hn_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns; sns.set()\n",
    "import matplotlib.pyplot as plt\n",
    "import pytz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {},
   "outputs": [],
   "source": [
    "#read in data\n",
    "hn = pd.read_csv('hn_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 386,
   "metadata": {},
   "outputs": [],
   "source": [
    "#resort by upvotes and reset index\n",
    "hn_data = hn.sort_values(by = 'stories_score', ascending = False).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 389,
   "metadata": {},
   "outputs": [],
   "source": [
    "#make stories time column consist of timestamp objects\n",
    "hn_data['stories_time'] = pd.to_datetime(hn_data['stories_unix'], unit = 's')\n",
    "#add a day of the week column\n",
    "hn_data['stories_day'] = hn_data['stories_time'].dt.day_name()\n",
    "#drop unix column\n",
    "hn_data = hn_data.drop(columns = 'stories_unix')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>stories_score</th>\n",
       "      <th>stories_title</th>\n",
       "      <th>stories_time</th>\n",
       "      <th>stories_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6015</td>\n",
       "      <td>Stephen Hawking has died</td>\n",
       "      <td>2018-03-14 03:50:30</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5771</td>\n",
       "      <td>A Message to Our Customers</td>\n",
       "      <td>2016-02-17 08:38:37</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4338</td>\n",
       "      <td>Steve Jobs has passed away.</td>\n",
       "      <td>2011-10-05 23:42:23</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4107</td>\n",
       "      <td>Reflecting on one very, very strange year at Uber</td>\n",
       "      <td>2017-02-19 21:16:33</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3531</td>\n",
       "      <td>Show HN: This up votes itself</td>\n",
       "      <td>2012-03-23 00:40:39</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3384</td>\n",
       "      <td>F.C.C. Repeals Net Neutrality Rules</td>\n",
       "      <td>2017-12-14 18:13:35</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3238</td>\n",
       "      <td>Cloudflare Reverse Proxies Are Dumping Uniniti...</td>\n",
       "      <td>2017-02-23 23:05:08</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3125</td>\n",
       "      <td>UK votes to leave EU</td>\n",
       "      <td>2016-06-24 03:48:57</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3086</td>\n",
       "      <td>Tim Cook Speaks Up</td>\n",
       "      <td>2014-10-30 11:12:23</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3030</td>\n",
       "      <td>Announcing the first SHA-1 collision</td>\n",
       "      <td>2017-02-23 13:01:08</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>3015</td>\n",
       "      <td>I Sell Onions on the Internet</td>\n",
       "      <td>2019-04-23 13:00:24</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3001</td>\n",
       "      <td>macOS High Sierra: Anyone can login as “root” ...</td>\n",
       "      <td>2017-11-28 19:41:10</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2968</td>\n",
       "      <td>SpaceX’s Falcon Heavy successfully launches</td>\n",
       "      <td>2018-02-06 20:57:15</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2903</td>\n",
       "      <td>2048</td>\n",
       "      <td>2014-03-10 15:44:42</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2901</td>\n",
       "      <td>Paul Allen has died</td>\n",
       "      <td>2018-10-15 22:00:14</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2873</td>\n",
       "      <td>Microsoft Is Said to Have Agreed to Acquire Gi...</td>\n",
       "      <td>2018-06-03 20:14:26</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2867</td>\n",
       "      <td>Announcing unlimited free private repos</td>\n",
       "      <td>2019-01-07 17:03:59</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2744</td>\n",
       "      <td>Don't Fly During Ramadan</td>\n",
       "      <td>2013-08-22 17:10:57</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2735</td>\n",
       "      <td>W3C abandons consensus, standardizes DRM, EFF ...</td>\n",
       "      <td>2017-09-18 19:45:08</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2699</td>\n",
       "      <td>CIA malware and hacking tools</td>\n",
       "      <td>2017-03-07 13:10:56</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2690</td>\n",
       "      <td>Show HN: A retro video game console I've been ...</td>\n",
       "      <td>2019-03-14 20:25:03</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2666</td>\n",
       "      <td>Hyperloop</td>\n",
       "      <td>2013-08-12 20:29:01</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2611</td>\n",
       "      <td>IBM acquires Red Hat</td>\n",
       "      <td>2018-10-28 17:57:59</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2589</td>\n",
       "      <td>Ask HN: Is S3 down?</td>\n",
       "      <td>2017-02-28 17:45:58</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2585</td>\n",
       "      <td>Linus Torvalds apologizes for his behavior, ta...</td>\n",
       "      <td>2018-09-16 19:44:57</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2553</td>\n",
