Upload 2 files
Browse files- datacleaning.ipynb +1066 -0
- train_data.csv +0 -0
datacleaning.ipynb
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| 1 |
+
{
|
| 2 |
+
"cells": [
|
| 3 |
+
{
|
| 4 |
+
"cell_type": "code",
|
| 5 |
+
"execution_count": 1,
|
| 6 |
+
"metadata": {},
|
| 7 |
+
"outputs": [
|
| 8 |
+
{
|
| 9 |
+
"name": "stderr",
|
| 10 |
+
"output_type": "stream",
|
| 11 |
+
"text": [
|
| 12 |
+
"/Users/wangkaiyuan/Desktop/UPenn/Fall 2024/CIS 5190/CIS5190finalproj/.venv/lib/python3.9/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020\n",
|
| 13 |
+
" warnings.warn(\n"
|
| 14 |
+
]
|
| 15 |
+
}
|
| 16 |
+
],
|
| 17 |
+
"source": [
|
| 18 |
+
"import pandas as pd\n",
|
| 19 |
+
"import requests\n",
|
| 20 |
+
"from bs4 import BeautifulSoup"
|
| 21 |
+
]
|
| 22 |
+
},
|
| 23 |
+
{
|
| 24 |
+
"cell_type": "code",
|
| 25 |
+
"execution_count": 2,
|
| 26 |
+
"metadata": {},
|
| 27 |
+
"outputs": [
|
| 28 |
+
{
|
| 29 |
+
"data": {
|
| 30 |
+
"text/html": [
|
| 31 |
+
"<div>\n",
|
| 32 |
+
"<style scoped>\n",
|
| 33 |
+
" .dataframe tbody tr th:only-of-type {\n",
|
| 34 |
+
" vertical-align: middle;\n",
|
| 35 |
+
" }\n",
|
| 36 |
+
"\n",
|
| 37 |
+
" .dataframe tbody tr th {\n",
|
| 38 |
+
" vertical-align: top;\n",
|
| 39 |
+
" }\n",
|
| 40 |
+
"\n",
|
| 41 |
+
" .dataframe thead th {\n",
|
| 42 |
+
" text-align: right;\n",
|
| 43 |
+
" }\n",
|
| 44 |
+
"</style>\n",
|
| 45 |
+
"<table border=\"1\" class=\"dataframe\">\n",
|
| 46 |
+
" <thead>\n",
|
| 47 |
+
" <tr style=\"text-align: right;\">\n",
|
| 48 |
+
" <th></th>\n",
|
| 49 |
+
" <th>url</th>\n",
|
| 50 |
+
" </tr>\n",
|
| 51 |
+
" </thead>\n",
|
| 52 |
+
" <tbody>\n",
|
| 53 |
+
" <tr>\n",
|
| 54 |
+
" <th>0</th>\n",
|
| 55 |
+
" <td>https://www.foxnews.com/lifestyle/jack-carrs-e...</td>\n",
|
| 56 |
+
" </tr>\n",
|
| 57 |
+
" <tr>\n",
|
| 58 |
+
" <th>1</th>\n",
|
| 59 |
+
" <td>https://www.foxnews.com/entertainment/bruce-wi...</td>\n",
|
| 60 |
+
" </tr>\n",
|
| 61 |
+
" <tr>\n",
|
| 62 |
+
" <th>2</th>\n",
|
| 63 |
+
" <td>https://www.foxnews.com/politics/blinken-meets...</td>\n",
|
| 64 |
+
" </tr>\n",
|
| 65 |
+
" <tr>\n",
|
| 66 |
+
" <th>3</th>\n",
|
| 67 |
+
" <td>https://www.foxnews.com/entertainment/emily-bl...</td>\n",
|
| 68 |
+
" </tr>\n",
|
| 69 |
+
" <tr>\n",
|
| 70 |
+
" <th>4</th>\n",
|
| 71 |
+
" <td>https://www.foxnews.com/media/the-view-co-host...</td>\n",
|
| 72 |
+
" </tr>\n",
|
| 73 |
+
" </tbody>\n",
|
| 74 |
+
"</table>\n",
|
| 75 |
+
"</div>"
|
| 76 |
+
],
|
| 77 |
+
"text/plain": [
|
| 78 |
+
" url\n",
|
| 79 |
+
"0 https://www.foxnews.com/lifestyle/jack-carrs-e...\n",
|
| 80 |
+
"1 https://www.foxnews.com/entertainment/bruce-wi...\n",
|
| 81 |
+
"2 https://www.foxnews.com/politics/blinken-meets...\n",
|
| 82 |
+
"3 https://www.foxnews.com/entertainment/emily-bl...\n",
|
| 83 |
+
"4 https://www.foxnews.com/media/the-view-co-host..."
|
| 84 |
+
]
|
| 85 |
+
},
|
| 86 |
+
"execution_count": 2,
|
| 87 |
+
"metadata": {},
|
| 88 |
+
"output_type": "execute_result"
|
| 89 |
+
}
|
| 90 |
+
],
|
| 91 |
+
"source": [
|
| 92 |
+
"# load csv file and process the data\n",
|
| 93 |
+
"urls_df = pd.read_csv('url_only_data.csv')\n",
|
| 94 |
+
"urls_df.head()\n"
|
| 95 |
+
]
|
| 96 |
+
},
|
| 97 |
+
{
|
| 98 |
+
"cell_type": "code",
|
| 99 |
+
"execution_count": 3,
|
| 100 |
+
"metadata": {},
|
| 101 |
+
"outputs": [],
|
| 102 |
+
"source": [
|
| 103 |
+
"# define the function to fetch the title of the news article\n",
|
| 104 |
+
"def fetch_title(url):\n",
|
| 105 |
+
" try:\n",
|
| 106 |
+
" response = requests.get(url)\n",
|
| 107 |
+
" if response.status_code != 200:\n",
|
| 108 |
+
" return f\"Error: {response.status_code}\"\n",
|
| 109 |
+
" soup = BeautifulSoup(response.text, \"html.parser\")\n",
|
| 110 |
+
" # Try to find the headline based on a common class used on Fox News pages\n",
|
| 111 |
+
" title = soup.find(\"h1\", class_=\"headline speakable\")\n",
|
| 112 |
+
" return title.text.strip() if title else \"Title not found\"\n",
|
| 113 |
+
" except Exception as e:\n",
|
| 114 |
+
" return f\"Error: {e}\"\n",
|
| 115 |
+
"\n",
|
| 116 |
+
"def fetch_title_altered(url):\n",
|
| 117 |
+
" try:\n",
|
| 118 |
+
" response = requests.get(url)\n",
|
| 119 |
+
" if response.status_code != 200:\n",
|
| 120 |
+
" return f\"Error: {response.status_code}\"\n",
|
| 121 |
+
" soup = BeautifulSoup(response.text, \"html.parser\")\n",
|
| 122 |
+
" # Try to find the headline based on a common class used on Fox News pages\n",
|
| 123 |
+
" title = soup.find(\"h1\")\n",
|
| 124 |
+
" return title.text.strip() if title else \"Title not found\"\n",
|
| 125 |
+
" except Exception as e:\n",
|
| 126 |
+
" return f\"Error: {e}\""
|
| 127 |
+
]
|
| 128 |
+
},
|
| 129 |
+
{
|
| 130 |
+
"cell_type": "code",
|
| 131 |
+
"execution_count": 4,
|
| 132 |
+
"metadata": {},
|
| 133 |
+
"outputs": [],
|
| 134 |
+
"source": [
|
| 135 |
+
"# remove the '.print' from the urls\n",
|
| 136 |
+
"urls_df['url'] = urls_df['url'].str.replace('.print', '', regex=False)"
|
| 137 |
+
]
|
| 138 |
+
},
|
| 139 |
+
{
|
| 140 |
+
"cell_type": "code",
|
| 141 |
+
"execution_count": 5,
|
| 142 |
+
"metadata": {},
|
| 143 |
+
"outputs": [
|
| 144 |
+
{
|
| 145 |
+
"ename": "KeyboardInterrupt",
|
| 146 |
+
"evalue": "",
|
| 147 |
+
"output_type": "error",
|
| 148 |
+
"traceback": [
|
| 149 |
+
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
| 150 |
+
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
|
| 151 |
+
"Cell \u001b[0;32mIn[5], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# fetch the title of the news article\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m urls_df[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtitle\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[43murls_df\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43murl\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfetch_title\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 152 |
+
"File \u001b[0;32m~/Desktop/UPenn/Fall 2024/CIS 5190/CIS5190finalproj/.venv/lib/python3.9/site-packages/pandas/core/series.py:4917\u001b[0m, in \u001b[0;36mSeries.apply\u001b[0;34m(self, func, convert_dtype, args, by_row, **kwargs)\u001b[0m\n\u001b[1;32m 4789\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mapply\u001b[39m(\n\u001b[1;32m 4790\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 4791\u001b[0m func: AggFuncType,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 4796\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m 4797\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m DataFrame \u001b[38;5;241m|\u001b[39m Series:\n\u001b[1;32m 4798\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 4799\u001b[0m \u001b[38;5;124;03m Invoke function on values of Series.\u001b[39;00m\n\u001b[1;32m 4800\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 4915\u001b[0m \u001b[38;5;124;03m dtype: float64\u001b[39;00m\n\u001b[1;32m 4916\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 4917\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mSeriesApply\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 4918\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4919\u001b[0m \u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4920\u001b[0m \u001b[43m \u001b[49m\u001b[43mconvert_dtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconvert_dtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4921\u001b[0m \u001b[43m \u001b[49m\u001b[43mby_row\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mby_row\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4922\u001b[0m \u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4923\u001b[0m \u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4924\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 153 |
