</td>\n",
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       "      <td>280.239990</td>\n",
       "      <td>205.300003</td>\n",
       "      <td>55.130001</td>\n",
       "      <td>293.329987</td>\n",
       "      <td>100.489998</td>\n",
       "      <td>1938.160034</td>\n",
       "      <td>165.860001</td>\n",
       "      <td>607.280029</td>\n",
       "      <td>572.809998</td>\n",
       "      <td>317.130005</td>\n",
       "      <td>417.130005</td>\n",
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       "      <td>118.849998</td>\n",
       "      <td>332.130005</td>\n",
       "      <td>84.540001</td>\n",
       "      <td>514.710022</td>\n",
       "      <td>522.830017</td>\n",
       "      <td>221.889999</td>\n",
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       "    <tr>\n",
       "      <th>2024-10-03</th>\n",
       "      <td>225.669998</td>\n",
       "      <td>361.239990</td>\n",
       "      <td>503.799988</td>\n",
       "      <td>199.589996</td>\n",
       "      <td>162.850006</td>\n",
       "      <td>181.960007</td>\n",
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       "      <td>1935.949951</td>\n",
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       "      <th>2024-10-04</th>\n",
       "      <td>226.800003</td>\n",
       "      <td>362.239990</td>\n",
       "      <td>507.220001</td>\n",
       "      <td>201.970001</td>\n",
       "      <td>170.899994</td>\n",
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       "      <th>2024-10-07</th>\n",
       "      <td>221.690002</td>\n",
       "      <td>356.799988</td>\n",
       "      <td>487.299988</td>\n",
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       "      <td>521.909973</td>\n",
       "      <td>223.740005</td>\n",
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       "    <tr>\n",
       "      <th>2024-10-08</th>\n",
       "      <td>225.770004</td>\n",
       "      <td>360.380005</td>\n",
       "      <td>496.239990</td>\n",
       "      <td>200.880005</td>\n",
       "      <td>172.800003</td>\n",
       "      <td>182.720001</td>\n",
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       "      <td>293.010010</td>\n",
       "      <td>207.020004</td>\n",
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       "      <td>286.339996</td>\n",
       "      <td>101.379997</td>\n",
       "      <td>1989.579956</td>\n",
       "      <td>164.380005</td>\n",
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       "      <td>322.820007</td>\n",
       "      <td>414.709991</td>\n",
       "      <td>721.760010</td>\n",
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       "      <td>518.349976</td>\n",
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      "text/plain": [
       "                  AAPL         ACN        ADBE        AMAT         AMD  \\\n",
       "Date                                                                     \n",
       "2024-10-02  226.779999  356.290009  505.809998  201.149994  159.779999   \n",
       "2024-10-03  225.669998  361.239990  503.799988  199.589996  162.850006   \n",
       "2024-10-04  226.800003  362.239990  507.220001  201.970001  170.899994   \n",
       "2024-10-07  221.690002  356.799988  487.299988  200.130005  170.970001   \n",
       "2024-10-08  225.770004  360.380005  496.239990  200.880005  172.800003   \n",
       "\n",
       "                  AMZN         BAH         COF         CRM        CRWD  \\\n",
       "Date                                                                     \n",
       "2024-10-02  184.759995  161.309998  146.520004  279.480011  280.239990   \n",
       "2024-10-03  181.960007  160.960007  145.199997  280.910004  283.750000   \n",
       "2024-10-04  186.509995  160.800003  153.440002  287.750000  292.239990   \n",
       "2024-10-07  180.800003  161.259995  152.000000  284.570007  286.970001   \n",
       "2024-10-08  182.720001  161.399994  149.500000  291.570007  293.010010   \n",
       "\n",
       "                  CTAS       EFIV         EFX        ESGV         FICO  \\\n",
