{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "145fbd89-a3ee-4628-8e83-4069e504fb03",
   "metadata": {},
   "source": [
    "# Initial EDA\n",
    "What's in here that looks useful?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "075030c8-e9fe-4fce-b752-d910d64ebfb1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:39.214089Z",
     "iopub.status.busy": "2022-06-07T15:25:39.213748Z",
     "iopub.status.idle": "2022-06-07T15:25:40.335156Z",
     "shell.execute_reply": "2022-06-07T15:25:40.334266Z",
     "shell.execute_reply.started": "2022-06-07T15:25:39.214015Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set_theme(style='darkgrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c14f6c4c-fb4b-4e69-817e-28dbae07c298",
   "metadata": {},
   "source": [
    "## First load the data and get basic info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "94c1ae77-ccbd-42ce-9e34-3b0f96342002",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:40.336431Z",
     "iopub.status.busy": "2022-06-07T15:25:40.336185Z",
     "iopub.status.idle": "2022-06-07T15:25:40.738364Z",
     "shell.execute_reply": "2022-06-07T15:25:40.737807Z",
     "shell.execute_reply.started": "2022-06-07T15:25:40.336415Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 48565 entries, 0 to 48564\n",
      "Data columns (total 23 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   author               48544 non-null  object \n",
      " 1   created_utc          48565 non-null  float64\n",
      " 2   distinguished        47 non-null     object \n",
      " 3   edited               48565 non-null  object \n",
      " 4   id                   48565 non-null  object \n",
      " 5   is_original_content  48565 non-null  bool   \n",
      " 6   is_self              48565 non-null  bool   \n",
      " 7   link_flair_text      25836 non-null  object \n",
      " 8   locked               48565 non-null  bool   \n",
      " 9   name                 48565 non-null  object \n",
      " 10  num_comments         48565 non-null  int64  \n",
      " 11  over_18              48565 non-null  bool   \n",
      " 12  permalink            48565 non-null  object \n",
      " 13  score                48565 non-null  int64  \n",
      " 14  selftext             2243 non-null   object \n",
      " 15  spoiler              48565 non-null  bool   \n",
      " 16  stickied             48565 non-null  bool   \n",
      " 17  subreddit            48565 non-null  object \n",
      " 18  title                48565 non-null  object \n",
      " 19  upvote_ratio         48565 non-null  float64\n",
      " 20  url                  48565 non-null  object \n",
      " 21  utc_now              48565 non-null  float64\n",
      " 22  post_age             48565 non-null  float64\n",
      "dtypes: bool(6), float64(4), int64(2), object(11)\n",
      "memory usage: 6.6+ MB\n"
     ]
    }
   ],
   "source": [
    "# Load from \"db\"\n",
    "db = pd.read_csv('data/startingover.csv')\n",
    "db.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2759ec8-a6f9-43fc-926e-8fb85edf49df",
   "metadata": {},
   "source": [
    "'num_comments' is going to be the target, let's get a closer look at the distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4a036089-f235-4a48-b57a-6b5f7a8f598d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:40.740085Z",
     "iopub.status.busy": "2022-06-07T15:25:40.739890Z",
     "iopub.status.idle": "2022-06-07T15:25:41.471046Z",
     "shell.execute_reply": "2022-06-07T15:25:41.470383Z",
     "shell.execute_reply.started": "2022-06-07T15:25:40.740063Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count    48565.000000\n",
      "mean        84.723463\n",
      "std        346.739562\n",
      "min          0.000000\n",
      "25%         10.000000\n",
      "50%         26.000000\n",
      "75%         69.000000\n",
      "max      27985.000000\n",
      "Name: num_comments, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(db.num_comments.describe())\n",
    "sns.histplot(db.num_comments,log_scale=(False,True),bins=50);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "839e5d30-ab8f-4871-8191-20cf3b1b7c2d",
   "metadata": {},
   "source": [
    "This appears to be heavily impacted by outliers, I'll pick a cutoff at 6000 comments and see where that gets us"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0e5a5c07-51c4-4251-a955-8a16c9500fad",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:41.471990Z",
     "iopub.status.busy": "2022-06-07T15:25:41.471813Z",
     "iopub.status.idle": "2022-06-07T15:25:41.478361Z",
     "shell.execute_reply": "2022-06-07T15:25:41.477689Z",