       "      <td>Pardon Snowden</td>\n",
       "      <td>2016-09-14 08:31:15</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2493</td>\n",
       "      <td>The Big Hack: How China Used a Tiny Chip to In...</td>\n",
       "      <td>2018-10-04 09:21:28</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2475</td>\n",
       "      <td>Be Kind</td>\n",
       "      <td>2016-10-14 12:26:46</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2444</td>\n",
       "      <td>No Thank You, Mr. Pecker</td>\n",
       "      <td>2019-02-07 22:52:16</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2381</td>\n",
       "      <td>Tell HN: New features and a moderator</td>\n",
       "      <td>2016-07-11 19:34:57</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135774</th>\n",
       "      <td>0</td>\n",
       "      <td>Spain Youth Unemployment Rises To Record 57.7%</td>\n",
       "      <td>2014-01-16 10:45:18</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135775</th>\n",
       "      <td>0</td>\n",
       "      <td>5 Lame Deaths In Comic Books</td>\n",
       "      <td>2010-07-23 10:21:46</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135776</th>\n",
       "      <td>0</td>\n",
       "      <td>Twitter Hashtag Connection Graph</td>\n",
       "      <td>2014-05-04 08:10:12</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135777</th>\n",
       "      <td>0</td>\n",
       "      <td>Import and convert MOD to iPhone(iPhone 4) on ...</td>\n",
       "      <td>2010-07-15 08:12:19</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135778</th>\n",
       "      <td>0</td>\n",
       "      <td>Placeholder</td>\n",
       "      <td>2014-05-31 18:42:20</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135779</th>\n",
       "      <td>0</td>\n",
       "      <td>Be Inspired (By Everything) 01</td>\n",
       "      <td>2010-06-21 15:06:21</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135780</th>\n",
       "      <td>0</td>\n",
       "      <td>Free Valentine's Gifts From Doodels</td>\n",
       "      <td>2013-02-07 00:29:53</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135781</th>\n",
       "      <td>0</td>\n",
       "      <td>Nike Air Force 1 07 Black Black Varsity Red</td>\n",
       "      <td>2010-06-08 08:40:22</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135782</th>\n",
       "      <td>0</td>\n",
       "      <td>Google Translate</td>\n",
       "      <td>2013-12-22 11:11:00</td>\n",
       "      <td>Sunday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135783</th>\n",
       "      <td>0</td>\n",
       "      <td>But I want to be a rocket scientist...</td>\n",
       "      <td>2013-06-29 16:41:13</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135784</th>\n",
       "      <td>0</td>\n",
       "      <td>Keevoice</td>\n",
       "      <td>2013-12-24 10:53:20</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135785</th>\n",
       "      <td>0</td>\n",
       "      <td>Timetric - the economic data you need right now</td>\n",
       "      <td>2010-12-04 16:54:58</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135786</th>\n",
       "      <td>0</td>\n",
       "      <td>JinX - The Javascript Includer Wordpress Plugin</td>\n",
       "      <td>2010-07-20 17:02:40</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135787</th>\n",
       "      <td>0</td>\n",
       "      <td>À la découverte des soins orientaux à Essaouira</td>\n",
       "      <td>2013-02-25 15:51:23</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135788</th>\n",
       "      <td>0</td>\n",
       "      <td>Red tide spawns blue light show at night on Sa...</td>\n",
       "      <td>2011-09-30 06:33:07</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135789</th>\n",
       "      <td>0</td>\n",
       "      <td>����</td>\n",
       "      <td>2011-03-24 22:25:20</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135790</th>\n",
       "      <td>0</td>\n",
       "      <td>Online jobs</td>\n",
       "      <td>2011-07-30 06:56:01</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135791</th>\n",
       "      <td>0</td>\n",
       "      <td>E-Civil 2014: Jornadas de Engenharia Civil</td>\n",
       "      <td>2014-03-17 11:41:51</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135792</th>\n",
       "      <td>0</td>\n",
       "      <td>Show HN: Chrome Extension: Cloud Assistant for...</td>\n",
       "      <td>2017-09-27 17:29:18</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135793</th>\n",
       "      <td>0</td>\n",
       "      <td>PHP BDD is now \"nice\"</td>\n",
       "      <td>2012-08-25 09:51:02</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135794</th>\n",
       "      <td>0</td>\n",
       "      <td>Kontest reboots its popular Facebook Contest P...</td>\n",
       "      <td>2012-10-02 07:24:23</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135795</th>\n",
       "      <td>0</td>\n",
       "      <td>Global Logistics Media - Damco the Movie</td>\n",
       "      <td>2012-02-27 03:59:28</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135796</th>\n",
       "      <td>0</td>\n",
       "      <td>Landslide</td>\n",