       "Date                                                                     \n",
       "2024-10-02  205.300003  55.130001  293.329987  100.489998  1938.160034   \n",
       "2024-10-03  204.550003  55.049999  293.500000  100.250000  1935.949951   \n",
       "2024-10-04  204.910004  55.500000  283.600006  101.199997  1913.380005   \n",
       "2024-10-07  204.470001  55.070000  282.170013  100.180000  1955.000000   \n",
       "2024-10-08  207.020004  55.610001  286.339996  101.379997  1989.579956   \n",
       "\n",
       "                 GOOGL        INTU        META         MGK        MSFT  \\\n",
       "Date                                                                     \n",
       "2024-10-02  165.860001  607.280029  572.809998  317.130005  417.130005   \n",
       "2024-10-03  165.860001  603.809998  582.770020  317.720001  416.540009   \n",
       "2024-10-04  167.059998  610.669983  595.940002  321.079987  416.059998   \n",
       "2024-10-07  162.979996  602.429993  584.780029  317.160004  409.540009   \n",
       "2024-10-08  164.380005  613.369995  592.890015  322.820007  414.709991   \n",
       "\n",
       "                  NFLX         NOW        NVDA        PANW       SCHD  \\\n",
       "Date                                                                    \n",
       "2024-10-02  711.090027  880.409973  118.849998  332.130005  84.540001   \n",
       "2024-10-03  706.799988  890.640015  122.849998  335.940002  84.320000   \n",
       "2024-10-04  719.700012  917.679993  124.919998  342.359985  84.650002   \n",
       "2024-10-07  701.919983  905.940002  127.720001  337.940002  84.300003   \n",
       "2024-10-08  721.760010  922.000000  132.889999  355.130005  84.160004   \n",
       "\n",
       "                  SPGI         VOO         XLK  \n",
       "Date                                            \n",
       "2024-10-02  514.710022  522.830017  221.889999  \n",
       "2024-10-03  514.599976  521.840027  222.809998  \n",
       "2024-10-04  512.169983  526.650024  225.289993  \n",
       "2024-10-07  506.420013  521.909973  223.740005  \n",
       "2024-10-08  518.349976  526.849976  227.919998  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "price_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>ACN</th>\n",
       "      <th>ADBE</th>\n",
       "      <th>AMAT</th>\n",
       "      <th>AMD</th>\n",
       "      <th>AMZN</th>\n",
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       "      <th>2024-10-02</th>\n",
       "      <td>222.346001</td>\n",
       "      <td>335.073199</td>\n",
       "      <td>542.148796</td>\n",
       "      <td>194.8210</td>\n",
       "      <td>146.970001</td>\n",
       "      <td>179.098201</td>\n",
       "      <td>152.6362</td>\n",
       "      <td>142.702999</td>\n",
       "      <td>257.487599</td>\n",
       "      <td>260.142201</td>\n",
       "      <td>197.220001</td>\n",
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       "      <td>292.020599</td>\n",
       "      <td>97.8752</td>\n",
       "      <td>1764.333997</td>\n",
       "      <td>162.2700</td>\n",
       "      <td>633.540397</td>\n",
       "      <td>520.679798</td>\n",
       "      <td>309.1066</td>\n",
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       "      <td>672.320198</td>\n",
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       "      <td>115.7112</td>\n",
       "      <td>336.543399</td>\n",
       "      <td>82.6420</td>\n",
       "      <td>503.163199</td>\n",
       "      <td>508.268398</td>\n",
       "      <td>216.1998</td>\n",
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       "    <tr>\n",
       "      <th>2024-10-03</th>\n",
       "      <td>222.488601</td>\n",
       "      <td>335.724399</td>\n",
       "      <td>541.603997</td>\n",
       "      <td>194.6822</td>\n",
       "      <td>147.334401</td>\n",
       "      <td>179.120801</td>\n",
       "      <td>152.7736</td>\n",
       "      <td>142.678799</td>\n",
       "      <td>258.110199</td>\n",
       "      <td>260.654401</td>\n",
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       "      <td>53.83956</td>\n",