     "shell.execute_reply.started": "2022-06-07T15:25:41.471973Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(db[db.num_comments>6000])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e465633-ebbd-4497-8b27-52ad0aa48048",
   "metadata": {},
   "source": [
    "There are some extreme outliers here, they're skewing the data and there are so few of them that we won't miss them at all. So we'll drop and re-plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4a028cd9-0e67-4e35-865d-9f2cf1fbc23f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:41.479374Z",
     "iopub.status.busy": "2022-06-07T15:25:41.479182Z",
     "iopub.status.idle": "2022-06-07T15:25:41.912305Z",
     "shell.execute_reply": "2022-06-07T15:25:41.911570Z",
     "shell.execute_reply.started": "2022-06-07T15:25:41.479357Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count    48544.000000\n",
      "mean        79.740957\n",
      "std        223.601340\n",
      "min          0.000000\n",
      "25%         10.000000\n",
      "50%         26.000000\n",
      "75%         68.250000\n",
      "max       5876.000000\n",
      "Name: num_comments, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "db = db.drop(db[db.num_comments>6000].index)\n",
    "print(db.num_comments.describe())\n",
    "sns.histplot(db.num_comments,log_scale=(False,True),bins=50);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8da9e6ae-24f5-4fc1-b6d6-2ad382a32fcd",
   "metadata": {},
   "source": [
    "Much clearer picture, also I put the plots on a log scale so we can actually see the distribution, otherwise it'd just be a massive bar at 0 and it would push everything else so far down that you can't see anything. I could probably go further but I don't want to misrepresent the data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebe836cb-249b-4b4c-bde6-a6637a847063",
   "metadata": {},
   "source": [
    "## Comparing Features\n",
    "There are a few features that jumped out at me as interesting:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d93d2f88-6cf0-43b9-b347-f392c98c350e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:41.913362Z",
     "iopub.status.busy": "2022-06-07T15:25:41.913187Z",
     "iopub.status.idle": "2022-06-07T15:25:41.921295Z",
     "shell.execute_reply": "2022-06-07T15:25:41.920552Z",
     "shell.execute_reply.started": "2022-06-07T15:25:41.913345Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Out of 48544 total posts...\n",
      "--------------------------------\n",
      "2495 posts are self posts\n",
      "1001 posts are NSFW (18+)\n",
      "866 posts are marked as spoilers\n",
      "830 posts are of original content\n",
      "212 posts are locked\n",
      "145 posts are stickied\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(f'\\\n",
    "Out of {len(db)} total posts...\\n\\\n",
    "--------------------------------\\n\\\n",
    "{db.is_self.value_counts()[True]} posts are self posts\\n\\\n",
    "{db.over_18.value_counts()[True]} posts are NSFW (18+)\\n\\\n",
    "{db.spoiler.value_counts()[True]} posts are marked as spoilers\\n\\\n",
    "{db.is_original_content.value_counts()[True]} posts are of original content\\n\\\n",
    "{db.locked.value_counts()[True]} posts are locked\\n\\\n",
    "{db.stickied.value_counts()[True]} posts are stickied\\n\\\n",
    "')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05ce41b2-5669-4d0b-a4d5-ff8d8d7171cb",
   "metadata": {},
   "source": [
    "While the number of these posts compared to the total posts isn't significant I feel that they can only add (not much) to the accuracy of the model. They only add one column each so it's cheap as well. If I had more time I would probably create a column for has_flair as well."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d79c7d53-1ee3-4180-b40f-1069a7f85ae1",
   "metadata": {},
   "source": [
    "## Numerics vs Target\n",
    "Some numeric columns I would like to include are score, post age, upvote ratio, and number of comments (which will become the target). Let's get an idea for what's going on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "252bb5a6-d24a-4ef2-b093-3a9c780c3812",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:41.922293Z",
     "iopub.status.busy": "2022-06-07T15:25:41.922118Z",
     "iopub.status.idle": "2022-06-07T15:25:50.783370Z",
     "shell.execute_reply": "2022-06-07T15:25:50.782637Z",
     "shell.execute_reply.started": "2022-06-07T15:25:41.922275Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count     48544.000000\n",
      "mean       2130.988176\n",
      "std        6702.179836\n",