       "      <td>2013-02-07 10:57:31</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135797</th>\n",
       "      <td>0</td>\n",
       "      <td>Prediksi Skor Estonia vs Belarus</td>\n",
       "      <td>2013-06-03 03:22:12</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135798</th>\n",
       "      <td>0</td>\n",
       "      <td>How To Find A Starving Crowd of Hungry Buyers</td>\n",
       "      <td>2014-01-16 11:10:35</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135799</th>\n",
       "      <td>0</td>\n",
       "      <td>Final Dergisi Dershaneleri - Sınav Giriş Kartı</td>\n",
       "      <td>2013-12-31 14:37:18</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135800</th>\n",
       "      <td>0</td>\n",
       "      <td>Matt Cutts Talks About The Google Algorithm</td>\n",
       "      <td>2014-01-16 10:17:45</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135801</th>\n",
       "      <td>0</td>\n",
       "      <td>Youmexvideo - Online Video Entertainment</td>\n",
       "      <td>2012-12-01 16:28:42</td>\n",
       "      <td>Saturday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135802</th>\n",
       "      <td>0</td>\n",
       "      <td>How many ways can you mess up IO?</td>\n",
       "      <td>2015-01-06 20:20:51</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3135803</th>\n",
       "      <td>-1</td>\n",
       "      <td>The DevOps Democracy</td>\n",
       "      <td>2015-11-13 16:14:14</td>\n",
       "      <td>Friday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3135804 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         stories_score                                      stories_title  \\\n",
       "0                 6015                           Stephen Hawking has died   \n",
       "1                 5771                         A Message to Our Customers   \n",
       "2                 4338                        Steve Jobs has passed away.   \n",
       "3                 4107  Reflecting on one very, very strange year at Uber   \n",
       "4                 3531                      Show HN: This up votes itself   \n",
       "5                 3384                F.C.C. Repeals Net Neutrality Rules   \n",
       "6                 3238  Cloudflare Reverse Proxies Are Dumping Uniniti...   \n",
       "7                 3125                               UK votes to leave EU   \n",
       "8                 3086                                 Tim Cook Speaks Up   \n",
       "9                 3030               Announcing the first SHA-1 collision   \n",
       "10                3015                      I Sell Onions on the Internet   \n",
       "11                3001  macOS High Sierra: Anyone can login as “root” ...   \n",
       "12                2968        SpaceX’s Falcon Heavy successfully launches   \n",
       "13                2903                                               2048   \n",
       "14                2901                                Paul Allen has died   \n",
       "15                2873  Microsoft Is Said to Have Agreed to Acquire Gi...   \n",
       "16                2867            Announcing unlimited free private repos   \n",
       "17                2744                           Don't Fly During Ramadan   \n",
       "18                2735  W3C abandons consensus, standardizes DRM, EFF ...   \n",
       "19                2699                      CIA malware and hacking tools   \n",
       "20                2690  Show HN: A retro video game console I've been ...   \n",
       "21                2666                                          Hyperloop   \n",
       "22                2611                               IBM acquires Red Hat   \n",
       "23                2589                                Ask HN: Is S3 down?   \n",
       "24                2585  Linus Torvalds apologizes for his behavior, ta...   \n",
       "25                2553                                     Pardon Snowden   \n",
       "26                2493  The Big Hack: How China Used a Tiny Chip to In...   \n",
       "27                2475                                            Be Kind   \n",
       "28                2444                           No Thank You, Mr. Pecker   \n",
       "29                2381              Tell HN: New features and a moderator   \n",
       "...                ...                                                ...   \n",
       "3135774              0     Spain Youth Unemployment Rises To Record 57.7%   \n",
       "3135775              0                       5 Lame Deaths In Comic Books   \n",
       "3135776              0                   Twitter Hashtag Connection Graph   \n",
       "3135777              0  Import and convert MOD to iPhone(iPhone 4) on ...   \n",
       "3135778              0                                        Placeholder   \n",
       "3135779              0                     Be Inspired (By Everything) 01   \n",
       "3135780              0                Free Valentine's Gifts From Doodels   \n",
       "3135781              0        Nike Air Force 1 07 Black Black Varsity Red   \n",
       "3135782              0                                   Google Translate   \n",
       "3135783              0             But I want to be a rocket scientist...   \n",