       "      <td>292.672799</td>\n",
       "      <td>97.9590</td>\n",
       "      <td>1771.868196</td>\n",
       "      <td>162.1346</td>\n",
       "      <td>633.211797</td>\n",
       "      <td>523.109799</td>\n",
       "      <td>309.3904</td>\n",
       "      <td>418.527399</td>\n",
       "      <td>673.736398</td>\n",
       "      <td>846.072002</td>\n",
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       "      <td>82.7144</td>\n",
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       "      <td>508.759399</td>\n",
       "      <td>216.3384</td>\n",
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       "      <th>2024-10-04</th>\n",
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       "      <td>336.366799</td>\n",
       "      <td>541.105396</td>\n",
       "      <td>194.6752</td>\n",
       "      <td>147.986001</td>\n",
       "      <td>179.254001</td>\n",
       "      <td>152.9180</td>\n",
       "      <td>142.785799</td>\n",
       "      <td>258.734799</td>\n",
       "      <td>261.416201</td>\n",
       "      <td>197.864751</td>\n",
       "      <td>53.89756</td>\n",
       "      <td>292.994199</td>\n",
       "      <td>98.0742</td>\n",
       "      <td>1778.597195</td>\n",
       "      <td>162.1302</td>\n",
       "      <td>632.898796</td>\n",
       "      <td>525.960399</td>\n",
       "      <td>309.8214</td>\n",
       "      <td>418.480599</td>\n",
       "      <td>675.448597</td>\n",
       "      <td>847.849802</td>\n",
       "      <td>116.1360</td>\n",
       "      <td>337.221999</td>\n",
       "      <td>82.7838</td>\n",
       "      <td>504.398799</td>\n",
       "      <td>509.396799</td>\n",
       "      <td>216.5728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-07</th>\n",
       "      <td>222.749401</td>\n",
       "      <td>336.933599</td>\n",
       "      <td>540.002596</td>\n",
       "      <td>194.5484</td>\n",
       "      <td>148.605601</td>\n",
       "      <td>179.220001</td>\n",
       "      <td>153.3464</td>\n",
       "      <td>142.838599</td>\n",
       "      <td>259.172000</td>\n",
       "      <td>262.032401</td>\n",
       "      <td>198.147201</td>\n",
       "      <td>53.93536</td>\n",
       "      <td>293.202800</td>\n",
       "      <td>98.1454</td>\n",
       "      <td>1785.578396</td>\n",
       "      <td>162.0498</td>\n",
       "      <td>632.280197</td>\n",
       "      <td>528.341999</td>\n",
       "      <td>310.1158</td>\n",
       "      <td>418.166000</td>\n",
       "      <td>676.859597</td>\n",
       "      <td>849.416403</td>\n",
       "      <td>116.4292</td>\n",
       "      <td>337.444599</td>\n",
       "      <td>82.8204</td>\n",
       "      <td>504.730799</td>\n",
       "      <td>509.828399</td>\n",
       "      <td>216.7220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-08</th>\n",
       "      <td>222.900001</td>\n",
       "      <td>337.617198</td>\n",
       "      <td>539.195196</td>\n",
       "      <td>194.4546</td>\n",
       "      <td>149.266601</td>\n",
       "      <td>179.210401</td>\n",
       "      <td>153.6846</td>\n",
       "      <td>142.847399</td>\n",
       "      <td>259.831600</td>\n",
       "      <td>262.716401</td>\n",
       "      <td>198.463301</td>\n",
       "      <td>53.98296</td>\n",
       "      <td>293.451000</td>\n",
       "      <td>98.2386</td>\n",
       "      <td>1793.595596</td>\n",
       "      <td>161.9468</td>\n",
       "      <td>631.820397</td>\n",
       "      <td>530.885599</td>\n",
       "      <td>310.5058</td>\n",
       "      <td>417.925599</td>\n",
       "      <td>678.755597</td>\n",
       "      <td>851.875203</td>\n",
       "      <td>116.8552</td>\n",
       "      <td>338.105999</td>\n",
       "      <td>82.8606</td>\n",
       "      <td>505.301199</td>\n",
       "      <td>510.351398</td>\n",
       "      <td>216.9740</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  AAPL         ACN        ADBE      AMAT         AMD  \\\n",
       "Date                                                                   \n",