      "min          45.000000\n",
      "25%         263.000000\n",
      "50%         568.000000\n",
      "75%        1465.000000\n",
      "max      193501.000000\n",
      "Name: score, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(db.score.describe())\n",
    "sns.jointplot(x=db.score/100,y=db.num_comments/100,kind='reg');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a366340c-d4b8-4a42-a067-23c1cbdd74ba",
   "metadata": {},
   "source": [
    "Both axes divided by 100 to make it easier to read\n",
    "\n",
    "Score is a strong predictor of number of comments, the highest scoring posts are almost guaranteed to have an above-median number of comments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3179bf66-9c82-4e7a-82c0-c534c5fc6159",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:50.784680Z",
     "iopub.status.busy": "2022-06-07T15:25:50.784339Z",
     "iopub.status.idle": "2022-06-07T15:25:55.975570Z",
     "shell.execute_reply": "2022-06-07T15:25:55.975060Z",
     "shell.execute_reply.started": "2022-06-07T15:25:50.784655Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count     48544.000000\n",
      "mean      59368.201209\n",
      "std       23001.003540\n",
      "min       14846.543459\n",
      "25%       41004.177545\n",
      "50%       57975.297003\n",
      "75%       76686.219161\n",
      "max      101274.168406\n",
      "Name: post_age, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(db.post_age.describe())\n",
    "sns.jointplot(x=db.post_age,y=db.num_comments, kind='reg');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d9922a6-e7cf-4513-8dca-0bfd1aa33447",
   "metadata": {},
   "source": [
    "It could be clearer, but there is some correlation with age and post count. You can also see how sparse super hot posts actually are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b0c00c9b-0e22-411f-8fdf-13c06d2ae877",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:55.976540Z",
     "iopub.status.busy": "2022-06-07T15:25:55.976347Z",
     "iopub.status.idle": "2022-06-07T15:25:55.986845Z",
     "shell.execute_reply": "2022-06-07T15:25:55.986201Z",
     "shell.execute_reply.started": "2022-06-07T15:25:55.976523Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>subreddit</th>\n",
       "      <th>num_comments</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>38037</th>\n",
       "      <td>to push past armed courtroom guards</td>\n",
       "      <td>therewasanattempt</td>\n",
       "      <td>5876</td>\n",
       "      <td>72261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36183</th>\n",
       "      <td>Avs VS Oilers Western Conference Finals Game 4...</td>\n",
       "      <td>ColoradoAvalanche</td>\n",
       "      <td>5851</td>\n",
       "      <td>300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33841</th>\n",
       "      <td>Live WWE RAW Discussion Thread! - June 6th, 2022!</td>\n",
       "      <td>SquaredCircle</td>\n",
       "      <td>5682</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36694</th>\n",
       "      <td>What would you never tell your current partner?</td>\n",
       "      <td>AskMen</td>\n",
       "      <td>5679</td>\n",
       "      <td>10159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1181</th>\n",
       "      <td>Nearly half of families with kids can no longe...</td>\n",
       "      <td>news</td>\n",
       "      <td>5464</td>\n",
       "      <td>60516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28900</th>\n",
       "      <td>Ohio House Republicans vote to put Canada on a...</td>\n",
       "      <td>nottheonion</td>\n",
       "      <td>5389</td>\n",
       "      <td>53999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39946</th>\n",
       "      <td>Elon Musk asserts his \"right to terminate\" Twi...</td>\n",
       "      <td>technology</td>\n",
       "      <td>5369</td>\n",
       "      <td>28363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28235</th>\n",
       "      <td>Prince Louis of Cambridge</td>\n",
       "      <td>funny</td>\n",
       "      <td>5334</td>\n",
       "      <td>104033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32875</th>\n",
       "      <td>\"Everybody is trying to blame us\"</td>\n",
       "      <td>PublicFreakout</td>\n",
       "      <td>5230</td>\n",
       "      <td>89886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7931</th>\n",
       "      <td>My GF’s friend stayed with us last weekend (fo...</td>\n",
       "      <td>iamverybadass</td>\n",
       "      <td>5173</td>\n",
       "      <td>24474</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   title          subreddit  \\\n",
