2.read_excel & plot-stock_data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import style\n",
    "style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Close5</th>\n",
       "      <th>20ma</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-12-24</th>\n",
       "      <td>284.890015</td>\n",
       "      <td>282.920013</td>\n",
       "      <td>284.690002</td>\n",
       "      <td>284.269989</td>\n",
       "      <td>12119700</td>\n",
       "      <td>283.596924</td>\n",
       "      <td>300.350006</td>\n",
       "      <td>271.432806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-26</th>\n",
       "      <td>289.980011</td>\n",
       "      <td>284.700012</td>\n",
       "      <td>284.820007</td>\n",
       "      <td>289.910004</td>\n",
       "      <td>23280300</td>\n",
       "      <td>289.223602</td>\n",
       "      <td>297.429993</td>\n",
       "      <td>272.710774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-27</th>\n",
       "      <td>293.970001</td>\n",
       "      <td>288.119995</td>\n",
       "      <td>291.119995</td>\n",
       "      <td>289.799988</td>\n",
       "      <td>36566500</td>\n",
       "      <td>289.113831</td>\n",
       "      <td>299.799988</td>\n",
       "      <td>273.806174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-30</th>\n",
       "      <td>292.690002</td>\n",
       "      <td>285.220001</td>\n",
       "      <td>289.459991</td>\n",
       "      <td>291.519989</td>\n",
       "      <td>36028600</td>\n",
       "      <td>290.829773</td>\n",
       "      <td>298.390015</td>\n",
       "      <td>275.016800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>293.679993</td>\n",
       "      <td>289.519989</td>\n",
       "      <td>289.929993</td>\n",
       "      <td>293.649994</td>\n",
       "      <td>25201400</td>\n",
       "      <td>292.954712</td>\n",
       "      <td>303.190002</td>\n",
       "      <td>276.487808</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  High         Low        Open       Close    Volume  \\\n",
       "Date                                                                   \n",
       "2019-12-24  284.890015  282.920013  284.690002  284.269989  12119700   \n",
       "2019-12-26  289.980011  284.700012  284.820007  289.910004  23280300   \n",
       "2019-12-27  293.970001  288.119995  291.119995  289.799988  36566500   \n",
       "2019-12-30  292.690002  285.220001  289.459991  291.519989  36028600   \n",
       "2019-12-31  293.679993  289.519989  289.929993  293.649994  25201400   \n",
       "\n",
       "             Adj Close      Close5        20ma  \n",
       "Date                                            \n",
       "2019-12-24  283.596924  300.350006  271.432806  \n",
       "2019-12-26  289.223602  297.429993  272.710774  \n",
       "2019-12-27  289.113831  299.799988  273.806174  \n",
       "2019-12-30  290.829773  298.390015  275.016800  \n",
       "2019-12-31  292.954712  303.190002  276.487808  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel('stock_data.xlsx', parse_dates = True, index_col = 'Date')\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2019 = df.loc['2019-01-01':'2019-12-31']\n",
    "df2019[['Close','Close5']].plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Close5</th>\n",
       "      <th>20ma</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2019-12-24</th>\n",
       "      <td>284.890015</td>\n",
       "      <td>282.920013</td>\n",
       "      <td>284.690002</td>\n",
       "      <td>284.269989</td>\n",
       "      <td>12119700</td>\n",
       "      <td>283.596924</td>\n",
       "      <td>300.350006</td>\n",
       "      <td>271.432806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-26</th>\n",
       "      <td>289.980011</td>\n",
       "      <td>284.700012</td>\n",
       "      <td>284.820007</td>\n",
       "      <td>289.910004</td>\n",
       "      <td>23280300</td>\n",
       "      <td>289.223602</td>\n",
       "      <td>297.429993</td>\n",
       "      <td>272.710774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-27</th>\n",
       "      <td>293.970001</td>\n",
       "      <td>288.119995</td>\n",
       "      <td>291.119995</td>\n",
       "      <td>289.799988</td>\n",
       "      <td>36566500</td>\n",
       "      <td>289.113831</td>\n",
       "      <td>299.799988</td>\n",
       "      <td>273.806174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-30</th>\n",
       "      <td>292.690002</td>\n",
       "      <td>285.220001</td>\n",
       "      <td>289.459991</td>\n",
       "      <td>291.519989</td>\n",
       "      <td>36028600</td>\n",
       "      <td>290.829773</td>\n",
       "      <td>298.390015</td>\n",
       "      <td>275.016800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>293.679993</td>\n",
       "      <td>289.519989</td>\n",
       "      <td>289.929993</td>\n",
       "      <td>293.649994</td>\n",
       "      <td>25201400</td>\n",
       "      <td>292.954712</td>\n",
       "      <td>303.190002</td>\n",
       "      <td>276.487808</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  High         Low        Open       Close    Volume  \\\n",
       "Date                                                                   \n",
       "2019-12-24  284.890015  282.920013  284.690002  284.269989  12119700   \n",
       "2019-12-26  289.980011  284.700012  284.820007  289.910004  23280300   \n",
       "2019-12-27  293.970001  288.119995  291.119995  289.799988  36566500   \n",
       "2019-12-30  292.690002  285.220001  289.459991  291.519989  36028600   \n",
       "2019-12-31  293.679993  289.519989  289.929993  293.649994  25201400   \n",
       "\n",
       "             Adj Close      Close5        20ma  \n",
       "Date                                            \n",
       "2019-12-24  283.596924  300.350006  271.432806  \n",
       "2019-12-26  289.223602  297.429993  272.710774  \n",
       "2019-12-27  289.113831  299.799988  273.806174  \n",
       "2019-12-30  290.829773  298.390015  275.016800  \n",
       "2019-12-31  292.954712  303.190002  276.487808  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2019.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax1 = plt.subplot2grid((6,1), (0,0), rowspan=5, colspan=1)\n",
    "ax2 = plt.subplot2grid((6,1), (5,0), rowspan=5, colspan=1, sharex=ax1)\n",
    "\n",
    "ax1.plot(df2019.index, df2019['Adj Close'])\n",
    "ax1.plot(df2019.index, df2019['20ma'])\n",
    "ax2.bar(df2019.index, df2019['Volume'])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
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