Stupid Solution.ipynb

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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Darrell Lucus</td>\n",
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       "      <td>FLYNN: Hillary Clinton, Big Woman on Campus - ...</td>\n",
       "      <td>Daniel J. Flynn</td>\n",
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       "      <td>Why the Truth Might Get You Fired</td>\n",
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      "text/plain": [
       "                                                title              author  \\\n",
       "id                                                                          \n",
       "0   House Dem Aide: We Didn’t Even See Comey’s Let...       Darrell Lucus   \n",
       "1   FLYNN: Hillary Clinton, Big Woman on Campus - ...     Daniel J. Flynn   \n",
       "2                   Why the Truth Might Get You Fired  Consortiumnews.com   \n",
       "3   15 Civilians Killed In Single US Airstrike Hav...     Jessica Purkiss   \n",
       "4   Iranian woman jailed for fictional unpublished...      Howard Portnoy   \n",
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       "                                                 text  label  \n",
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       "3   Videos 15 Civilians Killed In Single US Airstr...      1  \n",
       "4   Print \\nAn Iranian woman has been sentenced to...      1  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = pd.read_csv('train.csv', index_col='id')\n",
    "train = train.fillna('')\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th>text</th>\n",
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       "      <td>Specter of Trump Loosens Tongues, if Not Purse...</td>\n",
       "      <td>David Streitfeld</td>\n",
       "      <td>PALO ALTO, Calif.  —   After years of scorning...</td>\n",
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       "      <td>Russian warships ready to strike terrorists ne...</td>\n",
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       "    <tr>\n",
       "      <th>20802</th>\n",
       "      <td>#NoDAPL: Native American Leaders Vow to Stay A...</td>\n",
       "      <td>Common Dreams</td>\n",
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       "      <td>Tim Tebow Will Attempt Another Comeback, This ...</td>\n",
       "      <td>Daniel Victor</td>\n",
       "      <td>If at first you don’t succeed, try a different...</td>\n",
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       "    <tr>\n",
       "      <th>20804</th>\n",
       "      <td>Keiser Report: Meme Wars (E995)</td>\n",
       "      <td>Truth Broadcast Network</td>\n",
       "      <td>42 mins ago 1 Views 0 Comments 0 Likes 'For th...</td>\n",
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      "text/plain": [
       "                                                   title  \\\n",
       "id                                                         \n",
       "20800  Specter of Trump Loosens Tongues, if Not Purse...   \n",
       "20801  Russian warships ready to strike terrorists ne...   \n",
       "20802  #NoDAPL: Native American Leaders Vow to Stay A...   \n",
       "20803  Tim Tebow Will Attempt Another Comeback, This ...   \n",
       "20804                    Keiser Report: Meme Wars (E995)   \n",
       "\n",
       "                        author  \\\n",
       "id                               \n",
       "20800         David Streitfeld   \n",
       "20801                            \n",
       "20802            Common Dreams   \n",
       "20803            Daniel Victor   \n",
       "20804  Truth Broadcast Network   \n",
       "\n",
       "                                                    text  \n",
       "id                                                        \n",
       "20800  PALO ALTO, Calif.  —   After years of scorning...  \n",
       "20801  Russian warships ready to strike terrorists ne...  \n",
       "20802  Videos #NoDAPL: Native American Leaders Vow to...  \n",
       "20803  If at first you don’t succeed, try a different...  \n",
       "20804  42 mins ago 1 Views 0 Comments 0 Likes 'For th...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test = pd.read_csv('test.csv', index_col='id')\n",
    "test = test.fillna('')\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's start by considering what the dumbest \"model\" we could make is."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Randomly guessing is pretty dumb. Let's try that!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from random import choice\n",
    "def model(text):\n",
    "    options = [0, 1]\n",
    "    return choice(options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = train.apply(model)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5\n"
     ]
    }
   ],
   "source": [
    "correct = 0\n",
    "for prediction, actual in zip(predictions, train['label']):\n",
    "    if prediction == actual:\n",
    "        correct += 1\n",
    "print(correct / len(predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <th>20803</th>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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      "text/plain": [
       "       label\n",
       "id          \n",
       "20800      1\n",
       "20801      1\n",
       "20802      1\n",
       "20803      1\n",
       "20804      1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
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   ],
   "source": [
    "test['label'] = test['text'].apply(model)\n",
    "\n",
    "submit = test.drop(['title', 'author', 'text'], axis=1)\n",
    "submit.to_csv('submit.csv', index='id')\n",
    "submit.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets try to figure out what \"fake news\" has in common\n",
    "\n",
    "We don't know which rows are fake in our test file, but we do know which ones are fake from the train file, because we have labels for that one.\n",