+
"File \u001b[0;32m~/Desktop/UPenn/Fall 2024/CIS 5190/CIS5190finalproj/.venv/lib/python3.9/site-packages/pandas/core/apply.py:1427\u001b[0m, in \u001b[0;36mSeriesApply.apply\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1424\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mapply_compat()\n\u001b[1;32m 1426\u001b[0m \u001b[38;5;66;03m# self.func is Callable\u001b[39;00m\n\u001b[0;32m-> 1427\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapply_standard\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
| 154 |
+
"File \u001b[0;32m~/Desktop/UPenn/Fall 2024/CIS 5190/CIS5190finalproj/.venv/lib/python3.9/site-packages/pandas/core/apply.py:1507\u001b[0m, in \u001b[0;36mSeriesApply.apply_standard\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1501\u001b[0m \u001b[38;5;66;03m# row-wise access\u001b[39;00m\n\u001b[1;32m 1502\u001b[0m \u001b[38;5;66;03m# apply doesn't have a `na_action` keyword and for backward compat reasons\u001b[39;00m\n\u001b[1;32m 1503\u001b[0m \u001b[38;5;66;03m# we need to give `na_action=\"ignore\"` for categorical data.\u001b[39;00m\n\u001b[1;32m 1504\u001b[0m \u001b[38;5;66;03m# TODO: remove the `na_action=\"ignore\"` when that default has been changed in\u001b[39;00m\n\u001b[1;32m 1505\u001b[0m \u001b[38;5;66;03m# Categorical (GH51645).\u001b[39;00m\n\u001b[1;32m 1506\u001b[0m action \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(obj\u001b[38;5;241m.\u001b[39mdtype, CategoricalDtype) \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m-> 1507\u001b[0m mapped \u001b[38;5;241m=\u001b[39m \u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_map_values\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1508\u001b[0m \u001b[43m \u001b[49m\u001b[43mmapper\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcurried\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mna_action\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maction\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconvert\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconvert_dtype\u001b[49m\n\u001b[1;32m 1509\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1511\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(mapped) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(mapped[\u001b[38;5;241m0\u001b[39m], ABCSeries):\n\u001b[1;32m 1512\u001b[0m \u001b[38;5;66;03m# GH#43986 Need to do list(mapped) in order to get treated as nested\u001b[39;00m\n\u001b[1;32m 1513\u001b[0m \u001b[38;5;66;03m# See also GH#25959 regarding EA support\u001b[39;00m\n\u001b[1;32m 1514\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m obj\u001b[38;5;241m.\u001b[39m_constructor_expanddim(\u001b[38;5;28mlist\u001b[39m(mapped), index\u001b[38;5;241m=\u001b[39mobj\u001b[38;5;241m.\u001b[39mindex)\n",
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| 155 |
+
"File \u001b[0;32m~/Desktop/UPenn/Fall 2024/CIS 5190/CIS5190finalproj/.venv/lib/python3.9/site-packages/pandas/core/base.py:921\u001b[0m, in \u001b[0;36mIndexOpsMixin._map_values\u001b[0;34m(self, mapper, na_action, convert)\u001b[0m\n\u001b[1;32m 918\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(arr, ExtensionArray):\n\u001b[1;32m 919\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m arr\u001b[38;5;241m.\u001b[39mmap(mapper, na_action\u001b[38;5;241m=\u001b[39mna_action)\n\u001b[0;32m--> 921\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43malgorithms\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmap_array\u001b[49m\u001b[43m(\u001b[49m\u001b[43marr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmapper\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mna_action\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mna_action\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconvert\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconvert\u001b[49m\u001b[43m)\u001b[49m\n",
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| 156 |
+
"File \u001b[0;32m~/Desktop/UPenn/Fall 2024/CIS 5190/CIS5190finalproj/.venv/lib/python3.9/site-packages/pandas/core/algorithms.py:1743\u001b[0m, in \u001b[0;36mmap_array\u001b[0;34m(arr, mapper, na_action, convert)\u001b[0m\n\u001b[1;32m 1741\u001b[0m values \u001b[38;5;241m=\u001b[39m arr\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;28mobject\u001b[39m, copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 1742\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m na_action \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 1743\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmap_infer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmapper\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconvert\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconvert\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1744\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1745\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m lib\u001b[38;5;241m.\u001b[39mmap_infer_mask(\n\u001b[1;32m 1746\u001b[0m values, mapper, mask\u001b[38;5;241m=\u001b[39misna(values)\u001b[38;5;241m.\u001b[39mview(np\u001b[38;5;241m.\u001b[39muint8), convert\u001b[38;5;241m=\u001b[39mconvert\n\u001b[1;32m 1747\u001b[0m )\n",
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+
"File \u001b[0;32mlib.pyx:2972\u001b[0m, in \u001b[0;36mpandas._libs.lib.map_infer\u001b[0;34m()\u001b[0m\n",
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+
"Cell \u001b[0;32mIn[3], line 7\u001b[0m, in \u001b[0;36mfetch_title\u001b[0;34m(url)\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m response\u001b[38;5;241m.\u001b[39mstatus_code \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m200\u001b[39m:\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mresponse\u001b[38;5;241m.\u001b[39mstatus_code\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 7\u001b[0m soup \u001b[38;5;241m=\u001b[39m \u001b[43mBeautifulSoup\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtext\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mhtml.parser\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[38;5;66;03m# Try to find the headline based on a common class used on Fox News pages\u001b[39;00m\n\u001b[1;32m 9\u001b[0m title \u001b[38;5;241m=\u001b[39m soup\u001b[38;5;241m.\u001b[39mfind(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mh1\u001b[39m\u001b[38;5;124m\"\u001b[39m, class_\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mheadline speakable\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
