ticker-report.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f40b16c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import date, timedelta\n",
    "import yfinance as yf\n",
    "import mercury as mr\n",
    "import pandas as pd\n",
    "import mplfinance as mpf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6ef35b5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/mercury+json": "{\n    \"widget\": \"App\",\n    \"title\": \"Ticker Report\",\n    \"description\": \"Report financial data for selected ticker\",\n    \"show_code\": false,\n    \"show_prompt\": false,\n    \"output\": \"app\",\n    \"schedule\": \"\",\n    \"notify\": \"{}\",\n    \"continuous_update\": true,\n    \"static_notebook\": false,\n    \"show_sidebar\": true,\n    \"full_screen\": true,\n    \"allow_download\": true,\n    \"stop_on_error\": false,\n    \"model_id\": \"mercury-app\",\n    \"code_uid\": \"App.0.40.25.1-rand8403ae9f\"\n}",
      "text/html": [
       "<h3>Mercury Application</h3><small>This output won't appear in the web app.</small>"
      ],
      "text/plain": [
       "mercury.App"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "app = mr.App(title=\"Ticker Report\", description=\"Report financial data for selected ticker\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8be2ae07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/mercury+json": "{\n    \"widget\": \"Text\",\n    \"value\": \"META\",\n    \"rows\": 1,\n    \"label\": \"Ticker\",\n    \"model_id\": \"a5a58e86a09d456b893f2ccd7702026a\",\n    \"code_uid\": \"Text.0.40.15.1-randbedb008d\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a5a58e86a09d456b893f2ccd7702026a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "mercury.Text"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ticker = mr.Text(label=\"Ticker\", value=\"META\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "943392a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/mercury+json": "{\n    \"widget\": \"Slider\",\n    \"value\": 52,\n    \"min\": 4,\n    \"max\": 260,\n    \"step\": 1,\n    \"label\": \"Weeks\",\n    \"model_id\": \"c1f0b4919aa64e7881436efc45f066c2\",\n    \"code_uid\": \"Slider.0.40.36.1-rand8e2809c6\",\n    \"url_key\": \"\",\n    \"disabled\": false,\n    \"hidden\": false\n}",
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c1f0b4919aa64e7881436efc45f066c2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "mercury.Slider"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weeks = mr.Slider(label=\"Weeks\", value=52, min=4, max=260)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "2a2972d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "start = date.today() - timedelta(weeks.value*7)\n",
    "end = date.today() + timedelta(2)\n",
    "df = pd.DataFrame(yf.download(ticker.value, start=start, end=end, progress=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "791e456b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "343"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(df.High.max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "9730add4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style scoped>\n",
       "        .numberbox-container {\n",
       "        width: 100%;\n",
       "        display: flex;\n",
       "        flex-direction: row;\n",
       "        }\n",
       "        @media (max-width: 800px) {\n",
       "        .numberbox-container {\n",
       "            flex-direction: column;\n",
       "        }\n",
       "        }\n",
       "        </style><div class=\"numberbox-container\" style=\"display: flex; background: #fff;\">\n",
       "<div style=\"text-align: center; width: 100%; border: 1px solid lightgray; margin-right: 15px; margin-top: 15px; padding-top: 40px; padding-bottom: 30px; background: white; border-radius:5px\">\n",
       "  <span style=\"font-size: 4em; color: black; font-family: monospace; \">META</span>\n",
       "  \n",
       "  \n",
       "</div>\n",
       "  \n",
       "<div style=\"text-align: center; width: 100%; border: 1px solid lightgray; margin-right: 15px; margin-top: 15px; padding-top: 40px; padding-bottom: 30px; background: white; border-radius:5px\">\n",
       "  <span style=\"font-size: 4em; color: black; font-family: monospace; \">343</span>\n",
       "  \n",
       "  <span style=\"font-size: 2em; color: gray; display: block; padding-top: 20px; font-family: monospace; line-height: 1.3em;\">52-Week High</span>\n",
       "</div>\n",
       "  \n",
       "<div style=\"text-align: center; width: 100%; border: 1px solid lightgray; margin-right: 0px; margin-top: 15px; padding-top: 40px; padding-bottom: 30px; background: white; border-radius:5px\">\n",
       "  <span style=\"font-size: 4em; color: black; font-family: monospace; \">108</span>\n",
       "  \n",
       "  <span style=\"font-size: 2em; color: gray; display: block; padding-top: 20px; font-family: monospace; line-height: 1.3em;\">52-Week Low</span>\n",
       "</div>\n",
       "  </div>"
      ],
      "text/plain": [
       "<widgets.numberbox.NumberBox at 0x7f4e675e97f0>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#mr.NumberBox([\n",
    "#    mr.NumberBox(data=ticker.value),\n",
    "#    mr.NumberBox(data=df.High.max().round(1), title=f\"{weeks.value}-Week High\"),\n",