       "3135784              0                                           Keevoice   \n",
       "3135785              0    Timetric - the economic data you need right now   \n",
       "3135786              0    JinX - The Javascript Includer Wordpress Plugin   \n",
       "3135787              0    À la découverte des soins orientaux à Essaouira   \n",
       "3135788              0  Red tide spawns blue light show at night on Sa...   \n",
       "3135789              0                                               ����   \n",
       "3135790              0                                        Online jobs   \n",
       "3135791              0         E-Civil 2014: Jornadas de Engenharia Civil   \n",
       "3135792              0  Show HN: Chrome Extension: Cloud Assistant for...   \n",
       "3135793              0                              PHP BDD is now \"nice\"   \n",
       "3135794              0  Kontest reboots its popular Facebook Contest P...   \n",
       "3135795              0           Global Logistics Media - Damco the Movie   \n",
       "3135796              0                                          Landslide   \n",
       "3135797              0                   Prediksi Skor Estonia vs Belarus   \n",
       "3135798              0      How To Find A Starving Crowd of Hungry Buyers   \n",
       "3135799              0     Final Dergisi Dershaneleri - Sınav Giriş Kartı   \n",
       "3135800              0        Matt Cutts Talks About The Google Algorithm   \n",
       "3135801              0           Youmexvideo - Online Video Entertainment   \n",
       "3135802              0                  How many ways can you mess up IO?   \n",
       "3135803             -1                               The DevOps Democracy   \n",
       "\n",
       "               stories_time stories_day  \n",
       "0       2018-03-14 03:50:30   Wednesday  \n",
       "1       2016-02-17 08:38:37   Wednesday  \n",
       "2       2011-10-05 23:42:23   Wednesday  \n",
       "3       2017-02-19 21:16:33      Sunday  \n",
       "4       2012-03-23 00:40:39      Friday  \n",
       "5       2017-12-14 18:13:35    Thursday  \n",
       "6       2017-02-23 23:05:08    Thursday  \n",
       "7       2016-06-24 03:48:57      Friday  \n",
       "8       2014-10-30 11:12:23    Thursday  \n",
       "9       2017-02-23 13:01:08    Thursday  \n",
       "10      2019-04-23 13:00:24     Tuesday  \n",
       "11      2017-11-28 19:41:10     Tuesday  \n",
       "12      2018-02-06 20:57:15     Tuesday  \n",
       "13      2014-03-10 15:44:42      Monday  \n",
       "14      2018-10-15 22:00:14      Monday  \n",
       "15      2018-06-03 20:14:26      Sunday  \n",
       "16      2019-01-07 17:03:59      Monday  \n",
       "17      2013-08-22 17:10:57    Thursday  \n",
       "18      2017-09-18 19:45:08      Monday  \n",
       "19      2017-03-07 13:10:56     Tuesday  \n",
       "20      2019-03-14 20:25:03    Thursday  \n",
       "21      2013-08-12 20:29:01      Monday  \n",
       "22      2018-10-28 17:57:59      Sunday  \n",
       "23      2017-02-28 17:45:58     Tuesday  \n",
       "24      2018-09-16 19:44:57      Sunday  \n",
       "25      2016-09-14 08:31:15   Wednesday  \n",
       "26      2018-10-04 09:21:28    Thursday  \n",
       "27      2016-10-14 12:26:46      Friday  \n",
       "28      2019-02-07 22:52:16    Thursday  \n",
       "29      2016-07-11 19:34:57      Monday  \n",
       "...                     ...         ...  \n",
       "3135774 2014-01-16 10:45:18    Thursday  \n",
       "3135775 2010-07-23 10:21:46      Friday  \n",
       "3135776 2014-05-04 08:10:12      Sunday  \n",
       "3135777 2010-07-15 08:12:19    Thursday  \n",
       "3135778 2014-05-31 18:42:20    Saturday  \n",
       "3135779 2010-06-21 15:06:21      Monday  \n",
       "3135780 2013-02-07 00:29:53    Thursday  \n",
       "3135781 2010-06-08 08:40:22     Tuesday  \n",
       "3135782 2013-12-22 11:11:00      Sunday  \n",
       "3135783 2013-06-29 16:41:13    Saturday  \n",
       "3135784 2013-12-24 10:53:20     Tuesday  \n",
       "3135785 2010-12-04 16:54:58    Saturday  \n",
       "3135786 2010-07-20 17:02:40     Tuesday  \n",
       "3135787 2013-02-25 15:51:23      Monday  \n",
       "3135788 2011-09-30 06:33:07      Friday  \n",
       "3135789 2011-03-24 22:25:20    Thursday  \n",
       "3135790 2011-07-30 06:56:01    Saturday  \n",
       "3135791 2014-03-17 11:41:51      Monday  \n",
       "3135792 2017-09-27 17:29:18   Wednesday  \n",
       "3135793 2012-08-25 09:51:02    Saturday  \n",
       "3135794 2012-10-02 07:24:23     Tuesday  \n",
       "3135795 2012-02-27 03:59:28      Monday  \n",
       "3135796 2013-02-07 10:57:31    Thursday  \n",
       "3135797 2013-06-03 03:22:12      Monday  \n",
       "3135798 2014-01-16 11:10:35    Thursday  \n",
       "3135799 2013-12-31 14:37:18     Tuesday  \n",
       "3135800 2014-01-16 10:17:45    Thursday  \n",
       "3135801 2012-12-01 16:28:42    Saturday  \n",
       "3135802 2015-01-06 20:20:51     Tuesday  \n",
       "3135803 2015-11-13 16:14:14      Friday  \n",
       "\n",
       "[3135804 rows x 4 columns]"
      ]
     },
     "execution_count": 357,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hn_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "metadata": {},