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| 159 |
+
"File \u001b[0;32m~/Desktop/UPenn/Fall 2024/CIS 5190/CIS5190finalproj/.venv/lib/python3.9/site-packages/bs4/__init__.py:335\u001b[0m, in \u001b[0;36mBeautifulSoup.__init__\u001b[0;34m(self, markup, features, builder, parse_only, from_encoding, exclude_encodings, element_classes, **kwargs)\u001b[0m\n\u001b[1;32m 333\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbuilder\u001b[38;5;241m.\u001b[39minitialize_soup(\u001b[38;5;28mself\u001b[39m)\n\u001b[1;32m 334\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 335\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_feed\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 336\u001b[0m success \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m 337\u001b[0m \u001b[38;5;28;01mbreak\u001b[39;00m\n",
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| 160 |
+
"File \u001b[0;32m~/Desktop/UPenn/Fall 2024/CIS 5190/CIS5190finalproj/.venv/lib/python3.9/site-packages/bs4/__init__.py:478\u001b[0m, in \u001b[0;36mBeautifulSoup._feed\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 475\u001b[0m \u001b[38;5;66;03m# Convert the document to Unicode.\u001b[39;00m\n\u001b[1;32m 476\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbuilder\u001b[38;5;241m.\u001b[39mreset()\n\u001b[0;32m--> 478\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuilder\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfeed\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmarkup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 479\u001b[0m \u001b[38;5;66;03m# Close out any unfinished strings and close all the open tags.\u001b[39;00m\n\u001b[1;32m 480\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mendData()\n",
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| 161 |
+
"File \u001b[0;32m~/Desktop/UPenn/Fall 2024/CIS 5190/CIS5190finalproj/.venv/lib/python3.9/site-packages/bs4/builder/_htmlparser.py:380\u001b[0m, in \u001b[0;36mHTMLParserTreeBuilder.feed\u001b[0;34m(self, markup)\u001b[0m\n\u001b[1;32m 378\u001b[0m parser\u001b[38;5;241m.\u001b[39msoup \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msoup\n\u001b[1;32m 379\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 380\u001b[0m \u001b[43mparser\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfeed\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmarkup\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 381\u001b[0m parser\u001b[38;5;241m.\u001b[39mclose()\n\u001b[1;32m 382\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 383\u001b[0m \u001b[38;5;66;03m# html.parser raises AssertionError in rare cases to\u001b[39;00m\n\u001b[1;32m 384\u001b[0m \u001b[38;5;66;03m# indicate a fatal problem with the markup, especially\u001b[39;00m\n\u001b[1;32m 385\u001b[0m \u001b[38;5;66;03m# when there's an error in the doctype declaration.\u001b[39;00m\n",
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+
"File \u001b[0;32m/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/html/parser.py:110\u001b[0m, in \u001b[0;36mHTMLParser.feed\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 104\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Feed data to the parser.\u001b[39;00m\n\u001b[1;32m 105\u001b[0m \n\u001b[1;32m 106\u001b[0m \u001b[38;5;124;03mCall this as often as you want, with as little or as much text\u001b[39;00m\n\u001b[1;32m 107\u001b[0m \u001b[38;5;124;03mas you want (may include '\\n').\u001b[39;00m\n\u001b[1;32m 108\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 109\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrawdata \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrawdata \u001b[38;5;241m+\u001b[39m data\n\u001b[0;32m--> 110\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgoahead\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n",
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+
"File \u001b[0;32m/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/html/parser.py:172\u001b[0m, in \u001b[0;36mHTMLParser.goahead\u001b[0;34m(self, end)\u001b[0m\n\u001b[1;32m 170\u001b[0m k \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparse_starttag(i)\n\u001b[1;32m 171\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m startswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m</\u001b[39m\u001b[38;5;124m\"\u001b[39m, i):\n\u001b[0;32m--> 172\u001b[0m k \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparse_endtag\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 173\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m startswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m<!--\u001b[39m\u001b[38;5;124m\"\u001b[39m, i):\n\u001b[1;32m 174\u001b[0m k \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparse_comment(i)\n",
|
| 164 |
+
"File \u001b[0;32m/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/html/parser.py:392\u001b[0m, in \u001b[0;36mHTMLParser.parse_endtag\u001b[0;34m(self, i)\u001b[0m\n\u001b[1;32m 390\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 391\u001b[0m gtpos \u001b[38;5;241m=\u001b[39m match\u001b[38;5;241m.\u001b[39mend()\n\u001b[0;32m--> 392\u001b[0m match \u001b[38;5;241m=\u001b[39m \u001b[43mendtagfind\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmatch\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrawdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# </ + tag + >\u001b[39;00m\n\u001b[1;32m 393\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m match:\n\u001b[1;32m 394\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcdata_elem \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
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+
"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
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+
]
|
| 167 |
+
}
|
| 168 |
+
],
|
| 169 |
+
"source": [
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| 170 |
+
"# fetch the title of the news article\n",
|
| 171 |
+
"urls_df['title'] = urls_df['url'].apply(fetch_title)"
|
| 172 |
+
]
|
| 173 |
+
},
|
| 174 |
+
{
|
| 175 |
+
"cell_type": "code",
|
| 176 |
+
"execution_count": null,
|
| 177 |
+
"metadata": {},
|
| 178 |
+
"outputs": [
|
| 179 |
+
{
|
| 180 |
+
"name": "stderr",
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| 181 |
+
"output_type": "stream",
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| 182 |
+
"text": [
