Sentiment_Analysis.ipynb

{
  "cells": [
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      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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          "base_uri": "https://localhost:8080/"
        },
        "id": "ldQcRF92LX6L",
        "outputId": "86b6bae2-42fc-4243-a5c3-cdb003ca1122"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Collecting newsapi-python\n",
            "  Downloading newsapi_python-0.2.7-py2.py3-none-any.whl (7.9 kB)\n",
            "Requirement already satisfied: requests<3.0.0 in /usr/local/lib/python3.10/dist-packages (from newsapi-python) (2.31.0)\n",
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            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0->newsapi-python) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0->newsapi-python) (2023.11.17)\n",
            "Installing collected packages: newsapi-python\n",
            "Successfully installed newsapi-python-0.2.7\n"
          ]
        }
      ],
      "source": [
        "pip install newsapi-python"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Iwl1BIx4NPLq",
        "outputId": "9cc0f38f-ccd4-4832-c947-22b540c7c7bb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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          ]
        }
      ],
      "source": [
        "!pip install yfinance\n",
        "!pip install requests\n",
        "!pip install transformers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VvSBuDGQPrIE"
      },
      "outputs": [],
      "source": [
        "import datetime, requests, yfinance\n",
        "from newsapi import NewsApiClient\n",
        "from getpass import getpass\n",
        "\n",
        "#initialising\n",
        "newsapi = NewsApiClient(api_key='a6e2f4eb2869408ebeb2c5df7a2d9764')\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qHIUX3B2NXT8"
      },
      "outputs": [],
      "source": [
        "#to obtain news headlines\n",
        "top_headlines = newsapi.get_top_headlines(q='stocks',\n",
        "                                          qintitle='Netflix',\n",
        "                                          category='business',\n",
        "                                          language='en',\n",
        "                                          country='in')\n",
        "\n",
        "\n",
        "#top_headlines"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DccW8rCGQjW-",
        "outputId": "f2d67634-7dfe-46e6-fb64-668aa36bc73d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'status': 'ok', 'totalResults': 9, 'articles': []}"
            ]
          },
          "execution_count": 45,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# /v2/everything\n",
        "all_articles = newsapi.get_everything(q='stocks',\n",
        "                                      qintitle='netflix',\n",
        "                                      domains='bbc.co.uk,techcrunch.com',\n",
        "                                      language='en',\n",
        "                                      sort_by='relevancy',\n",
        "                                      page=2)\n",
        "all_articles\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gtMGl9DYQ9WT"
      },
      "outputs": [],
      "source": [
        "# /v2/top-headlines/sources\n",
        "sources = newsapi.get_sources()\n",
        "#sources"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "background_save": true
        },
        "id": "3JFHOgfWZacx"
      },
      "outputs": [],
      "source": [
        "# Accessing the articles\n",
        "articles = top_headlines['articles']\n",
        "#articles"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "id": "aL2cftfPRJD8",
        "outputId": "63062fb6-fa5e-4533-8240-a52ac436d028"
      },
      "outputs": [
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              "        document.querySelector('#df-8acb9796-cc66-4d3d-92b3-01f61edfb82f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                           EPS Estimate  Reported EPS  Surprise(%)\n",
              "Earnings Date                                                     \n",
              "2024-10-16 16:00:00-04:00           NaN           NaN          NaN\n",
              "2024-07-17 19:00:00-04:00           NaN           NaN          NaN\n",
              "2024-04-16 16:00:00-04:00           NaN           NaN          NaN\n",
              "2024-01-17 16:00:00-05:00          2.03           NaN          NaN\n",
              "2023-10-18 12:00:00-04:00          3.49          3.73       0.0695"
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#to fetch earnings\n",
        "\n",
        "ticker=yfinance.Ticker(\"NFLX\")\n",
        "ES= ticker.get_earnings_dates()\n",
        "ES.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "l4mr7B8_Szt4"
      },
      "outputs": [],
      "source": [
        "#ticker.news"
      ]
    },
    {
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        },
        "id": "n858bYjnS6OK",
        "outputId": "492b42d2-c19f-4309-fcfe-1fc1a45964c4"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "No model was supplied, defaulted to distilbert-base-uncased-finetuned-sst-2-english and revision af0f99b (https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english).\n",
            "Using a pipeline without specifying a model name and revision in production is not recommended.\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "6bcdbc8ebb984dfaa615f177ebb336bb",
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            "text/plain": [
              "config.json:   0%|          | 0.00/629 [00:00<?, ?B/s]"
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          "output_type": "display_data"
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        {
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              "model_id": "c4ec08b1115748319aad6cb142c7db58",
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              "version_minor": 0
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            "text/plain": [
              "model.safetensors:   0%|          | 0.00/268M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
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        {
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              "version_minor": 0
            },
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/48.0 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
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        },
        {
          "data": {
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              "model_id": "7eaf6ba1a0914189aec325553d3e22cd",
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              "version_minor": 0
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            "text/plain": [
              "vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
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        }
      ],
      "source": [
        "from transformers import pipeline\n",
        "classifier= pipeline('sentiment-analysis')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5yG6XQFNTa3y",
        "outputId": "abf3934d-83ca-4b0b-c53d-4fef98432dba"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[{'label': 'NEGATIVE', 'score': 0.9990346431732178}]"
            ]
          },
          "execution_count": 30,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#example for sentiment scores\n",
        "classifier('the fox crossed the road and got hit by a car and was injured')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AOrFxJNIZgA1",
        "outputId": "ab4598ed-03e6-4aa8-9267-381088b65960"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Gainers and Losers: 10 stocks that moved the most on December 6 - Moneycontrol',\n",
              " 'Business News at 09:30 am on 6th December 2023 - The Financial Express',\n",
              " 'Hot Stocks | Expect double-digit returns in JK Paper, Vedant Fashions, Indian Hume Pipe - Moneycontrol',\n",
              " 'Thermal power rises in Apr-Oct as demand soars | Mint - Mint',\n",
              " 'Nifty and Bank Nifty Prediction for Tomorrow, 6 December 2023 - Nifty50stocks']"
            ]
          },
          "execution_count": 59,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Extracting titles for classification\n",
        "titles_for_classification = [article['title'] for article in articles]\n",
        "titles_for_classification\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DR8ngeX_Ra3t",
        "outputId": "d613c4f8-0e9a-451c-bf8b-7cb5a7061cb0"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[{'label': 'NEGATIVE', 'score': 0.9707534909248352},\n",
              " {'label': 'POSITIVE', 'score': 0.9378536939620972},\n",
              " {'label': 'NEGATIVE', 'score': 0.9987707734107971},\n",
              " {'label': 'POSITIVE', 'score': 0.996690034866333},\n",
              " {'label': 'NEGATIVE', 'score': 0.8112667798995972}]"
            ]
          },
          "execution_count": 60,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#classifier is a function that takes text for classification\n",
        "classifier_result = classifier(titles_for_classification)\n",
        "\n",
        "#Printing the classification result\n",
        "classifier_result\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "voIByzXkUnea"
      },
      "outputs": [],
      "source": []
    }
  ],
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