       "2024-10-02  222.346001  335.073199  542.148796  194.8210  146.970001   \n",
       "2024-10-03  222.488601  335.724399  541.603997  194.6822  147.334401   \n",
       "2024-10-04  222.674801  336.366799  541.105396  194.6752  147.986001   \n",
       "2024-10-07  222.749401  336.933599  540.002596  194.5484  148.605601   \n",
       "2024-10-08  222.900001  337.617198  539.195196  194.4546  149.266601   \n",
       "\n",
       "                  AMZN       BAH         COF         CRM        CRWD  \\\n",
       "Date                                                                   \n",
       "2024-10-02  179.098201  152.6362  142.702999  257.487599  260.142201   \n",
       "2024-10-03  179.120801  152.7736  142.678799  258.110199  260.654401   \n",
       "2024-10-04  179.254001  152.9180  142.785799  258.734799  261.416201   \n",
       "2024-10-07  179.220001  153.3464  142.838599  259.172000  262.032401   \n",
       "2024-10-08  179.210401  153.6846  142.847399  259.831600  262.716401   \n",
       "\n",
       "                  CTAS      EFIV         EFX     ESGV         FICO     GOOGL  \\\n",
       "Date                                                                           \n",
       "2024-10-02  197.220001  53.79796  292.020599  97.8752  1764.333997  162.2700   \n",
       "2024-10-03  197.540751  53.83956  292.672799  97.9590  1771.868196  162.1346   \n",
       "2024-10-04  197.864751  53.89756  292.994199  98.0742  1778.597195  162.1302   \n",
       "2024-10-07  198.147201  53.93536  293.202800  98.1454  1785.578396  162.0498   \n",
       "2024-10-08  198.463301  53.98296  293.451000  98.2386  1793.595596  161.9468   \n",
       "\n",
       "                  INTU        META       MGK        MSFT        NFLX  \\\n",
       "Date                                                                   \n",
       "2024-10-02  633.540397  520.679798  309.1066  418.774599  672.320198   \n",
       "2024-10-03  633.211797  523.109799  309.3904  418.527399  673.736398   \n",
       "2024-10-04  632.898796  525.960399  309.8214  418.480599  675.448597   \n",
       "2024-10-07  632.280197  528.341999  310.1158  418.166000  676.859597   \n",
       "2024-10-08  631.820397  530.885599  310.5058  417.925599  678.755597   \n",
       "\n",
       "                   NOW      NVDA        PANW     SCHD        SPGI         VOO  \\\n",
       "Date                                                                            \n",
       "2024-10-02  842.876602  115.7112  336.543399  82.6420  503.163199  508.268398   \n",
       "2024-10-03  846.072002  115.8832  336.777399  82.7144  503.821999  508.759399   \n",
       "2024-10-04  847.849802  116.1360  337.221999  82.7838  504.398799  509.396799   \n",
       "2024-10-07  849.416403  116.4292  337.444599  82.8204  504.730799  509.828399   \n",
       "2024-10-08  851.875203  116.8552  338.105999  82.8606  505.301199  510.351398   \n",
       "\n",
       "                 XLK  \n",
       "Date                  \n",
       "2024-10-02  216.1998  \n",
       "2024-10-03  216.3384  \n",
       "2024-10-04  216.5728  \n",
       "2024-10-07  216.7220  \n",
       "2024-10-08  216.9740  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sma_60 = price_df.rolling(50).mean()\n",
    "sma_60.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "sma_price_diff = 100*(price_df/ sma_60 - 1).round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL</th>\n",
       "      <th>ACN</th>\n",
       "      <th>ADBE</th>\n",
       "      <th>AMAT</th>\n",
       "      <th>AMD</th>\n",
       "      <th>AMZN</th>\n",
       "      <th>BAH</th>\n",
       "      <th>COF</th>\n",
       "      <th>CRM</th>\n",
       "      <th>CRWD</th>\n",
       "      <th>CTAS</th>\n",
       "      <th>EFIV</th>\n",
       "      <th>EFX</th>\n",
       "      <th>ESGV</th>\n",
       "      <th>FICO</th>\n",
       "      <th>GOOGL</th>\n",
       "      <th>INTU</th>\n",
       "      <th>META</th>\n",
       "      <th>MGK</th>\n",
       "      <th>MSFT</th>\n",
       "      <th>NFLX</th>\n",
       "      <th>NOW</th>\n",
       "      <th>NVDA</th>\n",