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| 183 |
+
"/var/folders/y8/__mdhnk12l9d1zxvj_wms9h00000gn/T/ipykernel_38707/2702622145.py:3: SettingWithCopyWarning: \n",
|
| 184 |
+
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
|
| 185 |
+
"Try using .loc[row_indexer,col_indexer] = value instead\n",
|
| 186 |
+
"\n",
|
| 187 |
+
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
|
| 188 |
+
" not_found['title'] = not_found['url'].apply(fetch_title_altered)\n"
|
| 189 |
+
]
|
| 190 |
+
}
|
| 191 |
+
],
|
| 192 |
+
"source": [
|
| 193 |
+
"# fetch the title of the news article that was not found\n",
|
| 194 |
+
"not_found = urls_df[urls_df['title'] == 'Title not found']\n",
|
| 195 |
+
"not_found['title'] = not_found['url'].apply(fetch_title_altered)\n",
|
| 196 |
+
"\n"
|
| 197 |
+
]
|
| 198 |
+
},
|
| 199 |
+
{
|
| 200 |
+
"cell_type": "code",
|
| 201 |
+
"execution_count": 72,
|
| 202 |
+
"metadata": {},
|
| 203 |
+
"outputs": [],
|
| 204 |
+
"source": [
|
| 205 |
+
"urls_df.update(not_found)"
|
| 206 |
+
]
|
| 207 |
+
},
|
| 208 |
+
{
|
| 209 |
+
"cell_type": "code",
|
| 210 |
+
"execution_count": 75,
|
| 211 |
+
"metadata": {},
|
| 212 |
+
"outputs": [],
|
| 213 |
+
"source": [
|
| 214 |
+
"# remove duplicates titles\n",
|
| 215 |
+
"urls_df.drop_duplicates(subset='title', keep='first', inplace=True)"
|
| 216 |
+
]
|
| 217 |
+
},
|
| 218 |
+
{
|
| 219 |
+
"cell_type": "code",
|
| 220 |
+
"execution_count": 84,
|
| 221 |
+
"metadata": {},
|
| 222 |
+
"outputs": [],
|
| 223 |
+
"source": [
|
| 224 |
+
"# convert title to string\n",
|
| 225 |
+
"urls_df['title'] = urls_df['title'].astype(str)"
|
| 226 |
+
]
|
| 227 |
+
},
|
| 228 |
+
{
|
| 229 |
+
"cell_type": "code",
|
| 230 |
+
"execution_count": null,
|
| 231 |
+
"metadata": {},
|
| 232 |
+
"outputs": [],
|
| 233 |
+
"source": [
|
| 234 |
+
"# remove the \" \"\" \" from the titles\n",
|
| 235 |
+
"urls_df['title'] = urls_df['title'].str.strip('\"')"
|
| 236 |
+
]
|
| 237 |
+
},
|
| 238 |
+
{
|
| 239 |
+
"cell_type": "code",
|
| 240 |
+
"execution_count": 93,
|
| 241 |
+
"metadata": {},
|
| 242 |
+
"outputs": [],
|
| 243 |
+
"source": [
|
| 244 |
+
"# save the data to a new csv file\n",
|
| 245 |
+
"urls_df.to_csv('fetched_headlines.csv', index=False)"
|
| 246 |
+
]
|
| 247 |
+
},
|
| 248 |
+
{
|
| 249 |
+
"cell_type": "code",
|
| 250 |
+
"execution_count": 104,
|
| 251 |
+
"metadata": {},
|
| 252 |
+
"outputs": [],
|
| 253 |
+
"source": [
|
| 254 |
+
"# Split the data into training and testing sets\n",
|
| 255 |
+
"from sklearn.model_selection import train_test_split\n",
|
| 256 |
+
"from sklearn.feature_extraction.text import TfidfVectorizer\n",
|
| 257 |
+
"from sklearn.linear_model import LogisticRegression\n",
|
| 258 |
+
"from sklearn.metrics import classification_report\n",
|
| 259 |
+
"from sklearn.metrics import accuracy_score\n"
|
| 260 |
+
]
|
| 261 |
+
},
|
| 262 |
+
{
|
| 263 |
+
"cell_type": "code",
|
| 264 |
+
"execution_count": 91,
|
| 265 |
+
"metadata": {},
|
| 266 |
+
"outputs": [],
|
| 267 |
+
"source": [
|
| 268 |
+
"# Convert the labels to binary values (0 for ’FoxNews’, 1 for ’NBC’)\n",
|
| 269 |
+
"urls_df['label'] = urls_df['url'].apply(lambda x: 0 if 'foxnews.com' in x else 1 if 'nbcnews.com' in x else None)"
|
| 270 |
+
]
|
| 271 |
+
},
|
| 272 |
+
{
|
| 273 |
+
"cell_type": "code",
|
| 274 |
+
"execution_count": 97,
|
| 275 |
+
"metadata": {},
|
| 276 |
+
"outputs": [],
|
| 277 |
+
"source": [
|
| 278 |
+
"# split the data into training and testing sets\n",
|
| 279 |
+
"X_train, X_test, y_train, y_test = train_test_split(urls_df['title'], urls_df['label'], test_size=0.2, random_state=42)\n"
|
| 280 |
+
]
|
| 281 |
+
},
|
| 282 |
+
{
|
| 283 |
+
"cell_type": "code",
|
| 284 |
+
"execution_count": 98,
|
| 285 |
+
"metadata": {},
|
| 286 |
+
"outputs": [],
|
| 287 |
+
"source": [
|
| 288 |
+
"# Convert the text data to TF-IDF features\n",
|
| 289 |
+
"vectorizer = TfidfVectorizer(stop_words='english', max_features=100)\n",
|
| 290 |
+
"X_train_tfidf = vectorizer.fit_transform(X_train)\n",
|
| 291 |
+
"X_test_tfidf = vectorizer.transform(X_test)"
|
| 292 |
+
]
|
| 293 |
+
},
|
| 294 |
+
{
|
| 295 |
+
"cell_type": "code",
|
| 296 |
+
"execution_count": 99,
|
| 297 |
+
"metadata": {},
|
| 298 |
+
"outputs": [
|
| 299 |
+
{
|
| 300 |
+
"data": {
|
| 301 |
+
"text/html": [
|
| 302 |
+
"<style>#sk-container-id-1 {\n",
|
| 303 |
+
" /* Definition of color scheme common for light and dark mode */\n",
|
| 304 |
+
" --sklearn-color-text: black;\n",
|
| 305 |
+
" --sklearn-color-line: gray;\n",
|
| 306 |
+
" /* Definition of color scheme for unfitted estimators */\n",
|
| 307 |
+
" --sklearn-color-unfitted-level-0: #fff5e6;\n",
|
| 308 |
+
" --sklearn-color-unfitted-level-1: #f6e4d2;\n",
|
| 309 |
+
" --sklearn-color-unfitted-level-2: #ffe0b3;\n",
|
| 310 |
+
" --sklearn-color-unfitted-level-3: chocolate;\n",
|
| 311 |
+
" /* Definition of color scheme for fitted estimators */\n",
|
| 312 |
+
" --sklearn-color-fitted-level-0: #f0f8ff;\n",
|
| 313 |
+
" --sklearn-color-fitted-level-1: #d4ebff;\n",
|
| 314 |
+
" --sklearn-color-fitted-level-2: #b3dbfd;\n",
|
| 315 |
+
" --sklearn-color-fitted-level-3: cornflowerblue;\n",
|
| 316 |
+
"\n",
|
| 317 |
+
" /* Specific color for light theme */\n",
|
| 318 |
+
" --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
|
| 319 |
+
" --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
|
| 320 |
+
" --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
|
| 321 |
+
" --sklearn-color-icon: #696969;\n",
|
| 322 |
+
"\n",
|
| 323 |
+
" @media (prefers-color-scheme: dark) {\n",
|
| 324 |
+
" /* Redefinition of color scheme for dark theme */\n",
|
| 325 |
+
" --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
|
| 326 |
+
" --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
|
| 327 |
+
" --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
|
| 328 |
+
" --sklearn-color-icon: #878787;\n",
|
| 329 |
+
" }\n",
|
| 330 |
+
"}\n",
|
| 331 |
+
"\n",
|
| 332 |
+
"#sk-container-id-1 {\n",
|
| 333 |
+
" color: var(--sklearn-color-text);\n",
|
| 334 |
+
"}\n",
|
| 335 |
+
"\n",
|
| 336 |
+
"#sk-container-id-1 pre {\n",
|
| 337 |
+
" padding: 0;\n",
|
| 338 |
+
"}\n",
|
| 339 |
+
"\n",
|
| 340 |
+
"#sk-container-id-1 input.sk-hidden--visually {\n",
|
| 341 |
+
" border: 0;\n",
|
| 342 |
+
" clip: rect(1px 1px 1px 1px);\n",
|
| 343 |
+
" clip: rect(1px, 1px, 1px, 1px);\n",
|
| 344 |
+
" height: 1px;\n",
|
| 345 |
+
" margin: -1px;\n",
|
| 346 |
+
" overflow: hidden;\n",
|
| 347 |
+
" padding: 0;\n",
|
| 348 |
+
" position: absolute;\n",
|
| 349 |
+
" width: 1px;\n",
|
| 350 |
+
"}\n",
|
| 351 |
+
"\n",
|
| 352 |
+
"#sk-container-id-1 div.sk-dashed-wrapped {\n",
|
| 353 |
+
" border: 1px dashed var(--sklearn-color-line);\n",
|
| 354 |
+
" margin: 0 0.4em 0.5em 0.4em;\n",
|
| 355 |
+
" box-sizing: border-box;\n",
|
| 356 |
+
