hn_post_times.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# When are HackerNews Stories Posted?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T06:50:03.519385Z",
     "start_time": "2020-06-09T06:50:01.550739Z"
    }
   },
   "outputs": [],
   "source": [
    "import calendar\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T06:50:03.531033Z",
     "start_time": "2020-06-09T06:50:03.521323Z"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "plt.style.use(\"seaborn-whitegrid\")\n",
    "plt.rcParams['figure.figsize'] = [20.0, 4.0]\n",
    "plt.rcParams['axes.titlesize'] = 30\n",
    "plt.rcParams['axes.labelsize'] = 28\n",
    "plt.rcParams['xtick.labelsize'] = 24\n",
    "plt.rcParams['ytick.labelsize'] = 24\n",
    "plt.rcParams['legend.fontsize'] = 24\n",
    "colors = [i['color'] for i in plt.rcParams['axes.prop_cycle']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data was grabbed from the BigQuery database of HN, found [here](https://console.cloud.google.com/marketplace/details/y-combinator/hacker-news?filter=solution-type:dataset&q=hacker%20news&id=5227103e-0eb9-4744-872b-325a8df50bee).\n",
    "\n",
    "The query was:\n",
    "\n",
    "```SQL\n",
    "SELECT `timestamp`, `points` FROM `bigquery-public-data.hacker_news.full` WHERE type='story'\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T18:36:25.736912Z",
     "start_time": "2020-06-09T18:36:25.440291Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "timestamp,score\r\n",
      "2012-08-03 17:25:36 UTC,123\r\n",
      "2013-10-30 16:25:31 UTC,20\r\n",
      "2013-10-23 17:51:06 UTC,18\r\n",
      "2016-01-11 20:02:34 UTC,13\r\n",
      "2016-03-01 05:37:21 UTC,21\r\n",
      "2019-03-20 19:17:33 UTC,409\r\n",
      "2009-10-22 01:08:43 UTC,30\r\n",
      "2013-08-13 18:25:43 UTC,23\r\n",
      "2014-01-03 01:49:30 UTC,12\r\n"
     ]
    }
   ],
   "source": [
    "!head /Users/jessime.kirk/Data/hn_post_time2.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T19:21:23.404216Z",
     "start_time": "2020-06-09T19:06:04.241401Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3733751, 2)\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-08-03 17:25:36+00:00</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-10-30 16:25:31+00:00</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-10-23 17:51:06+00:00</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-11 20:02:34+00:00</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-03-01 05:37:21+00:00</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  timestamp  score\n",
       "0 2012-08-03 17:25:36+00:00  123.0\n",
       "1 2013-10-30 16:25:31+00:00   20.0\n",
       "2 2013-10-23 17:51:06+00:00   18.0\n",
       "3 2016-01-11 20:02:34+00:00   13.0\n",
       "4 2016-03-01 05:37:21+00:00   21.0"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv_path = '/Users/jessime.kirk/Data/hn_post_time2.csv'\n",
    "df = pd.read_csv(csv_path)\n",
    "df['timestamp'] = df['timestamp'].apply(pd.to_datetime)\n",
    "print(df.shape)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T21:08:04.490336Z",
     "start_time": "2020-06-09T21:08:04.300449Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<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>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3548668.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>12.034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>51.614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>6015.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            score\n",
       "count 3548668.000\n",
       "mean       12.034\n",
       "std        51.614\n",
       "min        -1.000\n",
       "25%         1.000\n",
       "50%         2.000\n",
       "75%         3.000\n",
       "max      6015.000"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.float_format', lambda x: '%.3f' % x)\n",
    "pd.DataFrame(df['score'].describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T18:52:20.430520Z",
     "start_time": "2020-06-09T18:52:19.786587Z"
    }
   },
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 1440x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "capped = df['score'].copy()\n",
    "capped[capped > 10] = 10\n",
    "sns.distplot(capped.dropna(), kde=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-08T06:09:27.413116Z",
     "start_time": "2020-06-08T06:09:27.407080Z"
    }
   },
   "source": [
    "## Plot TimeSeries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T19:24:57.313783Z",
     "start_time": "2020-06-09T19:24:57.248064Z"
    }
   },
   "outputs": [],
   "source": [
    "df = df.set_index('timestamp')\n",
    "df['count'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T08:53:06.275904Z",
     "start_time": "2020-06-09T08:53:03.718005Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "resamp = df['count'].resample('M').sum()\n",
    "plt.plot(resamp[:-1]) # Drop this month since we're near the beginning\n",
    "plt.ylabel('count')\n",
    "plt.xlabel('month')\n",
    "plt.tight_layout()\n",
    "plt.savefig('/Users/jessime.kirk/Pictures/hn_ts.png', bbox_inches='tight', pad_inches=.5, dpi=150)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Frequency by Weekday"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T19:25:02.629608Z",
     "start_time": "2020-06-09T19:25:02.121300Z"
    }
   },
   "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>score</th>\n",
       "      <th>count</th>\n",
       "      <th>day</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>timestamp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-08-03 17:25:36+00:00</th>\n",