       "      <th>PANW</th>\n",
       "      <th>SCHD</th>\n",
       "      <th>SPGI</th>\n",
       "      <th>VOO</th>\n",
       "      <th>XLK</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-09-25</th>\n",
       "      <td>1.9</td>\n",
       "      <td>1.3</td>\n",
       "      <td>-5.2</td>\n",
       "      <td>0.5</td>\n",
       "      <td>10.8</td>\n",
       "      <td>7.6</td>\n",
       "      <td>5.1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>7.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>10.3</td>\n",
       "      <td>-1.4</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>11.1</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.8</td>\n",
       "      <td>8.4</td>\n",
       "      <td>7.3</td>\n",
       "      <td>6.7</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.8</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-26</th>\n",
       "      <td>2.5</td>\n",
       "      <td>6.8</td>\n",
       "      <td>-5.5</td>\n",
       "      <td>6.9</td>\n",
       "      <td>14.4</td>\n",
       "      <td>6.8</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.6</td>\n",
       "      <td>7.9</td>\n",
       "      <td>7.7</td>\n",
       "      <td>5.6</td>\n",
       "      <td>3.3</td>\n",
       "      <td>0.3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>10.6</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>10.6</td>\n",
       "      <td>4.5</td>\n",
       "      <td>2.7</td>\n",
       "      <td>6.7</td>\n",
       "      <td>6.3</td>\n",
       "      <td>7.1</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.7</td>\n",
       "      <td>2.1</td>\n",
       "      <td>4.1</td>\n",
       "      <td>5.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-27</th>\n",
       "      <td>2.6</td>\n",
       "      <td>4.8</td>\n",
       "      <td>-5.4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>12.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>4.6</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>-2.5</td>\n",
       "      <td>10.1</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>5.8</td>\n",
       "      <td>5.5</td>\n",
       "      <td>4.8</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>2.2</td>\n",
       "      <td>2.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-30</th>\n",
       "      <td>4.8</td>\n",
       "      <td>5.8</td>\n",
       "      <td>-4.8</td>\n",
       "      <td>3.2</td>\n",
       "      <td>11.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>10.9</td>\n",
       "      <td>1.8</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>10.7</td>\n",
       "      <td>4.2</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.9</td>\n",
       "      <td>6.7</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.9</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-01</th>\n",
       "      <td>1.8</td>\n",
       "      <td>5.2</td>\n",
       "      <td>-7.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.8</td>\n",
       "      <td>3.3</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.9</td>\n",
       "      <td>5.4</td>\n",
       "      <td>5.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.6</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>-4.4</td>\n",
       "      <td>11.1</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.3</td>\n",
       "      <td>5.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-02</th>\n",
       "      <td>2.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>-6.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>8.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.7</td>\n",
       "      <td>8.5</td>\n",
       "      <td>7.7</td>\n",
       "      <td>4.1</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>9.9</td>\n",
       "      <td>2.2</td>\n",
       "      <td>-4.1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.6</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>5.8</td>\n",
       "      <td>4.5</td>\n",
       "      <td>2.7</td>\n",
       "      <td>-1.3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2.9</td>\n",