" padding-bottom: 0.4em;\n",
|
| 357 |
+
" background-color: var(--sklearn-color-background);\n",
|
| 358 |
+
"}\n",
|
| 359 |
+
"\n",
|
| 360 |
+
"#sk-container-id-1 div.sk-container {\n",
|
| 361 |
+
" /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
|
| 362 |
+
" but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
|
| 363 |
+
" so we also need the `!important` here to be able to override the\n",
|
| 364 |
+
" default hidden behavior on the sphinx rendered scikit-learn.org.\n",
|
| 365 |
+
" See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
|
| 366 |
+
" display: inline-block !important;\n",
|
| 367 |
+
" position: relative;\n",
|
| 368 |
+
"}\n",
|
| 369 |
+
"\n",
|
| 370 |
+
"#sk-container-id-1 div.sk-text-repr-fallback {\n",
|
| 371 |
+
" display: none;\n",
|
| 372 |
+
"}\n",
|
| 373 |
+
"\n",
|
| 374 |
+
"div.sk-parallel-item,\n",
|
| 375 |
+
"div.sk-serial,\n",
|
| 376 |
+
"div.sk-item {\n",
|
| 377 |
+
" /* draw centered vertical line to link estimators */\n",
|
| 378 |
+
" background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
|
| 379 |
+
" background-size: 2px 100%;\n",
|
| 380 |
+
" background-repeat: no-repeat;\n",
|
| 381 |
+
" background-position: center center;\n",
|
| 382 |
+
"}\n",
|
| 383 |
+
"\n",
|
| 384 |
+
"/* Parallel-specific style estimator block */\n",
|
| 385 |
+
"\n",
|
| 386 |
+
"#sk-container-id-1 div.sk-parallel-item::after {\n",
|
| 387 |
+
" content: \"\";\n",
|
| 388 |
+
" width: 100%;\n",
|
| 389 |
+
" border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
|
| 390 |
+
" flex-grow: 1;\n",
|
| 391 |
+
"}\n",
|
| 392 |
+
"\n",
|
| 393 |
+
"#sk-container-id-1 div.sk-parallel {\n",
|
| 394 |
+
" display: flex;\n",
|
| 395 |
+
" align-items: stretch;\n",
|
| 396 |
+
" justify-content: center;\n",
|
| 397 |
+
" background-color: var(--sklearn-color-background);\n",
|
| 398 |
+
" position: relative;\n",
|
| 399 |
+
"}\n",
|
| 400 |
+
"\n",
|
| 401 |
+
"#sk-container-id-1 div.sk-parallel-item {\n",
|
| 402 |
+
" display: flex;\n",
|
| 403 |
+
" flex-direction: column;\n",
|
| 404 |
+
"}\n",
|
| 405 |
+
"\n",
|
| 406 |
+
"#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
|
| 407 |
+
" align-self: flex-end;\n",
|
| 408 |
+
" width: 50%;\n",
|
| 409 |
+
"}\n",
|
| 410 |
+
"\n",
|
| 411 |
+
"#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
|
| 412 |
+
" align-self: flex-start;\n",
|
| 413 |
+
" width: 50%;\n",
|
| 414 |
+
"}\n",
|
| 415 |
+
"\n",
|
| 416 |
+
"#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
|
| 417 |
+
" width: 0;\n",
|
| 418 |
+
"}\n",
|
| 419 |
+
"\n",
|
| 420 |
+
"/* Serial-specific style estimator block */\n",
|
| 421 |
+
"\n",
|
| 422 |
+
"#sk-container-id-1 div.sk-serial {\n",
|
| 423 |
+
" display: flex;\n",
|
| 424 |
+
" flex-direction: column;\n",
|
| 425 |
+
" align-items: center;\n",
|
| 426 |
+
" background-color: var(--sklearn-color-background);\n",
|
| 427 |
+
" padding-right: 1em;\n",
|
| 428 |
+
" padding-left: 1em;\n",
|
| 429 |
+
"}\n",
|
| 430 |
+
"\n",
|
| 431 |
+
"\n",
|
| 432 |
+
"/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
|
| 433 |
+
"clickable and can be expanded/collapsed.\n",
|
| 434 |
+
"- Pipeline and ColumnTransformer use this feature and define the default style\n",
|
| 435 |
+
"- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
|
| 436 |
+
"*/\n",
|
| 437 |
+
"\n",
|
| 438 |
+
"/* Pipeline and ColumnTransformer style (default) */\n",
|
| 439 |
+
"\n",
|
| 440 |
+
"#sk-container-id-1 div.sk-toggleable {\n",
|
| 441 |
+
" /* Default theme specific background. It is overwritten whether we have a\n",
|
| 442 |
+
" specific estimator or a Pipeline/ColumnTransformer */\n",
|
| 443 |
+
" background-color: var(--sklearn-color-background);\n",
|
| 444 |
+
"}\n",
|
| 445 |
+
"\n",
|
| 446 |
+
"/* Toggleable label */\n",
|
| 447 |
+
"#sk-container-id-1 label.sk-toggleable__label {\n",
|
| 448 |
+
" cursor: pointer;\n",
|
| 449 |
+
" display: block;\n",
|
| 450 |
+
" width: 100%;\n",
|
| 451 |
+
" margin-bottom: 0;\n",
|
| 452 |
+
" padding: 0.5em;\n",
|
| 453 |
+
" box-sizing: border-box;\n",
|
| 454 |
+
" text-align: center;\n",
|
| 455 |
+
"}\n",
|
| 456 |
+
"\n",
|
| 457 |
+
"#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
|
| 458 |
+
" /* Arrow on the left of the label */\n",
|
| 459 |
+
" content: \"▸\";\n",
|
| 460 |
+
" float: left;\n",
|
| 461 |
+
" margin-right: 0.25em;\n",
|
| 462 |
+
" color: var(--sklearn-color-icon);\n",
|
| 463 |
+
"}\n",
|
| 464 |
+
"\n",
|
| 465 |
+
"#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
|
| 466 |
+
" color: var(--sklearn-color-text);\n",
|
| 467 |
+
"}\n",
|
| 468 |
+
"\n",
|
| 469 |
+
"/* Toggleable content - dropdown */\n",
|
| 470 |
+
"\n",
|
| 471 |
+
"#sk-container-id-1 div.sk-toggleable__content {\n",
|
| 472 |
+
" max-height: 0;\n",
|
| 473 |
+
" max-width: 0;\n",
|
| 474 |
+
" overflow: hidden;\n",
|
| 475 |
+
" text-align: left;\n",
|
| 476 |
+
" /* unfitted */\n",
|
| 477 |
+
" background-color: var(--sklearn-color-unfitted-level-0);\n",
|
| 478 |
+
"}\n",
|
| 479 |
+
"\n",
|
| 480 |
+
"#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
|
| 481 |
+
" /* fitted */\n",
|
| 482 |
+
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
| 483 |
+
"}\n",
|
| 484 |
+
"\n",
|
| 485 |
+
"#sk-container-id-1 div.sk-toggleable__content pre {\n",
|
| 486 |
+
" margin: 0.2em;\n",
|
| 487 |
+
" border-radius: 0.25em;\n",
|
| 488 |
+
" color: var(--sklearn-color-text);\n",
|
| 489 |
+
" /* unfitted */\n",
|
| 490 |
+
" background-color: var(--sklearn-color-unfitted-level-0);\n",
|
| 491 |
+
"}\n",
|
| 492 |
+
"\n",
|
| 493 |
+
"#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
|
| 494 |
+
" /* unfitted */\n",
|
| 495 |
+
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
| 496 |
+
"}\n",
|
| 497 |
+
"\n",
|
| 498 |
+
"#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
|
| 499 |
+
" /* Expand drop-down */\n",
|
| 500 |
+
" max-height: 200px;\n",
|
| 501 |
+
" max-width: 100%;\n",
|
| 502 |
+
" overflow: auto;\n",
|
| 503 |
+
"}\n",
|
| 504 |
+
"\n",
|
| 505 |
+
"#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
|
| 506 |
+
" content: \"▾\";\n",
|
| 507 |
+
"}\n",
|
| 508 |
+
"\n",
|
| 509 |
+
"/* Pipeline/ColumnTransformer-specific style */\n",
|
| 510 |
+
"\n",
|
| 511 |
+
"#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
| 512 |
+
" color: var(--sklearn-color-text);\n",
|
| 513 |
+
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
| 514 |
+
"}\n",
|
| 515 |
+
"\n",
|
| 516 |
+
"#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
| 517 |
+
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
| 518 |
+
"}\n",
|
| 519 |
+
"\n",
|
| 520 |
+
"/* Estimator-specific style */\n",
|
| 521 |
+
"\n",
|
| 522 |
+
"/* Colorize estimator box */\n",
|
| 523 |
+
"#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
| 524 |
+
" /* unfitted */\n",
|
