Combination_MA_RSI.ipynb

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            "(246, 7)\n"
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              "                   Open         High          Low        Close    Adj Close  \\\n",
              "Date                                                                          \n",
              "2019-03-22  1150.000000  1153.500000  1135.400024  1138.074951  1128.533447   \n",
              "2019-03-25  1130.000000  1143.925049  1126.500000  1140.650024  1131.087036   \n",
              "2019-03-26  1137.949951  1157.500000  1136.300049  1155.675049  1145.985962   \n",
              "2019-03-27  1159.275024  1164.025024  1139.525024  1149.724976  1140.085938   \n",
              "2019-03-28  1149.400024  1162.500000  1143.925049  1151.400024  1141.746826   \n",
              "\n",
              "              Volume  \n",
              "Date                  \n",
              "2019-03-22  15201940  \n",
              "2019-03-25   4599630  \n",
              "2019-03-26   5893424  \n",
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          },
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        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from matplotlib import pyplot as plt\n",
        "import seaborn as sns\n",
        "#importing required libraries\n",
        "hdfc=pd.read_csv('/content/HDFCBANK.NS.csv')\n",
        "print(hdfc.shape)\n",
        "\n",
        "hdfc.index = hdfc[\"Date\"].apply(lambda x: pd.Timestamp(x))\n",
        "hdfc.drop(\"Date\", axis=1, inplace=True)\n",
        "\n",
        "hdfc.tail()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install yfinance\n",
        "!pip install ta"
      ],
      "metadata": {
        "id": "Ah8vVg-GtnBb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz \n",
        "!tar xvzf ta-lib-0.4.0-src.tar.gz\n",
        "import os\n",
        "os.chdir('ta-lib') # Can't use !cd in co-lab\n",
        "!./configure --prefix=/usr\n",
        "!make\n",
        "!make install\n",
        "os.chdir('../')\n",
        "!pip install TA-Lib"
      ],
      "metadata": {
        "id": "DEZGTyFnty5F"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Import talib\n",
        "import yfinance as yf\n",
        "import talib"
      ],
      "metadata": {
        "id": "yINKOV5mt2jF"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def rsi(df, periods = 14, ema = True):\n",
        "    \"\"\"\n",
        "    Returns a pd.Series with the relative strength index.\n",
        "    \"\"\"\n",
        "    close_delta = df['Adj Close'].diff()\n",
        "\n",
        "    # Make two series: one for lower closes and one for higher closes\n",
        "    up = close_delta.clip(lower=0)\n",
        "    down = -1 * close_delta.clip(upper=0)\n",
        "    \n",
        "    if ema == True:\n",
        "\t    # Use exponential moving average\n",
        "        ma_up = up.ewm(com = periods - 1, adjust=True, min_periods = periods).mean()\n",
        "        ma_down = down.ewm(com = periods - 1, adjust=True, min_periods = periods).mean()\n",
        "    else:\n",
        "        # Use simple moving average\n",
        "        ma_up = up.rolling(window = periods, adjust=False).mean()\n",
        "        ma_down = down.rolling(window = periods, adjust=False).mean()\n",
        "        \n",
        "    rsi = ma_up / ma_down\n",
        "    rsi = 100 - (100/(1 + rsi))\n",
        "    df[\"rsi\"] = rsi\n",
        "    return rsi"
      ],
      "metadata": {
        "id": "IWXAv1DluvDF"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "hdfc['200MA'] = hdfc[\"Adj Close\"].rolling(window = 14).mean()\n",
        "rsi(hdfc)\n",
        "\n",
        "hdfc.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
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        "id": "ZvlXZ-SIuUbK",
        "outputId": "f618da58-dc78-4797-8366-fa5380e55c2a"
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      "execution_count": 27,
      "outputs": [
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              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2018-04-02  945.250000  967.875000  945.250000  965.599976  951.427673   \n",
              "2018-04-03  961.974976  962.849976  955.500000  957.950012  943.889954   \n",
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              "\n",
              "             Volume  200MA  rsi  \n",
              "Date                             \n",
              "2018-04-02  2298184    NaN  NaN  \n",
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              "          const element = document.querySelector('#df-e19d4f19-f130-4d03-afe1-772b7cf561ef');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "hdfc = hdfc.iloc[14:, :]\n",
        "hdfc.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "GQM7lAHtwllE",
        "outputId": "5e66ffa6-5532-48bf-8186-1ffc963da391"
      },
      "execution_count": 28,
      "outputs": [
        {
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              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2018-04-20  970.500000  980.500000  966.075012  977.950012  963.596436   \n",
