PROBLEM_STATEMENT -1.ipynb

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   "source": [
    "# PROBLEM STATEMENT -1 :-\n",
    "\n",
    "Go through www.nseindia.com and derive the following data about the input stock-list.\n",
    "\n",
    "Data required: Open, High, Low, Close, Volume, Delivery Data, Delivery Percentage\n",
    "Input stock-list: RELIANCE, HDFCBANK, ADANIPORTS, ITC, SBI, IOC, RBLBANK, SBI\n",
    "\n",
    "Use necessary libraries to present the data obtained in a user-readable format.\n",
    "The code must include one function which takes the stock as input and return the data required in the user-readable format.\n",
    "\n",
    "Sample function definition-\n",
    "def func(stocknames): # here stocknames is the list of input stocks\n",
    "\t\t< write code here >\n",
    "\treturn data_required\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# APPROACH :-\n",
    "\n",
    "I have imported NSE from python library called nsetools which provides realtime data from nse website ,and then created empty list after this defined function which take argument as stock name then provides data required ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Delivery Data</th>\n",
       "      <th>Delivery Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>reliance</td>\n",
       "      <td>1929.80</td>\n",
       "      <td>1966.25</td>\n",
       "      <td>1930.05</td>\n",
       "      <td>1954.90</td>\n",
       "      <td>9114939.0</td>\n",
       "      <td>3073957.0</td>\n",
       "      <td>33.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>hdfcbank</td>\n",
       "      <td>1440.85</td>\n",
       "      <td>1449.00</td>\n",
       "      <td>1425.50</td>\n",
       "      <td>1433.30</td>\n",
       "      <td>8573787.0</td>\n",
       "      <td>4902182.0</td>\n",
       "      <td>57.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>adaniports</td>\n",
       "      <td>411.55</td>\n",
       "      <td>426.00</td>\n",
       "      <td>412.00</td>\n",
       "      <td>423.80</td>\n",
       "      <td>9170159.0</td>\n",
       "      <td>2295655.0</td>\n",
       "      <td>25.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>itc</td>\n",
       "      <td>193.65</td>\n",
       "      <td>196.35</td>\n",
       "      <td>192.40</td>\n",
       "      <td>194.40</td>\n",
       "      <td>15893346.0</td>\n",
       "      <td>5543840.0</td>\n",
       "      <td>34.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>sbin</td>\n",
       "      <td>244.25</td>\n",
       "      <td>248.95</td>\n",
       "      <td>244.25</td>\n",
       "      <td>248.05</td>\n",
       "      <td>37003272.0</td>\n",
       "      <td>9607134.0</td>\n",
       "      <td>25.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ioc</td>\n",
       "      <td>84.60</td>\n",
       "      <td>86.00</td>\n",
       "      <td>84.10</td>\n",
       "      <td>85.85</td>\n",
       "      <td>14386967.0</td>\n",
       "      <td>4050603.0</td>\n",
       "      <td>28.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>rblbank</td>\n",
       "      <td>223.80</td>\n",
       "      <td>227.80</td>\n",
       "      <td>220.10</td>\n",
       "      <td>225.70</td>\n",
       "      <td>12095583.0</td>\n",
       "      <td>1363814.0</td>\n",
       "      <td>11.28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Name     Open     High      Low    Close      Volume  Delivery Data  \\\n",
       "0    reliance  1929.80  1966.25  1930.05  1954.90   9114939.0      3073957.0   \n",
       "1    hdfcbank  1440.85  1449.00  1425.50  1433.30   8573787.0      4902182.0   \n",
       "2  adaniports   411.55   426.00   412.00   423.80   9170159.0      2295655.0   \n",
       "3         itc   193.65   196.35   192.40   194.40  15893346.0      5543840.0   \n",
       "4        sbin   244.25   248.95   244.25   248.05  37003272.0      9607134.0   \n",
       "5         ioc    84.60    86.00    84.10    85.85  14386967.0      4050603.0   \n",
       "6     rblbank   223.80   227.80   220.10   225.70  12095583.0      1363814.0   \n",
       "\n",
       "   Delivery Percentage  \n",
       "0                33.72  \n",
       "1                57.18  \n",
       "2                25.03  \n",
       "3                34.88  \n",
       "4                25.96  \n",
       "5                28.15  \n",
       "6                11.28  "
      ]
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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import urllib.request\n",
    "%matplotlib inline\n",
    "from urllib.request import urlopen\n",
    "from bs4 import BeautifulSoup\n",
    "from nsetools import Nse\n",
    "from pandas import DataFrame\n",
    "nse = Nse()\n",
    "\n",
    "DataRequired = []\n",
    "\n",
    "def requiredData(code):\n",
    "\n",
    "    quote = nse.get_quote(code)\n",
    "    # dictionary which store data fetches from nse\n",
    "\n",
    "    DesiredData= {}\n",
    "    # empty dictionary\n",
    "\n",
    "   # copied required data from quote\n",
    "    DesiredData['Name'] = code\n",
    "    DesiredData['Open'] = quote['basePrice']\n",
    "    DesiredData['High'] = quote['dayHigh']\n",
    "    DesiredData['Low'] = quote['dayLow']\n",
    "    DesiredData['Close'] = quote['closePrice']\n",
    "    DesiredData['Volume'] = quote['quantityTraded']\n",
    "    DesiredData['Delivery Data'] = quote['deliveryQuantity']\n",
    "    DesiredData['Delivery Percentage'] = quote['deliveryToTradedQuantity']\n",
    "    # appended dictionary to the list\n",
    "    DataRequired.append(DesiredData)\n",
    "\n",
    "\n",
    "requiredData('reliance')\n",
    "requiredData('hdfcbank')\n",
    "requiredData('adaniports')\n",
    "requiredData('itc')\n",
    "requiredData('sbin')\n",
    "requiredData('ioc')\n",
    "requiredData('rblbank')\n",
    "# passing the argument to function\n",
    "\n",
    "#print(DataRequired) \n",
    "\n",
    "\n",
    "df = pd.DataFrame(DataRequired)\n",
    "df.head(10)"
   ]
  }
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