| 525 |
+
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
| 526 |
+
"}\n",
|
| 527 |
+
"\n",
|
| 528 |
+
"#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
|
| 529 |
+
" /* fitted */\n",
|
| 530 |
+
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
| 531 |
+
"}\n",
|
| 532 |
+
"\n",
|
| 533 |
+
"#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
|
| 534 |
+
"#sk-container-id-1 div.sk-label label {\n",
|
| 535 |
+
" /* The background is the default theme color */\n",
|
| 536 |
+
" color: var(--sklearn-color-text-on-default-background);\n",
|
| 537 |
+
"}\n",
|
| 538 |
+
"\n",
|
| 539 |
+
"/* On hover, darken the color of the background */\n",
|
| 540 |
+
"#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
|
| 541 |
+
" color: var(--sklearn-color-text);\n",
|
| 542 |
+
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
| 543 |
+
"}\n",
|
| 544 |
+
"\n",
|
| 545 |
+
"/* Label box, darken color on hover, fitted */\n",
|
| 546 |
+
"#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
|
| 547 |
+
" color: var(--sklearn-color-text);\n",
|
| 548 |
+
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
| 549 |
+
"}\n",
|
| 550 |
+
"\n",
|
| 551 |
+
"/* Estimator label */\n",
|
| 552 |
+
"\n",
|
| 553 |
+
"#sk-container-id-1 div.sk-label label {\n",
|
| 554 |
+
" font-family: monospace;\n",
|
| 555 |
+
" font-weight: bold;\n",
|
| 556 |
+
" display: inline-block;\n",
|
| 557 |
+
" line-height: 1.2em;\n",
|
| 558 |
+
"}\n",
|
| 559 |
+
"\n",
|
| 560 |
+
"#sk-container-id-1 div.sk-label-container {\n",
|
| 561 |
+
" text-align: center;\n",
|
| 562 |
+
"}\n",
|
| 563 |
+
"\n",
|
| 564 |
+
"/* Estimator-specific */\n",
|
| 565 |
+
"#sk-container-id-1 div.sk-estimator {\n",
|
| 566 |
+
" font-family: monospace;\n",
|
| 567 |
+
" border: 1px dotted var(--sklearn-color-border-box);\n",
|
| 568 |
+
" border-radius: 0.25em;\n",
|
| 569 |
+
" box-sizing: border-box;\n",
|
| 570 |
+
" margin-bottom: 0.5em;\n",
|
| 571 |
+
" /* unfitted */\n",
|
| 572 |
+
" background-color: var(--sklearn-color-unfitted-level-0);\n",
|
| 573 |
+
"}\n",
|
| 574 |
+
"\n",
|
| 575 |
+
"#sk-container-id-1 div.sk-estimator.fitted {\n",
|
| 576 |
+
" /* fitted */\n",
|
| 577 |
+
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
| 578 |
+
"}\n",
|
| 579 |
+
"\n",
|
| 580 |
+
"/* on hover */\n",
|
| 581 |
+
"#sk-container-id-1 div.sk-estimator:hover {\n",
|
| 582 |
+
" /* unfitted */\n",
|
| 583 |
+
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
| 584 |
+
"}\n",
|
| 585 |
+
"\n",
|
| 586 |
+
"#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
|
| 587 |
+
" /* fitted */\n",
|
| 588 |
+
" background-color: var(--sklearn-color-fitted-level-2);\n",
|
| 589 |
+
"}\n",
|
| 590 |
+
"\n",
|
| 591 |
+
"/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
|
| 592 |
+
"\n",
|
| 593 |
+
"/* Common style for \"i\" and \"?\" */\n",
|
| 594 |
+
"\n",
|
| 595 |
+
".sk-estimator-doc-link,\n",
|
| 596 |
+
"a:link.sk-estimator-doc-link,\n",
|
| 597 |
+
"a:visited.sk-estimator-doc-link {\n",
|
| 598 |
+
" float: right;\n",
|
| 599 |
+
" font-size: smaller;\n",
|
| 600 |
+
" line-height: 1em;\n",
|
| 601 |
+
" font-family: monospace;\n",
|
| 602 |
+
" background-color: var(--sklearn-color-background);\n",
|
| 603 |
+
" border-radius: 1em;\n",
|
| 604 |
+
" height: 1em;\n",
|
| 605 |
+
" width: 1em;\n",
|
| 606 |
+
" text-decoration: none !important;\n",
|
| 607 |
+
" margin-left: 1ex;\n",
|
| 608 |
+
" /* unfitted */\n",
|
| 609 |
+
" border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
|
| 610 |
+
" color: var(--sklearn-color-unfitted-level-1);\n",
|
| 611 |
+
"}\n",
|
| 612 |
+
"\n",
|
| 613 |
+
".sk-estimator-doc-link.fitted,\n",
|
| 614 |
+
"a:link.sk-estimator-doc-link.fitted,\n",
|
| 615 |
+
"a:visited.sk-estimator-doc-link.fitted {\n",
|
| 616 |
+
" /* fitted */\n",
|
| 617 |
+
" border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
|
| 618 |
+
" color: var(--sklearn-color-fitted-level-1);\n",
|
| 619 |
+
"}\n",
|
| 620 |
+
"\n",
|
| 621 |
+
"/* On hover */\n",
|
| 622 |
+
"div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
|
| 623 |
+
".sk-estimator-doc-link:hover,\n",
|
| 624 |
+
"div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
|
| 625 |
+
".sk-estimator-doc-link:hover {\n",
|
| 626 |
+
" /* unfitted */\n",
|
| 627 |
+
" background-color: var(--sklearn-color-unfitted-level-3);\n",
|
| 628 |
+
" color: var(--sklearn-color-background);\n",
|
| 629 |
+
" text-decoration: none;\n",
|
| 630 |
+
"}\n",
|
| 631 |
+
"\n",
|
| 632 |
+
"div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
|
| 633 |
+
".sk-estimator-doc-link.fitted:hover,\n",
|
| 634 |
+
"div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
|
| 635 |
+
".sk-estimator-doc-link.fitted:hover {\n",
|
| 636 |
+
" /* fitted */\n",
|
| 637 |
+
" background-color: var(--sklearn-color-fitted-level-3);\n",
|
| 638 |
+
" color: var(--sklearn-color-background);\n",
|
| 639 |
+
" text-decoration: none;\n",
|
| 640 |
+
"}\n",
|
| 641 |
+
"\n",
|
| 642 |
+
"/* Span, style for the box shown on hovering the info icon */\n",
|
| 643 |
+
".sk-estimator-doc-link span {\n",
|
| 644 |
+
" display: none;\n",
|
| 645 |
+
" z-index: 9999;\n",
|
| 646 |
+
" position: relative;\n",
|
| 647 |
+
" font-weight: normal;\n",
|
| 648 |
+
" right: .2ex;\n",
|
| 649 |
+
" padding: .5ex;\n",
|
| 650 |
+
" margin: .5ex;\n",
|
| 651 |
+
" width: min-content;\n",
|
| 652 |
+
" min-width: 20ex;\n",
|
| 653 |
+
" max-width: 50ex;\n",
|
| 654 |
+
" color: var(--sklearn-color-text);\n",
|
| 655 |
+
" box-shadow: 2pt 2pt 4pt #999;\n",
|
| 656 |
+
" /* unfitted */\n",
|
| 657 |
+
" background: var(--sklearn-color-unfitted-level-0);\n",
|
| 658 |
+
" border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
|
| 659 |
+
"}\n",
|
| 660 |
+
"\n",
|
| 661 |
+
".sk-estimator-doc-link.fitted span {\n",
|
| 662 |
+
" /* fitted */\n",
|
| 663 |
+
" background: var(--sklearn-color-fitted-level-0);\n",
|
| 664 |
+
" border: var(--sklearn-color-fitted-level-3);\n",
|
| 665 |
+
"}\n",
|
| 666 |
+
"\n",
|
| 667 |
+
".sk-estimator-doc-link:hover span {\n",
|
| 668 |
+
" display: block;\n",
|
| 669 |
+
"}\n",
|
| 670 |
+
"\n",
|
| 671 |
+
"/* \"?\"-specific style due to the `<a>` HTML tag */\n",
|
| 672 |
+
"\n",
|
| 673 |
+
"#sk-container-id-1 a.estimator_doc_link {\n",
|
| 674 |
+
" float: right;\n",
|
| 675 |
+
" font-size: 1rem;\n",
|
| 676 |
+
" line-height: 1em;\n",
|
| 677 |
+
" font-family: monospace;\n",
|
| 678 |
+
" background-color: var(--sklearn-color-background);\n",
|
| 679 |
+
" border-radius: 1rem;\n",
|
| 680 |
+
" height: 1rem;\n",
|
| 681 |
+
" width: 1rem;\n",
|
| 682 |
+
" text-decoration: none;\n",
|
| 683 |
+
" /* unfitted */\n",
|
| 684 |
+
" color: var(--sklearn-color-unfitted-level-1);\n",
|
| 685 |
+
" border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
|
| 686 |
+
"}\n",
|
| 687 |
+
"\n",
|