       "      <td>2.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-03</th>\n",
       "      <td>1.4</td>\n",
       "      <td>7.6</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>10.5</td>\n",
       "      <td>1.6</td>\n",
       "      <td>5.4</td>\n",
       "      <td>1.8</td>\n",
       "      <td>8.8</td>\n",
       "      <td>8.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>9.3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-4.6</td>\n",
       "      <td>11.4</td>\n",
       "      <td>2.7</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>4.9</td>\n",
       "      <td>5.3</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-04</th>\n",
       "      <td>1.9</td>\n",
       "      <td>7.7</td>\n",
       "      <td>-6.3</td>\n",
       "      <td>3.7</td>\n",
       "      <td>15.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>7.5</td>\n",
       "      <td>11.2</td>\n",
       "      <td>11.8</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-3.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>7.6</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>13.3</td>\n",
       "      <td>3.6</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>6.6</td>\n",
       "      <td>8.2</td>\n",
       "      <td>7.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-07</th>\n",
       "      <td>-0.5</td>\n",
       "      <td>5.9</td>\n",
       "      <td>-9.8</td>\n",
       "      <td>2.9</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>5.2</td>\n",
       "      <td>6.4</td>\n",
       "      <td>9.8</td>\n",
       "      <td>9.5</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2.1</td>\n",
       "      <td>-3.8</td>\n",
       "      <td>2.1</td>\n",
       "      <td>9.5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>-4.7</td>\n",
       "      <td>10.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-2.1</td>\n",
       "      <td>3.7</td>\n",
       "      <td>6.7</td>\n",
       "      <td>9.7</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.4</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-08</th>\n",
       "      <td>1.3</td>\n",
       "      <td>6.7</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>15.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.7</td>\n",
       "      <td>12.2</td>\n",
       "      <td>11.5</td>\n",
       "      <td>4.3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-2.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>10.9</td>\n",
       "      <td>1.5</td>\n",
       "      <td>-2.9</td>\n",
       "      <td>11.7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>6.3</td>\n",
       "      <td>8.2</td>\n",
       "      <td>13.7</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.6</td>\n",
       "      <td>3.2</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            AAPL  ACN  ADBE  AMAT   AMD  AMZN  BAH  COF   CRM  CRWD  CTAS  \\\n",
       "Date                                                                        \n",
       "2024-09-25   1.9  1.3  -5.2   0.5  10.8   7.6  5.1  2.6   7.5   9.0   6.0   \n",
       "2024-09-26   2.5  6.8  -5.5   6.9  14.4   6.8  4.8  3.6   7.9   7.7   5.6   \n",
       "2024-09-27   2.6  4.8  -5.4   4.6  12.2   5.0  6.3  4.6   8.0   9.9   3.1   \n",
       "2024-09-30   4.8  5.8  -4.8   3.2  11.8   4.0  6.7  5.0   6.6   8.0   4.7   \n",
       "2024-10-01   1.8  5.2  -7.4   1.0   8.8   3.3  7.1  2.9   5.4   5.9   3.5   \n",
       "2024-10-02   2.0  6.3  -6.7   3.2   8.7   3.2  5.7  2.7   8.5   7.7   4.1   \n",
       "2024-10-03   1.4  7.6  -7.0   2.5  10.5   1.6  5.4  1.8   8.8   8.9   3.5   \n",
       "2024-10-04   1.9  7.7  -6.3   3.7  15.5   4.0  5.2  7.5  11.2  11.8   3.6   \n",
       "2024-10-07  -0.5  5.9  -9.8   2.9  15.0   0.9  5.2  6.4   9.8   9.5   3.2   \n",
       "2024-10-08   1.3  6.7  -8.0   3.3  15.8   2.0  5.0  4.7  12.2  11.5   4.3   \n",
       "\n",
       "            EFIV  EFX  ESGV  FICO  GOOGL  INTU  META  MGK  MSFT  NFLX  NOW  \\\n",
       "Date                                                                         \n",
       "2024-09-25   2.8  1.0   3.4  10.3   -1.4  -0.2  11.1  4.4   2.8   8.4  7.3   \n",