       "      <td>123.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10-30 16:25:31+00:00</th>\n",
       "      <td>20.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10-23 17:51:06+00:00</th>\n",
       "      <td>18.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11 20:02:34+00:00</th>\n",
       "      <td>13.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-01 05:37:21+00:00</th>\n",
       "      <td>21.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           score  count  day  hour\n",
       "timestamp                                         \n",
       "2012-08-03 17:25:36+00:00  123.0      1  4.0  17.0\n",
       "2013-10-30 16:25:31+00:00   20.0      1  2.0  16.0\n",
       "2013-10-23 17:51:06+00:00   18.0      1  2.0  17.0\n",
       "2016-01-11 20:02:34+00:00   13.0      1  0.0  20.0\n",
       "2016-03-01 05:37:21+00:00   21.0      1  1.0   5.0"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['day'] = df.index.weekday\n",
    "df['hour'] = df.index.hour\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T08:52:38.316804Z",
     "start_time": "2020-06-09T08:52:37.887844Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "day2name = dict(zip(range(7), calendar.day_name))\n",
    "\n",
    "by_day = pd.DataFrame(df.groupby('day')['day'].count())\n",
    "\n",
    "by_day = by_day.rename(columns={'day': 'count'}).reset_index()\n",
    "by_day['day'] = by_day['day'].apply(lambda x: day2name[x])\n",
    "\n",
    "sns.catplot(x=\"day\", y=\"count\", height=4, aspect=2, data=by_day, kind=\"bar\")\n",
    "plt.xticks(rotation=90)\n",
    "plt.savefig('/Users/jessime.kirk/Pictures/hn_day_count.png', bbox_inches='tight', pad_inches=.5, dpi=150)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Breakdown by hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T19:26:39.775827Z",
     "start_time": "2020-06-09T19:26:39.363660Z"
    }
   },
   "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>day_int</th>\n",
       "      <th>hour</th>\n",
       "      <th>count</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13195</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13419</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13686</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>13444</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13772</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   day_int  hour  count     day\n",
       "0      0.0   0.0  13195  Monday\n",
       "1      0.0   1.0  13419  Monday\n",
       "2      0.0   2.0  13686  Monday\n",
       "3      0.0   3.0  13444  Monday\n",
       "4      0.0   4.0  13772  Monday"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_day_hour = pd.DataFrame(df.groupby(['day', 'hour'])['hour'].count())\n",
    "by_day_hour = by_day_hour.rename(columns={'hour': 'count'}).reset_index().rename(columns={'day': 'day_int'})\n",
    "by_day_hour['day'] = by_day_hour['day_int'].apply(lambda x: day2name[x])\n",
    "by_day_hour.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T08:52:56.905490Z",
     "start_time": "2020-06-09T08:52:55.128084Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1653.28x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"hour\", y=\"count\", hue=\"day\", height=4, aspect=5, data=by_day_hour, kind=\"bar\")\n",
    "plt.xlabel('hour (UTC)')\n",
    "plt.savefig('/Users/jessime.kirk/Pictures/hn_day_hour_count.png', bbox_inches='tight', pad_inches=.5, dpi=150)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Relationship with score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T20:18:54.959599Z",
     "start_time": "2020-06-09T20:18:54.522142Z"
    }
   },
   "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>day_int</th>\n",
       "      <th>hour</th>\n",
       "      <th>score</th>\n",
       "      <th>std</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.511150</td>\n",
       "      <td>49.987305</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>15.626649</td>\n",
       "      <td>58.535864</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>14.246753</td>\n",
       "      <td>51.245476</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>13.823850</td>\n",
       "      <td>52.692747</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>12.274368</td>\n",
       "      <td>42.950746</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   day_int  hour      score        std     day\n",
       "0      0.0     0  14.511150  49.987305  Monday\n",
       "1      0.0     1  15.626649  58.535864  Monday\n",
       "2      0.0     2  14.246753  51.245476  Monday\n",
       "3      0.0     3  13.823850  52.692747  Monday\n",
       "4      0.0     4  12.274368  42.950746  Monday"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_dh_score = pd.DataFrame(df.groupby(['day', 'hour'])['score'].mean()) \n",
    "by_dh_score['std'] = df.groupby(['day', 'hour'])['score'].std()\n",
    "by_dh_score = by_dh_score.reset_index().rename(columns={'day': 'day_int'})\n",
    "by_dh_score['day'] = by_dh_score['day_int'].apply(lambda x: day2name[x])\n",
    "by_dh_score['hour'] = by_dh_score['hour'].astype(int)\n",
    "by_dh_score.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-09T21:28:38.183708Z",
     "start_time": "2020-06-09T21:28:35.871851Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1653.28x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x=\"hour\", y=\"score\", hue=\"day\", height=4, aspect=5, data=by_dh_score, kind=\"bar\")\n",
    "plt.xlabel('hour (UTC)')\n",
    "plt.savefig('/Users/jessime.kirk/Pictures/by_dh_score.png', bbox_inches='tight', pad_inches=.5, dpi=150)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}