| 688 |
+
"#sk-container-id-1 a.estimator_doc_link.fitted {\n",
|
| 689 |
+
" /* fitted */\n",
|
| 690 |
+
" border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
|
| 691 |
+
" color: var(--sklearn-color-fitted-level-1);\n",
|
| 692 |
+
"}\n",
|
| 693 |
+
"\n",
|
| 694 |
+
"/* On hover */\n",
|
| 695 |
+
"#sk-container-id-1 a.estimator_doc_link:hover {\n",
|
| 696 |
+
" /* unfitted */\n",
|
| 697 |
+
" background-color: var(--sklearn-color-unfitted-level-3);\n",
|
| 698 |
+
" color: var(--sklearn-color-background);\n",
|
| 699 |
+
" text-decoration: none;\n",
|
| 700 |
+
"}\n",
|
| 701 |
+
"\n",
|
| 702 |
+
"#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
|
| 703 |
+
" /* fitted */\n",
|
| 704 |
+
" background-color: var(--sklearn-color-fitted-level-3);\n",
|
| 705 |
+
"}\n",
|
| 706 |
+
"</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\"> LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression()</pre></div> </div></div></div></div>"
|
| 707 |
+
],
|
| 708 |
+
"text/plain": [
|
| 709 |
+
"LogisticRegression()"
|
| 710 |
+
]
|
| 711 |
+
},
|
| 712 |
+
"execution_count": 99,
|
| 713 |
+
"metadata": {},
|
| 714 |
+
"output_type": "execute_result"
|
| 715 |
+
}
|
| 716 |
+
],
|
| 717 |
+
"source": [
|
| 718 |
+
"# Train a Logistic Regression model\n",
|
| 719 |
+
"model = LogisticRegression(max_iter=100)\n",
|
| 720 |
+
"model.fit(X_train_tfidf, y_train)"
|
| 721 |
+
]
|
| 722 |
+
},
|
| 723 |
+
{
|
| 724 |
+
"cell_type": "code",
|
| 725 |
+
"execution_count": 100,
|
| 726 |
+
"metadata": {},
|
| 727 |
+
"outputs": [],
|
| 728 |
+
"source": [
|
| 729 |
+
"y_pred = model.predict(X_test_tfidf)"
|
| 730 |
+
]
|
| 731 |
+
},
|
| 732 |
+
{
|
| 733 |
+
"cell_type": "code",
|
| 734 |
+
"execution_count": 105,
|
| 735 |
+
"metadata": {},
|
| 736 |
+
"outputs": [
|
| 737 |
+
{
|
| 738 |
+
"name": "stdout",
|
| 739 |
+
"output_type": "stream",
|
| 740 |
+
"text": [
|
| 741 |
+
"Accuracy: 0.7084\n",
|
| 742 |
+
"Classification Report:\n",
|
| 743 |
+
" precision recall f1-score support\n",
|
| 744 |
+
"\n",
|
| 745 |
+
" 0 0.72 0.80 0.76 427\n",
|
| 746 |
+
" 1 0.70 0.59 0.64 331\n",
|
| 747 |
+
"\n",
|
| 748 |
+
" accuracy 0.71 758\n",
|
| 749 |
+
" macro avg 0.71 0.70 0.70 758\n",
|
| 750 |
+
"weighted avg 0.71 0.71 0.70 758\n",
|
| 751 |
+
"\n"
|
| 752 |
+
]
|
| 753 |
+
}
|
| 754 |
+
],
|
| 755 |
+
"source": [
|
| 756 |
+
"# 7. Evaluate the model\n",
|
| 757 |
+
"accuracy = accuracy_score(y_test, y_pred)\n",
|
| 758 |
+
"print(f\"Accuracy: {accuracy:.4f}\")\n",
|
| 759 |
+
"print(\"Classification Report:\\n\", classification_report(y_test, y_pred)\n",
|
| 760 |
+
")"
|
| 761 |
+
]
|
| 762 |
+
},
|
| 763 |
+
{
|
| 764 |
+
"cell_type": "code",
|
| 765 |
+
"execution_count": 7,
|
| 766 |
+
"metadata": {},
|
| 767 |
+
"outputs": [
|
| 768 |
+
{
|
| 769 |
+
"data": {
|
| 770 |
+
"text/plain": [
|
| 771 |
+
"<bound method NDFrame.head of url \\\n",
|
| 772 |
+
"0 https://www.foxnews.com/lifestyle/jack-carrs-e... \n",
|
| 773 |
+
"1 https://www.foxnews.com/entertainment/bruce-wi... \n",
|
| 774 |
+
"2 https://www.foxnews.com/politics/blinken-meets... \n",
|
| 775 |
+
"3 https://www.foxnews.com/entertainment/emily-bl... \n",
|
| 776 |
+
"4 https://www.foxnews.com/media/the-view-co-host... \n",
|
| 777 |
+
"... ... \n",
|
| 778 |
+
"3784 https://www.nbcnews.com/politics/2024-election... \n",
|
| 779 |
+
"3785 https://www.nbcnews.com/select/shopping/best-a... \n",
|
| 780 |
+
"3786 https://www.nbcnews.com/select/shopping/best-v... \n",
|
| 781 |
+
"3787 https://www.nbcnews.com/politics/2024-election... \n",
|
| 782 |
+
"3788 https://www.nbcnews.com/select/shopping/white-... \n",
|
| 783 |
+
"\n",
|
| 784 |
+
" title label \n",
|
| 785 |
+
"0 Jack Carr recalls Gen. Eisenhower's D-Day memo... 0 \n",
|
| 786 |
+
"1 Bruce Willis, Demi Moore avoided doing one thi... 0 \n",
|
| 787 |
+
"2 Blinken meets Qatar PM, says Israeli actions a... 0 \n",
|
| 788 |
+
"3 Emily Blunt says her ‘toes curl’ when people t... 0 \n",
|
| 789 |
+
"4 'The View' co-host, CNN commentator Ana Navarr... 0 \n",
|
| 790 |
+
"... ... ... \n",
|
| 791 |
+
"3784 Trump's lawyers seek post-Election Day delay f... 1 \n",
|
| 792 |
+
"3785 How to treat acne scars and hyperpigmentation,... 1 \n",
|
| 793 |
+
"3786 7 best vegetarian and vegan meal delivery serv... 1 \n",
|
| 794 |
+
"3787 Trump says presidential civilian award is 'bet... 1 \n",
|
| 795 |
+
"3788 19 best white elephant and Secret Santa gift i... 1 \n",
|
| 796 |
+
"\n",
|
| 797 |
+
"[3789 rows x 3 columns]>"
|
| 798 |
+
]
|
| 799 |
+
},
|
| 800 |
+
"execution_count": 7,
|
| 801 |
+
"metadata": {},
|
| 802 |
+
"output_type": "execute_result"
|
| 803 |
+
}
|
| 804 |
+
],
|
| 805 |
+
"source": [
|
| 806 |
+
"df = pd.read_csv('fetched_headlines.csv')\n",
|
| 807 |
+
"df.head"
|
| 808 |
+
]
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"cell_type": "code",
|
| 812 |
+
"execution_count": null,
|
| 813 |
+
"metadata": {},
|
| 814 |
+
"outputs": [
|
| 815 |
+
{
|
| 816 |
+
"data": {
|
| 817 |
+
"text/html": [
|
| 818 |
+
"<div>\n",
|
| 819 |
+
"<style scoped>\n",
|
| 820 |
+
" .dataframe tbody tr th:only-of-type {\n",
|
| 821 |
+
" vertical-align: middle;\n",
|
| 822 |
+
" }\n",
|
| 823 |
+
"\n",
|
| 824 |
+
" .dataframe tbody tr th {\n",
|
| 825 |
+
" vertical-align: top;\n",
|
| 826 |
+
" }\n",
|
| 827 |
+
"\n",
|
| 828 |
+
" .dataframe thead th {\n",
|
| 829 |
+
" text-align: right;\n",
|
| 830 |
+
" }\n",
|
| 831 |
+
"</style>\n",
|
| 832 |
+
"<table border=\"1\" class=\"dataframe\">\n",
|
| 833 |
+
" <thead>\n",
|
| 834 |
+
" <tr style=\"text-align: right;\">\n",
|
| 835 |
+
" <th></th>\n",
|
| 836 |
+
" <th>url</th>\n",
|
| 837 |
+
" <th>title</th>\n",
|
| 838 |
+
" <th>label</th>\n",
|
| 839 |
+
" <th>outlet</th>\n",
|
| 840 |
+
" </tr>\n",
|
| 841 |
+
" </thead>\n",
|
| 842 |
+
" <tbody>\n",
|
| 843 |
+
" <tr>\n",
|
| 844 |
+
" <th>0</th>\n",
|
| 845 |
+
" <td>https://www.foxnews.com/lifestyle/jack-carrs-e...</td>\n",
|
| 846 |
+
" <td>Jack Carr recalls Gen. Eisenhower's D-Day memo...</td>\n",
|
| 847 |
+
" <td>0</td>\n",
|
| 848 |
+
" <td>FoxNews</td>\n",
|
| 849 |
+
" </tr>\n",
|
| 850 |
+
" <tr>\n",
|
| 851 |
+
" <th>1</th>\n",
|
| 852 |
+
" <td>https://www.foxnews.com/entertainment/bruce-wi...</td>\n",
|
| 853 |
+
" <td>Bruce Willis, Demi Moore avoided doing one thi...</td>\n",
|
| 854 |
+
" <td>0</td>\n",
|
| 855 |
+
" <td>FoxNews</td>\n",
|
| 856 |
+
" </tr>\n",
|
| 857 |
+
" <tr>\n",
|
| 858 |
+
" <th>2</th>\n",
|
| 859 |
+
" <td>https://www.foxnews.com/politics/blinken-meets...</td>\n",
|
| 860 |
+
" <td>Blinken meets Qatar PM, says Israeli actions a...</td>\n",
|
| 861 |
+
" <td>0</td>\n",
|
| 862 |
+
" <td>FoxNews</td>\n",
|
| 863 |
+
" </tr>\n",
|
| 864 |
+
" <tr>\n",
|
| 865 |
+
" <th>3</th>\n",
|
| 866 |
+
" <td>https://www.foxnews.com/entertainment/emily-bl...</td>\n",
|
| 867 |
+