   "outputs": [],
   "source": [
    "#average scores per weekday\n",
    "days = ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']\n",
    "hn_avg_perday = pd.DataFrame(columns = ['Day', 'Average', 'Max'])\n",
    "hn_avg_perday['Day'] = days\n",
    "for i in range(0, 7):\n",
    "    hn_avg_perday['Average'][i] = hn_data[hn_data[\"stories_day\"] == days[i]].stories_score.mean()\n",
    "    hn_avg_perday['Max'][i] = hn_data[hn_data[\"stories_day\"] == days[i]].stories_score.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25284aeb8>"
      ]
     },
     "execution_count": 359,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot averages\n",
    "sns.barplot(x = days, y = hn_avg_perday.Average)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 414,
   "metadata": {},
   "outputs": [],
   "source": [
    "#averages per hour per day\n",
    "hn_avg_hrday = hn_data.groupby([hn_data[\"stories_day\"], hn_data[\"stories_time\"].dt.hour]).mean()\n",
    "hn_avg_hrday = hn_avg_hrday.reindex(days, level = 0).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 415,
   "metadata": {},
   "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>stories_day</th>\n",
       "      <th>stories_time</th>\n",
       "      <th>stories_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>23</td>\n",
       "      <td>15.548173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Monday</td>\n",
       "      <td>1</td>\n",
       "      <td>15.150421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>18</td>\n",
       "      <td>15.047117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>12</td>\n",
       "      <td>15.011485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>11</td>\n",
       "      <td>14.991381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>0</td>\n",
       "      <td>14.926044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>21</td>\n",
       "      <td>14.838941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>19</td>\n",
       "      <td>14.735488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>Saturday</td>\n",
       "      <td>19</td>\n",
       "      <td>14.714501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>15</td>\n",
       "      <td>14.601099</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    stories_day  stories_time  stories_score\n",
       "23       Sunday            23      15.548173\n",
       "25       Monday             1      15.150421\n",
       "18       Sunday            18      15.047117\n",
       "12       Sunday            12      15.011485\n",
       "11       Sunday            11      14.991381\n",
       "0        Sunday             0      14.926044\n",
       "21       Sunday            21      14.838941\n",
       "19       Sunday            19      14.735488\n",
       "163    Saturday            19      14.714501\n",
       "15       Sunday            15      14.601099"
      ]
     },
     "execution_count": 415,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hn_avg_hrday.nlargest(10, 'stories_score')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 425,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot all seven days\n",
    "plt.rcParams['figure.figsize']=(16,5)\n",
    "#there isn't a standard way to format seven plots so we will iterate over a dummy list\n",
    "plotarrange = [[0,1], [2, 3], [4, 5, 6]]\n",
    "for i in plotarrange:\n",
    "    fig, axs = plt.subplots(ncols = len(i))\n",
    "    x = 0\n",
    "    for j in range(i[0], i[-1]+1):\n",
    "        plot = sns.barplot(x = hn_avg_hrday.stories_time[hn_avg['stories_day'] == days[j]], \n",
    "                           y = hn_avg_hrday.stories_score[hn_avg['stories_day'] == days[j]], ax = axs[x])\n",
    "        plot.set(xlabel = 'Hour', ylabel = 'Average Score')\n",
    "        plot.set_title(days[j])\n",
    "        x+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "metadata": {},
   "outputs": [],
   "source": [
    "#return best ten results if averaged over time rounded to input nearest input length\n",
    "def max_avg_per_slice(x):\n",
    "    avg = hn_data.groupby([hn_data[\"stories_day\"], hn_data[\"stories_time\"].dt.round(x).dt.time]).mean()\n",
    "    avg = avg.reindex(days, level = 0)\n",
    "    avg = avg.reset_index()\n",
    "    return avg.nlargest(10, 'stories_score')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 427,
   "metadata": {},
   "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>stories_day</th>\n",
       "      <th>stories_time</th>\n",
       "      <th>stories_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>23:30:00</td>\n",
       "      <td>17.176054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>15:15:00</td>\n",
       "      <td>16.310833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>15:00:00</td>\n",
       "      <td>16.177297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>18:30:00</td>\n",
       "      <td>16.064540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>Monday</td>\n",
       "      <td>01:00:00</td>\n",
       "      <td>16.018083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>00:00:00</td>\n",
       "      <td>15.926516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>03:15:00</td>\n",