       "38037                to push past armed courtroom guards  therewasanattempt   \n",
       "36183  Avs VS Oilers Western Conference Finals Game 4...  ColoradoAvalanche   \n",
       "33841  Live WWE RAW Discussion Thread! - June 6th, 2022!      SquaredCircle   \n",
       "36694    What would you never tell your current partner?             AskMen   \n",
       "1181   Nearly half of families with kids can no longe...               news   \n",
       "28900  Ohio House Republicans vote to put Canada on a...        nottheonion   \n",
       "39946  Elon Musk asserts his \"right to terminate\" Twi...         technology   \n",
       "28235                          Prince Louis of Cambridge              funny   \n",
       "32875                  \"Everybody is trying to blame us\"     PublicFreakout   \n",
       "7931   My GF’s friend stayed with us last weekend (fo...      iamverybadass   \n",
       "\n",
       "       num_comments   score  \n",
       "38037          5876   72261  \n",
       "36183          5851     300  \n",
       "33841          5682     128  \n",
       "36694          5679   10159  \n",
       "1181           5464   60516  \n",
       "28900          5389   53999  \n",
       "39946          5369   28363  \n",
       "28235          5334  104033  \n",
       "32875          5230   89886  \n",
       "7931           5173   24474  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "db[db.num_comments>4000].sort_values('num_comments',ascending=False)[['title','subreddit','num_comments','score']].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8f94abd-f480-4ddc-9ec3-74e0f5e80b53",
   "metadata": {},
   "source": [
    "I expected to see mostly news here, and while news and current events is here (30% in my case at time of writing) the rest of it is drastically different. Anything can go viral it seems"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fde30375-0763-4d2c-88e3-5a5c516cb145",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:55.988879Z",
     "iopub.status.busy": "2022-06-07T15:25:55.988164Z",
     "iopub.status.idle": "2022-06-07T15:25:56.001194Z",
     "shell.execute_reply": "2022-06-07T15:25:56.000621Z",
     "shell.execute_reply.started": "2022-06-07T15:25:55.988838Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>subreddit</th>\n",
       "      <th>num_comments</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>46529</th>\n",
       "      <td>More of this please.</td>\n",
       "      <td>MadeMeSmile</td>\n",
       "      <td>5146</td>\n",
       "      <td>157009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47421</th>\n",
       "      <td>Helicopter footage of a loose cow being wrangl...</td>\n",
       "      <td>interestingasfuck</td>\n",
       "      <td>4347</td>\n",
       "      <td>126608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28235</th>\n",
       "      <td>Prince Louis of Cambridge</td>\n",
       "      <td>funny</td>\n",
       "      <td>5334</td>\n",
       "      <td>104033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16638</th>\n",
       "      <td>This $10 salad I paid for at a restaurant</td>\n",
       "      <td>mildlyinfuriating</td>\n",
       "      <td>4336</td>\n",
       "      <td>103858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32875</th>\n",
       "      <td>\"Everybody is trying to blame us\"</td>\n",
       "      <td>PublicFreakout</td>\n",
       "      <td>5230</td>\n",
       "      <td>89886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22957</th>\n",
       "      <td>Even the military knows assault rifles belong ...</td>\n",
       "      <td>WhitePeopleTwitter</td>\n",
       "      <td>4047</td>\n",
       "      <td>80801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38037</th>\n",
       "      <td>to push past armed courtroom guards</td>\n",
       "      <td>therewasanattempt</td>\n",
       "      <td>5876</td>\n",
       "      <td>72261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1181</th>\n",
       "      <td>Nearly half of families with kids can no longe...</td>\n",
       "      <td>news</td>\n",
       "      <td>5464</td>\n",
       "      <td>60516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19201</th>\n",
       "      <td>It Costs $110,000 to Fully Gear-Up in Diablo I...</td>\n",
       "      <td>technology</td>\n",
       "      <td>5150</td>\n",
       "      <td>58244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11976</th>\n",
       "      <td>Electric Vehicles are measurably reducing glob...</td>\n",