    "#    mr.NumberBox(data=df.Low.min().round(1), title=f\"{weeks.value}-Week Low\")\n",
    "#])\n",
    "mr.NumberBox([\n",
    "    mr.NumberBox(data=ticker.value),\n",
    "    mr.NumberBox(data=round(df.High.max()), title=f\"{weeks.value}-Week High\"),\n",
    "    mr.NumberBox(data=round(df.Low.min()), title=f\"{weeks.value}-Week Low\")\n",
    "])                 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "d2298ee5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1035x575 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_type = \"candle\" if weeks.value < 53 else \"line\"\n",
    "mpf.plot(df, type=plot_type, figratio=(18,10), volume=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "8ea8348e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-11-09</th>\n",
       "      <td>319.420013</td>\n",
       "      <td>324.179993</td>\n",
       "      <td>318.799988</td>\n",
       "      <td>320.549988</td>\n",
       "      <td>320.549988</td>\n",
       "      <td>16103100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-10</th>\n",
       "      <td>319.940002</td>\n",
       "      <td>329.100006</td>\n",
       "      <td>319.459991</td>\n",
       "      <td>328.769989</td>\n",
       "      <td>328.769989</td>\n",
       "      <td>19096200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-13</th>\n",
       "      <td>326.200012</td>\n",
       "      <td>332.329987</td>\n",
       "      <td>325.700012</td>\n",
       "      <td>329.190002</td>\n",
       "      <td>329.190002</td>\n",
       "      <td>16908900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-14</th>\n",
       "      <td>334.540009</td>\n",
       "      <td>338.100006</td>\n",
       "      <td>333.329987</td>\n",
       "      <td>336.309998</td>\n",
       "      <td>336.309998</td>\n",
       "      <td>17179400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-15</th>\n",
       "      <td>337.929993</td>\n",
       "      <td>338.399994</td>\n",
       "      <td>330.019989</td>\n",
       "      <td>332.709991</td>\n",
       "      <td>332.709991</td>\n",
       "      <td>14531200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-16</th>\n",
       "      <td>329.369995</td>\n",
       "      <td>334.579987</td>\n",
       "      <td>326.380005</td>\n",
       "      <td>334.190002</td>\n",
       "      <td>334.190002</td>\n",
       "      <td>18932600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-17</th>\n",
       "      <td>330.260010</td>\n",
       "      <td>335.500000</td>\n",
       "      <td>329.350006</td>\n",
       "      <td>335.040009</td>\n",
       "      <td>335.040009</td>\n",
       "      <td>14494400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-20</th>\n",
       "      <td>334.890015</td>\n",
       "      <td>341.869995</td>\n",
       "      <td>334.190002</td>\n",
       "      <td>339.970001</td>\n",
       "      <td>339.970001</td>\n",
       "      <td>16960500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-21</th>\n",
       "      <td>338.329987</td>\n",
       "      <td>339.899994</td>\n",
       "      <td>335.899994</td>\n",
       "      <td>336.980011</td>\n",
       "      <td>336.980011</td>\n",
       "      <td>12027900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-22</th>\n",
       "      <td>339.209991</td>\n",
       "      <td>342.920013</td>\n",
       "      <td>338.579987</td>\n",
       "      <td>341.489990</td>\n",
       "      <td>341.489990</td>\n",
       "      <td>10702700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Open        High         Low       Close   Adj Close  \\\n",
       "Date                                                                     \n",
       "2023-11-09  319.420013  324.179993  318.799988  320.549988  320.549988   \n",
       "2023-11-10  319.940002  329.100006  319.459991  328.769989  328.769989   \n",
       "2023-11-13  326.200012  332.329987  325.700012  329.190002  329.190002   \n",
       "2023-11-14  334.540009  338.100006  333.329987  336.309998  336.309998   \n",
       "2023-11-15  337.929993  338.399994  330.019989  332.709991  332.709991   \n",
       "2023-11-16  329.369995  334.579987  326.380005  334.190002  334.190002   \n",
       "2023-11-17  330.260010  335.500000  329.350006  335.040009  335.040009   \n",
       "2023-11-20  334.890015  341.869995  334.190002  339.970001  339.970001   \n",
       "2023-11-21  338.329987  339.899994  335.899994  336.980011  336.980011   \n",
       "2023-11-22  339.209991  342.920013  338.579987  341.489990  341.489990   \n",
       "\n",
       "              Volume  \n",
       "Date                  \n",
       "2023-11-09  16103100  \n",
       "2023-11-10  19096200  \n",
       "2023-11-13  16908900  \n",
       "2023-11-14  17179400  \n",
       "2023-11-15  14531200  \n",
       "2023-11-16  18932600  \n",
       "2023-11-17  14494400  \n",
       "2023-11-20  16960500  \n",
       "2023-11-21  12027900  \n",
       "2023-11-22  10702700  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head\n",
    "df.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5a357a0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11451ebf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85ecc8c5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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