" <td>Emily Blunt says her ‘toes curl’ when people t...</td>\n",
|
| 868 |
+
" <td>0</td>\n",
|
| 869 |
+
" <td>FoxNews</td>\n",
|
| 870 |
+
" </tr>\n",
|
| 871 |
+
" <tr>\n",
|
| 872 |
+
" <th>4</th>\n",
|
| 873 |
+
" <td>https://www.foxnews.com/media/the-view-co-host...</td>\n",
|
| 874 |
+
" <td>'The View' co-host, CNN commentator Ana Navarr...</td>\n",
|
| 875 |
+
" <td>0</td>\n",
|
| 876 |
+
" <td>FoxNews</td>\n",
|
| 877 |
+
" </tr>\n",
|
| 878 |
+
" </tbody>\n",
|
| 879 |
+
"</table>\n",
|
| 880 |
+
"</div>"
|
| 881 |
+
],
|
| 882 |
+
"text/plain": [
|
| 883 |
+
" url \\\n",
|
| 884 |
+
"0 https://www.foxnews.com/lifestyle/jack-carrs-e... \n",
|
| 885 |
+
"1 https://www.foxnews.com/entertainment/bruce-wi... \n",
|
| 886 |
+
"2 https://www.foxnews.com/politics/blinken-meets... \n",
|
| 887 |
+
"3 https://www.foxnews.com/entertainment/emily-bl... \n",
|
| 888 |
+
"4 https://www.foxnews.com/media/the-view-co-host... \n",
|
| 889 |
+
"\n",
|
| 890 |
+
" title label outlet \n",
|
| 891 |
+
"0 Jack Carr recalls Gen. Eisenhower's D-Day memo... 0 FoxNews \n",
|
| 892 |
+
"1 Bruce Willis, Demi Moore avoided doing one thi... 0 FoxNews \n",
|
| 893 |
+
"2 Blinken meets Qatar PM, says Israeli actions a... 0 FoxNews \n",
|
| 894 |
+
"3 Emily Blunt says her ‘toes curl’ when people t... 0 FoxNews \n",
|
| 895 |
+
"4 'The View' co-host, CNN commentator Ana Navarr... 0 FoxNews "
|
| 896 |
+
]
|
| 897 |
+
},
|
| 898 |
+
"execution_count": 8,
|
| 899 |
+
"metadata": {},
|
| 900 |
+
"output_type": "execute_result"
|
| 901 |
+
}
|
| 902 |
+
],
|
| 903 |
+
"source": [
|
| 904 |
+
"df['outlet'] = df['url'].apply(lambda x: 'FoxNews' if 'foxnews.com' in x else 'NBC')\n"
|
| 905 |
+
]
|
| 906 |
+
},
|
| 907 |
+
{
|
| 908 |
+
"cell_type": "code",
|
| 909 |
+
"execution_count": 10,
|
| 910 |
+
"metadata": {},
|
| 911 |
+
"outputs": [
|
| 912 |
+
{
|
| 913 |
+
"data": {
|
| 914 |
+
"text/html": [
|
| 915 |
+
"<div>\n",
|
| 916 |
+
"<style scoped>\n",
|
| 917 |
+
" .dataframe tbody tr th:only-of-type {\n",
|
| 918 |
+
" vertical-align: middle;\n",
|
| 919 |
+
" }\n",
|
| 920 |
+
"\n",
|
| 921 |
+
" .dataframe tbody tr th {\n",
|
| 922 |
+
" vertical-align: top;\n",
|
| 923 |
+
" }\n",
|
| 924 |
+
"\n",
|
| 925 |
+
" .dataframe thead th {\n",
|
| 926 |
+
" text-align: right;\n",
|
| 927 |
+
" }\n",
|
| 928 |
+
"</style>\n",
|
| 929 |
+
"<table border=\"1\" class=\"dataframe\">\n",
|
| 930 |
+
" <thead>\n",
|
| 931 |
+
" <tr style=\"text-align: right;\">\n",
|
| 932 |
+
" <th></th>\n",
|
| 933 |
+
" <th>title</th>\n",
|
| 934 |
+
" <th>outlet</th>\n",
|
| 935 |
+
" <th>label</th>\n",
|
| 936 |
+
" </tr>\n",
|
| 937 |
+
" </thead>\n",
|
| 938 |
+
" <tbody>\n",
|
| 939 |
+
" <tr>\n",
|
| 940 |
+
" <th>0</th>\n",
|
| 941 |
+
" <td>Jack Carr recalls Gen. Eisenhower's D-Day memo...</td>\n",
|
| 942 |
+
" <td>FoxNews</td>\n",
|
| 943 |
+
" <td>1</td>\n",
|
| 944 |
+
" </tr>\n",
|
| 945 |
+
" <tr>\n",
|
| 946 |
+
" <th>1</th>\n",
|
| 947 |
+
" <td>Bruce Willis, Demi Moore avoided doing one thi...</td>\n",
|
| 948 |
+
" <td>FoxNews</td>\n",
|
| 949 |
+
" <td>1</td>\n",
|
| 950 |
+
" </tr>\n",
|
| 951 |
+
" <tr>\n",
|
| 952 |
+
" <th>2</th>\n",
|
| 953 |
+
" <td>Blinken meets Qatar PM, says Israeli actions a...</td>\n",
|
| 954 |
+
" <td>FoxNews</td>\n",
|
| 955 |
+
" <td>1</td>\n",
|
| 956 |
+
" </tr>\n",
|
| 957 |
+
" <tr>\n",
|
| 958 |
+
" <th>3</th>\n",
|
| 959 |
+
" <td>Emily Blunt says her ‘toes curl’ when people t...</td>\n",
|
| 960 |
+
" <td>FoxNews</td>\n",
|
| 961 |
+
" <td>1</td>\n",
|
| 962 |
+
" </tr>\n",
|
| 963 |
+
" <tr>\n",
|
| 964 |
+
" <th>4</th>\n",
|
| 965 |
+
" <td>'The View' co-host, CNN commentator Ana Navarr...</td>\n",
|
| 966 |
+
" <td>FoxNews</td>\n",
|
| 967 |
+
" <td>1</td>\n",
|
| 968 |
+
" </tr>\n",
|
| 969 |
+
" </tbody>\n",
|
| 970 |
+
"</table>\n",
|
| 971 |
+
"</div>"
|
| 972 |
+
],
|
| 973 |
+
"text/plain": [
|
| 974 |
+
" title outlet label\n",
|
| 975 |
+
"0 Jack Carr recalls Gen. Eisenhower's D-Day memo... FoxNews 1\n",
|
| 976 |
+
"1 Bruce Willis, Demi Moore avoided doing one thi... FoxNews 1\n",
|
| 977 |
+
"2 Blinken meets Qatar PM, says Israeli actions a... FoxNews 1\n",
|
| 978 |
+
"3 Emily Blunt says her ‘toes curl’ when people t... FoxNews 1\n",
|
| 979 |
+
"4 'The View' co-host, CNN commentator Ana Navarr... FoxNews 1"
|
| 980 |
+
]
|
| 981 |
+
},
|
| 982 |
+
"execution_count": 10,
|
| 983 |
+
"metadata": {},
|
| 984 |
+
"output_type": "execute_result"
|
| 985 |
+
}
|
| 986 |
+
],
|
| 987 |
+
"source": [
|
| 988 |
+
"# Swap label and outlet position and update label values\n",
|
| 989 |
+
"df['label'] = df['outlet'].apply(lambda x: 1 if x == 'FoxNews' else 0)\n",
|
| 990 |
+
"df = df[[ 'title', 'outlet', 'label']]\n",
|
| 991 |
+
"df.head()"
|
| 992 |
+
]
|
| 993 |
+
},
|
| 994 |
+
{
|
| 995 |
+
"cell_type": "code",
|
| 996 |
+
"execution_count": 11,
|
| 997 |
+
"metadata": {},
|
| 998 |
+
"outputs": [],
|
| 999 |
+
"source": [
|
| 1000 |
+
"df.to_csv('train_data.csv', index=False)"
|
| 1001 |
+
]
|
| 1002 |
+
},
|
| 1003 |
+
{
|
| 1004 |
+
"cell_type": "code",
|
| 1005 |
+
"execution_count": 12,
|
| 1006 |
+
"metadata": {},
|
| 1007 |
+
"outputs": [
|
| 1008 |
+
{
|
| 1009 |
+
"data": {
|
| 1010 |
+
"text/plain": [
|
| 1011 |
+
"array([<class 'str'>], dtype=object)"
|
| 1012 |
+
]
|
| 1013 |
+
},
|
| 1014 |
+
"execution_count": 12,
|
| 1015 |
+
"metadata": {},
|
| 1016 |
+
"output_type": "execute_result"
|
| 1017 |
+
}
|
| 1018 |
+
],
|
| 1019 |
+
"source": [
|
| 1020 |
+
"df['title'].apply(type).unique()"
|
| 1021 |
+
]
|
| 1022 |
+
},
|
| 1023 |
+
{
|
| 1024 |
+
"cell_type": "code",
|
| 1025 |
+
"execution_count": null,
|
| 1026 |
+
"metadata": {},
|
| 1027 |
+
"outputs": [],
|
| 1028 |
+
"source": []
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"cell_type": "code",
|
| 1032 |
+
"execution_count": null,
|
| 1033 |
+
"metadata": {},
|
| 1034 |
+
"outputs": [],
|
| 1035 |
+
"source": []
|
| 1036 |
+
},
|
| 1037 |
+
{
|
| 1038 |
+
"cell_type": "code",
|
| 1039 |
+
"execution_count": null,
|
| 1040 |
+
"metadata": {},
|
| 1041 |
+
"outputs": [],
|
| 1042 |
+
"source": []
|
| 1043 |
+
}
|
| 1044 |
+
],
|
| 1045 |
+
"metadata": {
|
| 1046 |
+
"kernelspec": {
|
| 1047 |
+
"display_name": ".venv",
|
| 1048 |
+
"language": "python",
|
| 1049 |
+
"name": "python3"
|
| 1050 |
+
},
|
| 1051 |
+
"language_info": {
|
| 1052 |
+
"codemirror_mode": {
|
| 1053 |
+
"name": "ipython",
|
| 1054 |
+
"version": 3
|
| 1055 |
+
},
|
| 1056 |
+
"file_extension": ".py",
|
| 1057 |
+
"mimetype": "text/x-python",
|
| 1058 |
+
"name": "python",
|
| 1059 |
+
"nbconvert_exporter": "python",
|
| 1060 |
+
"pygments_lexer": "ipython3",
|
| 1061 |
+
"version": "3.9.6"
|
| 1062 |
+
}
|
| 1063 |
+
},
|
| 1064 |
+
"nbformat": 4,
|
| 1065 |
+
"nbformat_minor": 2
|
| 1066 |
+
}
|
train_data.csv
ADDED
|
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See raw diff
|
|
|