       "      <td>15.851672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>18:15:00</td>\n",
       "      <td>15.819050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>652</th>\n",
       "      <td>Saturday</td>\n",
       "      <td>19:00:00</td>\n",
       "      <td>15.739108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sunday</td>\n",
       "      <td>00:45:00</td>\n",
       "      <td>15.676190</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    stories_day stories_time  stories_score\n",
       "94       Sunday     23:30:00      17.176054\n",
       "61       Sunday     15:15:00      16.310833\n",
       "60       Sunday     15:00:00      16.177297\n",
       "74       Sunday     18:30:00      16.064540\n",
       "100      Monday     01:00:00      16.018083\n",
       "0        Sunday     00:00:00      15.926516\n",
       "13       Sunday     03:15:00      15.851672\n",
       "73       Sunday     18:15:00      15.819050\n",
       "652    Saturday     19:00:00      15.739108\n",
       "3        Sunday     00:45:00      15.676190"
      ]
     },
     "execution_count": 427,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_avg_per_slice('15min')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [],
   "source": [
    "#fill empty titles with empty string\n",
    "hn_data['stories_title'] = hn_data['stories_title'].fillna(\"\")\n",
    "#group by title lengths and average scores\n",
    "title_grouped = hn_data.groupby(hn_data['stories_title'].map(lambda x: len(x.split()))).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "metadata": {},
   "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>stories_score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stories_title</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.147800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13.300602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13.293389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13.317486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12.523615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11.426665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>11.222462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.741851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.959100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11.005919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11.529824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>11.523619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11.784539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>11.715329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>12.432403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>12.007161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>11.698625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>10.893513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>8.153543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10.414141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>8.405405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5.357143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>3.590909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>8.176471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2.857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2.454545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>3.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>4.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               stories_score\n",
       "stories_title               \n",
       "0                   2.750000\n",
       "1                   8.147800\n",
       "2                  13.300602\n",
       "3                  13.293389\n",
       "4                  13.317486\n",
       "5                  12.523615\n",
       "6                  11.426665\n",
       "7                  11.222462\n",
       "8                  10.741851\n",
       "9                  10.959100\n",
       "10                 11.005919\n",
       "11                 11.529824\n",
       "12                 11.523619\n",
       "13                 11.784539\n",
       "14                 11.715329\n",
       "15                 12.432403\n",
       "16                 12.007161\n",
       "17                 11.698625\n",
       "18                 10.893513\n",
       "19                  8.153543\n",
       "20                 10.414141\n",
       "21                  8.405405\n",
       "22                  5.357143\n",
       "23                  3.590909\n",
       "24                  8.176471\n",
       "25                  2.857143\n",
       "26                  6.000000\n",
       "27                  2.454545\n",
       "28                  1.800000\n",
       "29                  3.600000\n",
       "30                  4.500000\n",
       "34                  1.500000\n",
       "36                  3.000000"
      ]
     },
     "execution_count": 390,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "title_grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot average scores for each title length\n",
    "sns.barplot(x = title_grouped.index, y = 'stories_score', data = title_grouped)\n",
    "plt.xlabel('Title Length')\n",
    "plt.ylabel('Avg Score')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}