       "2024-09-26   3.3  0.3   4.0  10.6   -0.4   0.2  10.6  4.5   2.7   6.7  6.3   \n",
       "2024-09-27   3.2  0.0   3.6  10.0    0.5  -2.5  10.1  3.7   1.9   5.8  5.5   \n",
       "2024-09-30   3.7  1.0   3.9  10.9    1.8  -2.2  10.7  4.2   2.5   5.9  6.7   \n",
       "2024-10-01   2.6 -0.4   2.7   9.0    2.7  -4.4  11.1  2.5   0.3   5.2  3.2   \n",
       "2024-10-02   2.5  0.4   2.7   9.9    2.2  -4.1  10.0  2.6  -0.4   5.8  4.5   \n",
       "2024-10-03   2.2  0.3   2.3   9.3    2.3  -4.6  11.4  2.7  -0.5   4.9  5.3   \n",
       "2024-10-04   3.0 -3.2   3.2   7.6    3.0  -3.5  13.3  3.6  -0.6   6.6  8.2   \n",
       "2024-10-07   2.1 -3.8   2.1   9.5    0.6  -4.7  10.7  2.3  -2.1   3.7  6.7   \n",
       "2024-10-08   3.0 -2.4   3.2  10.9    1.5  -2.9  11.7  4.0  -0.8   6.3  8.2   \n",
       "\n",
       "            NVDA  PANW  SCHD  SPGI  VOO  XLK  \n",
       "Date                                          \n",
       "2024-09-25   6.7   1.3   1.2   2.9  3.8  3.7  \n",
       "2024-09-26   7.1   0.7   1.7   2.1  4.1  5.1  \n",
       "2024-09-27   4.8  -0.2   2.2   2.2  3.6  4.1  \n",
       "2024-09-30   4.8   1.5   2.5   2.9  3.9  4.3  \n",
       "2024-10-01   1.0  -2.2   2.3   1.9  2.9  1.8  \n",
       "2024-10-02   2.7  -1.3   2.3   2.3  2.9  2.6  \n",
       "2024-10-03   6.0  -0.2   1.9   2.1  2.6  3.0  \n",
       "2024-10-04   7.6   1.5   2.3   1.5  3.4  4.0  \n",
       "2024-10-07   9.7   0.1   1.8   0.3  2.4  3.2  \n",
       "2024-10-08  13.7   5.0   1.6   2.6  3.2  5.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sma_price_diff.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_5935/2642137245.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  last_row.sort_values(inplace=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '%')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "last_row = sma_price_diff.iloc[-1]\n",
    "last_row.name = sma_60.index[-1]\n",
    "last_row.sort_values(inplace=True)\n",
    "\n",
    "ax = last_row.plot.bar(figsize=(10, 6))\n",
    "ax.set_ylim(min(-4, last_row.min() - 2),last_row.max() + 2)\n",
    "ax.set_title(f\"Comparisons Against 60 day Moving Average: {last_row.name.date()}\")\n",
    "ax.set_ylabel(\"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "ticker_to_plot = 'AMZN' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(156.02000427246094, 205.0)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s1 = price_df[ticker_to_plot]\n",
    "s2_ma = sma_60[ticker_to_plot].dropna()\n",
    "s1 = s1.loc[s2_ma.index]\n",
    "\n",
    "ax = s2_ma.plot(figsize = (10, 6), linewidth=2)\n",
    "s1.plot(ax=ax, sharex=True, linewidth=2, linestyle=\"--\")\n",
    "\n",
    "ax.set_title(f\"{ticker_to_plot} Price vs 60 Day Moving Average\")\n",
    "ax.set_ylim(s1.min()-5, s1.max()+5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_ma(ticker_to_plot, sma_series, price_df):\n",
    "    s1 = price_df[ticker_to_plot]\n",
    "    s2_ma = sma_series[ticker_to_plot].dropna()\n",
    "    s1 = s1.loc[s2_ma.index]\n",
    "\n",
    "    ax = s2_ma.plot(figsize = (10, 6), linewidth=2)\n",
    "    s1.plot(ax=ax, sharex=True, linewidth=2, linestyle=\"--\")\n",
    "\n",
    "    ax.set_title(f\"{ticker_to_plot} Price vs 60 Day Moving Average\")\n",
    "    ax.set_ylim(s1.min()-5, s1.max()+5)\n",
    "    plt.show()\n",
    "    return ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plot_ma('AAPL', sma_60, price_df=price_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for ticker_to_plot in sorted(ticker_symbols):\n",
    "#     ax = plot_ma(ticker_to_plot, sma_60, price_df=price_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
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   ],
   "source": [
    "import plotly.express as px\n",
    "\n",
    "fig = px.bar(last_row, x=last_row.index, y=last_row)\n",
    "fig.show()"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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  },
  {
   "cell_type": "code",
   "execution_count": 17,
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   "source": [