    "\n",
    "Lets start by seperating the train file into reliable and unreliable articles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fake = train[train['label'] == 1]\n",
    "real = train[train['label'] == 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Maybe real articles will more words?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fake_article_word_counts = fake['text'].str.split(' ').str.len()\n",
    "real_article_word_counts = real['text'].str.split(' ').str.len()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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1+uyzz9ost9lsPXrtstPplNPp9Dyuqanp8j7Cw8O7td1A5611Sd5dW3/oq+fS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\necKECaqurra0s5KSEk2fPl1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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10dd8a278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.subplot(121)\n",
    "plt.hist(np.log(fake_article_word_counts))\n",
    "plt.title(\"Fake Article Word Counts\")\n",
    "plt.subplot(122)\n",
    "plt.hist(np.log(real_article_word_counts))\n",
    "plt.title(\"Real Article Word Counts\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Doesn't look like real articles always have more words but it's difficult to tell. Lets calculate the means of each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Fake Length: 639.1147603956592\n",
      "Average Real Length: 907.6252045826513\n"
     ]
    }
   ],
   "source": [
    "average_fake_length = fake_article_word_counts.mean()\n",
    "average_real_length = real_article_word_counts.mean()\n",
    "print(\"Average Fake Length: {}\\nAverage Real Length: {}\".format(average_fake_length, average_real_length))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def model(text):\n",
    "    # If it has more than 660 words, we'll say it's reliable\n",
    "    if len(text.split()) > 660:\n",
    "        return 0\n",
    "    # Otherwise we'll say it's fake news\n",
    "    return 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How does our model do on our training data?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "predictions = train['text'].apply(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6276923076923077\n"
     ]
    }
   ],
   "source": [
    "correct = 0\n",
    "for prediction, actual in zip(predictions, train['label']):\n",
    "    if prediction == actual:\n",
    "        correct += 1\n",
    "print(correct / len(predictions))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Okay so that wasn't a great model... but it's a starting point.\n",
    "\n",
    "Next lets apply it to the test data and see how to prepare a submission."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>author</th>\n",
       "      <th>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>20800</th>\n",
       "      <td>Specter of Trump Loosens Tongues, if Not Purse...</td>\n",
       "      <td>David Streitfeld</td>\n",
       "      <td>PALO ALTO, Calif.  —   After years of scorning...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20801</th>\n",
       "      <td>Russian warships ready to strike terrorists ne...</td>\n",
       "      <td></td>\n",
       "      <td>Russian warships ready to strike terrorists ne...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20802</th>\n",
       "      <td>#NoDAPL: Native American Leaders Vow to Stay A...</td>\n",
       "      <td>Common Dreams</td>\n",
       "      <td>Videos #NoDAPL: Native American Leaders Vow to...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20803</th>\n",
       "      <td>Tim Tebow Will Attempt Another Comeback, This ...</td>\n",
       "      <td>Daniel Victor</td>\n",
       "      <td>If at first you don’t succeed, try a different...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20804</th>\n",
       "      <td>Keiser Report: Meme Wars (E995)</td>\n",
       "      <td>Truth Broadcast Network</td>\n",
       "      <td>42 mins ago 1 Views 0 Comments 0 Likes 'For th...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   title  \\\n",
       "id                                                         \n",
       "20800  Specter of Trump Loosens Tongues, if Not Purse...   \n",
       "20801  Russian warships ready to strike terrorists ne...   \n",
       "20802  #NoDAPL: Native American Leaders Vow to Stay A...   \n",
       "20803  Tim Tebow Will Attempt Another Comeback, This ...   \n",
       "20804                    Keiser Report: Meme Wars (E995)   \n",
       "\n",
       "                        author  \\\n",
       "id                               \n",
       "20800         David Streitfeld   \n",
       "20801                            \n",
       "20802            Common Dreams   \n",
       "20803            Daniel Victor   \n",
       "20804  Truth Broadcast Network   \n",
       "\n",
       "                                                    text  label  \n",
       "id                                                               \n",
       "20800  PALO ALTO, Calif.  —   After years of scorning...      0  \n",
       "20801  Russian warships ready to strike terrorists ne...      1  \n",
       "20802  Videos #NoDAPL: Native American Leaders Vow to...      0  \n",
       "20803  If at first you don’t succeed, try a different...      1  \n",
       "20804  42 mins ago 1 Views 0 Comments 0 Likes 'For th...      1  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test['label'] = test['text'].apply(model)\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "submit = test.drop(['title', 'author', 'text'], axis=1)\n",
    "submit.to_csv('submit.csv', index='id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
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   "codemirror_mode": {
    "name": "ipython",
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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 },
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