              "2018-04-23  989.500000  989.500000  930.150024  967.875000  953.669312   \n",
              "2018-04-24  967.500000  974.025024  963.000000  967.500000  953.299744   \n",
              "2018-04-25  963.950012  969.000000  956.000000  960.375000  946.279358   \n",
              "2018-04-26  958.400024  969.599976  955.625000  965.125000  950.959595   \n",
              "\n",
              "             Volume       200MA        rsi  \n",
              "Date                                        \n",
              "2018-04-20  4680690  949.502760  61.029942  \n",
              "2018-04-23  7652310  950.201285  51.696503  \n",
              "2018-04-24  2518708  952.022369  51.381466  \n",
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    {
      "cell_type": "code",
      "source": [
        "hdfc[\"Condition\"] = 0\n",
        "for index,row in hdfc.iterrows():\n",
        "  if row[\"Adj Close\"]>row[\"200MA\"] and row[\"rsi\"]<50:  \n",
        "    hdfc.at[index,\"Condition\"] = 1\n",
        "  elif row[\"Adj Close\"]<row[\"200MA\"] and row[\"rsi\"]>50:  \n",
        "    hdfc.at[index,\"Condition\"] = -1\n",
        "  else :\n",
        "    hdfc.at[index,\"Condition\"] = 0\n",
        "\n",
        "hdfc"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
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        "id": "RQ2taQ1Mw9Th",
        "outputId": "e7f9616b-1ef0-4180-c963-a3cdd41f927e"
      },
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   Open         High          Low        Close    Adj Close  \\\n",
              "Date                                                                          \n",
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              "...                 ...          ...          ...          ...          ...   \n",
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              "\n",
              "              Volume        200MA        rsi  Connection  Condition  \\\n",
              "Date                                                                  \n",
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              "\n",
              "            No_of_stocks  \n",
              "Date                      \n",
              "2018-04-20             0  \n",
              "2018-04-23             0  \n",
              "2018-04-24             0  \n",
              "2018-04-25             0  \n",
              "2018-04-26             0  \n",
              "...                  ...  \n",
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              "      <td>1164.025024</td>\n",
              "      <td>1139.525024</td>\n",
              "      <td>1149.724976</td>\n",
              "      <td>1140.085938</td>\n",
              "      <td>6942650</td>\n",
              "      <td>1106.887983</td>\n",
              "      <td>72.428376</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-03-28</th>\n",
              "      <td>1149.400024</td>\n",
              "      <td>1162.500000</td>\n",
              "      <td>1143.925049</td>\n",
              "      <td>1151.400024</td>\n",
              "      <td>1141.746826</td>\n",
              "      <td>9777164</td>\n",
              "      <td>1113.131627</td>\n",
              "      <td>72.829205</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>232 rows × 11 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-357fcafc-cc23-47dd-954e-87bc8e586bce')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
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              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-357fcafc-cc23-47dd-954e-87bc8e586bce button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-357fcafc-cc23-47dd-954e-87bc8e586bce');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import math\n",
        "initial_amt = 5000\n",
        "current_amt = 5000\n",
        "hdfc[\"No_of_stocks\"] = 0\n",
        "prev_no_of_stock = 0\n",
        "\n",
        "for index,row in hdfc.iterrows():\n",
        "  if row[\"Condition\"] == 1:\n",
        "    if current_amt > row[\"Adj Close\"]:\n",
        "      hdfc.at[index,\"No_of_stocks\"] = math.floor(current_amt/row[\"Adj Close\"])\n",
        "      prev_no_of_stock = hdfc.at[index,\"No_of_stocks\"]\n",
        "      current_amt = current_amt - (hdfc.at[index,\"No_of_stocks\"]*hdfc.at[index,\"Adj Close\"])\n",
        "      print(current_amt)\n",
        "\n",
        "    else:\n",
        "      row[\"No_of_stocks\"] = prev_no_of_stock\n",
        "\n",
        "  elif row[\"Condition\"] == -1:\n",
        "    if prev_no_of_stock > 0:\n",
        "      current_amt = current_amt + (prev_no_of_stock*hdfc.at[index,\"Adj Close\"])\n",
        "      print(current_amt)\n",
        "      hdfc.at[index,\"No_of_stocks\"] = 0\n",
        "      prev_no_of_stock = 0\n",
        "\n",
        "    else:\n",
        "      row[\"No_of_stocks\"] = 0\n",
        "\n",
        "  else:\n",
        "    hdfc.at[index,\"No_of_stocks\"] = prev_no_of_stock\n",
        "\n",
        "\n",
