hourly_earned_like.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from urllib.request import urlopen\n",
    "import json\n",
    "from datetime import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "from collections import defaultdict\n",
    "import pandas as pd\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_all_article():\n",
    "    # initialize\n",
    "    article_api   = \"https://alis.to/api/articles/recent?limit=100&page=%d\"\n",
    "    result          = []\n",
    "    page           = 1\n",
    "    # データ取得\n",
    "    while True:\n",
    "        try:\n",
    "            raw_article_data  = urlopen(article_api % page).read().decode(\"utf-8\") \n",
    "            json_article_data  = json.loads(raw_article_data)                    \n",
    "            articles_data        = json_article_data[\"Items\"]\n",
    "            result.extend(articles_data)\n",
    "            page += 1\n",
    "        except:\n",
    "            break\n",
    "    result = pd.DataFrame(result)\n",
    "    result[\"published_at\"] = result[\"published_at\"].map(lambda x:datetime.fromtimestamp(int(x)))\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_recent_article(date_span=7):\n",
    "    # initialize\n",
    "    article_api   = \"https://alis.to/api/articles/recent?limit=100&page=%d\"\n",
    "    page           = 1\n",
    "    result          = []\n",
    "    # データ取得\n",
    "    while True:\n",
    "        raw_article_data  = urlopen(article_api % page).read().decode(\"utf-8\") \n",
    "        json_article_data  = json.loads(raw_article_data)                    \n",
    "        articles_data        = json_article_data[\"Items\"]\n",
    "        result.extend(articles_data)\n",
    "        # ループ終了のチェック\n",
    "        today                 = datetime.now() \n",
    "        last_data_date    = datetime.fromtimestamp(int(result[-1][\"published_at\"]))\n",
    "        if (today-last_data_date).days >= (date_span+1):\n",
    "            result = pd.DataFrame(result)\n",
    "            result[\"published_at\"] = result[\"published_at\"].map(lambda x:datetime.fromtimestamp(int(x)))\n",
    "            return result\n",
    "        else:\n",
    "            page += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 公開時間・lile数を取得\n",
    "def get_date_and_like(article_data):\n",
    "    data               = defaultdict(lambda:{\"like\":0,\"count\":0})        \n",
    "    likes_api         = \"https://alis.to/api/articles/%s/likes\"  \n",
    "    for article in article_data.iterrows():\n",
    "        \n",
    "        article_id              = article[1][\"article_id\"]                                  \n",
    "        raw_like_data       = urlopen(likes_api % article_id).read().decode(\"utf-8\") \n",
    "        json_like_data      = json.loads(raw_like_data)\n",
    "        \n",
    "        like    = json_like_data[\"count\"]                                \n",
    "        hour  = article[1][\"published_at\"].hour   \n",
    "        \n",
    "        data[hour][\"like\"]     += like                                                 \n",
    "        data[hour][\"count\"] += 1\n",
    "    return data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# グラフ用にデータを整形\n",
    "def adjust_data(data):\n",
    "    x      = []              \n",
    "    mean   = []\n",
    "    for k,v in data.items():\n",
    "        x.append(k)\n",
    "        mean.append(v[\"like\"]/v[\"count\"])\n",
    "    return x,mean\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# グラフの作成\n",
    "def show_graph(data):\n",
    "    x,mean = adjust_data(data)\n",
    "    plt.bar(x,mean,color=\"lightblue\")               \n",
    "    plt.title(\"hourly earned like\") \n",
    "    plt.xlabel(\"published time\")    \n",
    "    plt.ylabel(\"mean earned like\") \n",
    "    plt.xticks(range(0,25,3))\n",
    "    y_max = max(mean)\n",
    "    y_min = min(mean)\n",
    "    diff = (y_max - y_min) * 0.1\n",
    "    plt.ylim(y_min - diff,y_max + diff)\n",
    "    plt.show()                    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def is_holyday(date):\n",
    "    if date.weekday() == 5 or date.weekday() == 6:\n",
    "        return True\n",
    "    else:\n",
    "        return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "articles = get_recent_article()\n",
    "holyday_articles = articles[articles[\"published_at\"].map(is_holyday)]\n",
    "weekday_articles = articles[articles[\"published_at\"].map(lambda x:not(is_holyday(x)))]\n",
    "weekday_data = get_date_and_like(weekday_articles)\n",
    "holyday_data = get_date_and_like(holyday_articles)\n",
    "x,weekday_mean = adjust_data(weekday_data)\n",
    "x,holyday_mean = adjust_data(holyday_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_ = [h+0.3 for h in x]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1.1999999999999997, 40.8)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,10),dpi=200)\n",
    "ax = fig.add_subplot(2,1,1)\n",
    "ax.bar(x,weekday_mean,width=0.3,label='weekday',color=\"lightblue\")\n",
    "ax.bar(x_,holyday_mean,width=0.3,label='holyday',color=\"lightpink\")\n",
    "ax.set_title(\"hourly earned like\") \n",
    "ax.set_xlabel(\"published time\")    \n",
    "ax.set_ylabel(\"mean earned like\")\n",
    "ax.set_xticks(range(0,25,3))\n",
    "ax.legend()\n",
    "y_max = max([max(weekday_mean),max(holyday_mean)])\n",
    "y_min = min([min(weekday_mean),min(holyday_mean)])\n",
    "diff = (y_max - y_min) * 0.1\n",
    "ax.set_ylim(y_min - diff,y_max + diff)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_graph(weekday_data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_graph(holyday_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}