    "df = pd.DataFrame()\n",
    "df['moving_average'] = sma_60['AAPL']\n",
    "df['AAPL'] = price_df['AAPL']\n",
    "\n",
    "df = df.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
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        },
        "xaxis": {
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          "text": "Date"
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        },
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         "anchor": "x",
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          "text": "value"
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   ],
   "source": [
    "fig = px.line(df)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>moving_average</th>\n",
       "      <th>AAPL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-06-04</th>\n",
       "      <td>178.066400</td>\n",
       "      <td>194.350006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-05</th>\n",
       "      <td>178.566800</td>\n",
       "      <td>195.869995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-06</th>\n",
       "      <td>179.062199</td>\n",
       "      <td>194.479996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-07</th>\n",
       "      <td>179.533799</td>\n",
       "      <td>196.889999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-10</th>\n",
       "      <td>179.966599</td>\n",
       "      <td>193.119995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2024-10-02</th>\n",
       "      <td>222.346001</td>\n",
       "      <td>226.779999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-03</th>\n",
       "      <td>222.488601</td>\n",
       "      <td>225.669998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-04</th>\n",
       "      <td>222.674801</td>\n",
       "      <td>226.800003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-07</th>\n",
       "      <td>222.749401</td>\n",
       "      <td>221.690002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-10-08</th>\n",
       "      <td>222.900001</td>\n",
       "      <td>225.770004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>88 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            moving_average        AAPL\n",
       "Date                                  \n",
       "2024-06-04      178.066400  194.350006\n",
       "2024-06-05      178.566800  195.869995\n",
       "2024-06-06      179.062199  194.479996\n",
       "2024-06-07      179.533799  196.889999\n",
       "2024-06-10      179.966599  193.119995\n",
       "...                    ...         ...\n",
       "2024-10-02      222.346001  226.779999\n",
       "2024-10-03      222.488601  225.669998\n",
       "2024-10-04      222.674801  226.800003\n",
       "2024-10-07      222.749401  221.690002\n",
       "2024-10-08      222.900001  225.770004\n",
       "\n",
       "[88 rows x 2 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8050/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# https://plotly.com/python/time-series/\n",
    "\n",
    "from dash import Dash, dcc, html, Input, Output\n",
    "import plotly.express as px\n",
    "\n",
    "app = Dash(__name__)\n",
    "\n",
    "\n",
    "app.layout = html.Div([\n",
    "    html.H4('Stock price analysis'),\n",
    "    dcc.Graph(id=\"time-series-chart\"),\n",
    "    html.P(\"Select stock:\"),\n",
    "    dcc.Dropdown(\n",
    "        id=\"ticker\",\n",
    "        options=ticker_symbols,\n",
    "        value=\"AAPL\",\n",
    "        clearable=False,\n",
    "    ),\n",
    "])\n",
    "\n",
    "\n",
    "@app.callback(\n",
    "    Output(\"time-series-chart\", \"figure\"), \n",
    "    Input(\"ticker\", \"value\"))\n",
    "\n",
    "\n",
    "def display_time_series(ticker):\n",
    "    df = pd.DataFrame()\n",
    "    df['MA(50)'] = sma_60[ticker]\n",
    "    df[ticker] = price_df[ticker]\n",
    "\n",
    "    df = df.dropna()\n",
    "    fig = px.line(df)\n",
    "    return fig\n",
    "\n",
    "\n",
    "app.run_server(debug=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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