        "print(current_amt)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S84UeUsJ1JQs",
        "outputId": "ad7af538-88bd-46af-de97-398e9c0846c0"
      },
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "26.920774999999594\n",
            "5132.628479999999\n",
            "966.5518199999997\n",
            "5152.460512\n",
            "5152.460512\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "hdfc.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "u2XsItcnBssn",
        "outputId": "22429089-f0cb-43b2-fcda-1f69b3fc2a62"
      },
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2018-04-20  970.500000  980.500000  966.075012  977.950012  963.596436   \n",
              "2018-04-23  989.500000  989.500000  930.150024  967.875000  953.669312   \n",
              "2018-04-24  967.500000  974.025024  963.000000  967.500000  953.299744   \n",
              "2018-04-25  963.950012  969.000000  956.000000  960.375000  946.279358   \n",
              "2018-04-26  958.400024  969.599976  955.625000  965.125000  950.959595   \n",
              "\n",
              "             Volume       200MA        rsi  Connection  Condition  \\\n",
              "Date                                                                \n",
              "2018-04-20  4680690  949.502760  61.029942           0          0   \n",
              "2018-04-23  7652310  950.201285  51.696503           0          0   \n",
              "2018-04-24  2518708  952.022369  51.381466           0          0   \n",
              "2018-04-25  2010296  952.439370  45.685944           0          0   \n",
              "2018-04-26  3923740  952.680420  49.689767           0          0   \n",
              "\n",
              "            No_of_stocks  \n",
              "Date                      \n",
              "2018-04-20             0  \n",
              "2018-04-23             0  \n",
              "2018-04-24             0  \n",
              "2018-04-25             0  \n",
              "2018-04-26             0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c8857db1-e2c8-457c-a20d-28729a3f4892\">\n",
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>Open</th>\n",
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              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>200MA</th>\n",
              "      <th>rsi</th>\n",
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              "      <th>Condition</th>\n",
              "      <th>No_of_stocks</th>\n",
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              "      <th>Date</th>\n",
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              "      <th>2018-04-20</th>\n",
              "      <td>970.500000</td>\n",
              "      <td>980.500000</td>\n",
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              "      <th>2018-04-24</th>\n",
              "      <td>967.500000</td>\n",
              "      <td>974.025024</td>\n",
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              "      <td>967.500000</td>\n",
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              "      <th>2018-04-25</th>\n",
              "      <td>963.950012</td>\n",
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              "      <th>2018-04-26</th>\n",
              "      <td>958.400024</td>\n",
              "      <td>969.599976</td>\n",
              "      <td>955.625000</td>\n",
              "      <td>965.125000</td>\n",
              "      <td>950.959595</td>\n",
              "      <td>3923740</td>\n",
              "      <td>952.680420</td>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      height: 32px;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c8857db1-e2c8-457c-a20d-28729a3f4892 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c8857db1-e2c8-457c-a20d-28729a3f4892');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "startidx = 0\n",
        "endidx = len(hdfc)\n",
        "      \n",
        "dates = hdfc.index\n",
        "close = hdfc['Adj Close']\n",
        "stocks = hdfc[\"No_of_stocks\"]\n",
        "condition = hdfc[\"Condition\"]"
      ],
      "metadata": {
        "id": "Z3ZisdUe4QPH"
      },
      "execution_count": 105,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.title(\"HDFC with number of shares held in a year\")\n",
        "plt.plot(dates,stocks)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        },
        "id": "KU356YOqBDh4",
        "outputId": "da2c1259-8102-4926-d850-4d55e5d7abb8"
      },
      "execution_count": 107,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Total profit made = Rs \" ,(current_amt - initial_amt))\n",
        "print(\"Percentage of profit = \",((current_amt-initial_amt)/initial_amt)*100, \"%\" )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XDW_R-wcEXwZ",
        "outputId": "5e9e7660-c6cc-4e13-badf-1db2e0bc8e87"
      },
      "execution_count": 113,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Total profit made = Rs  152.46051199999965\n",
            "Percentage of profit =  3.0492102399999927 %\n"
          ]
        }
      ]
    }
  ]
}