       "      <td>technology</td>\n",
       "      <td>4120</td>\n",
       "      <td>55080</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   title           subreddit  \\\n",
       "46529                               More of this please.         MadeMeSmile   \n",
       "47421  Helicopter footage of a loose cow being wrangl...   interestingasfuck   \n",
       "28235                          Prince Louis of Cambridge               funny   \n",
       "16638          This $10 salad I paid for at a restaurant   mildlyinfuriating   \n",
       "32875                  \"Everybody is trying to blame us\"      PublicFreakout   \n",
       "22957  Even the military knows assault rifles belong ...  WhitePeopleTwitter   \n",
       "38037                to push past armed courtroom guards   therewasanattempt   \n",
       "1181   Nearly half of families with kids can no longe...                news   \n",
       "19201  It Costs $110,000 to Fully Gear-Up in Diablo I...          technology   \n",
       "11976  Electric Vehicles are measurably reducing glob...          technology   \n",
       "\n",
       "       num_comments   score  \n",
       "46529          5146  157009  \n",
       "47421          4347  126608  \n",
       "28235          5334  104033  \n",
       "16638          4336  103858  \n",
       "32875          5230   89886  \n",
       "22957          4047   80801  \n",
       "38037          5876   72261  \n",
       "1181           5464   60516  \n",
       "19201          5150   58244  \n",
       "11976          4120   55080  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "db[db.num_comments>4000].sort_values('score',ascending=False)[['title','subreddit','num_comments','score']].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "523f31c6-7fdf-4079-8621-32574d400879",
   "metadata": {},
   "source": [
    "Sorting by score is a similar story. This is where machine learning really blows my mind, there's no apparent correlation here but somehow it manages to find it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "75749905-250d-41aa-90fc-16cd06be8e73",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:25:56.002307Z",
     "iopub.status.busy": "2022-06-07T15:25:56.001959Z",
     "iopub.status.idle": "2022-06-07T15:26:01.321549Z",
     "shell.execute_reply": "2022-06-07T15:26:01.321049Z",
     "shell.execute_reply.started": "2022-06-07T15:25:56.002277Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count    48544.000000\n",
      "mean         0.963388\n",
      "std          0.041302\n",
      "min          0.510000\n",
      "25%          0.950000\n",
      "50%          0.980000\n",
      "75%          0.990000\n",
      "max          1.000000\n",
      "Name: upvote_ratio, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(db.upvote_ratio.describe())\n",
    "sns.jointplot(x=db.upvote_ratio,y=db.num_comments, kind='reg');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fcffe77-4aa6-4df3-a4bd-bc020a112c12",
   "metadata": {},
   "source": [
    "Upvote ratio goes down as the number of comments increases, at first I thought this seemed backwards but I guess the majority of reddit comments are of such low quality that it drives the metric down into the dirt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af0cc9fa-7ba4-4579-b972-91102ea8ba0e",
   "metadata": {},
   "source": [
    "## Create Working Dataframes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92c7db6d-1915-4161-9ffc-7bb6763cf064",
   "metadata": {},
   "source": [
    "Let's put it in a dataframe so we can work with it. And also drop any NAs that appear (I don't see any, but I don't want any if they appear in the future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "20e22840-02f1-4d8e-8ee3-73835863f4a6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-07T15:26:01.323685Z",
     "iopub.status.busy": "2022-06-07T15:26:01.323365Z",
     "iopub.status.idle": "2022-06-07T15:26:01.619933Z",
     "shell.execute_reply": "2022-06-07T15:26:01.619372Z",
     "shell.execute_reply.started": "2022-06-07T15:26:01.323665Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "db[['title','subreddit','over_18','is_original_content','is_self','spoiler',\\\n",
    "         'locked','stickied','num_comments']].dropna().to_csv('data/workingdf.csv',index=False)\n",
    "\n",
    "db[['score','post_age','upvote_ratio']].to_csv('data/numerics.csv',index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "154b0f51-a46a-47a1-b73b-0d7f1f1f8f57",
   "metadata": {},
   "source": [
    "Next, we [clean](clean.ipynb)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}