double_y_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "731078e0-3b83-46e2-af54-8b9d10940423",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import MaxNLocator\n",
    "import matplotlib.ticker as tkr\n",
    "import matplotlib as mpl\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(action='ignore')\n",
    "\n",
    "import matplotlib\n",
    "from matplotlib import font_manager, rc\n",
    "import platform\n",
    "\n",
    "if platform.system() == 'Windows':\n",
    "# 윈도우인 경우\n",
    "    font_name = font_manager.FontProperties(fname=\"c:/Windows/Fonts/malgun.ttf\").get_name()\n",
    "    rc('font', family=font_name)\n",
    "else:    \n",
    "# Mac 인 경우\n",
    "    rc('font', family='AppleGothic')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d022dc3e-e42c-4c76-9438-6529f2682ccb",
   "metadata": {},
   "outputs": [],
   "source": [
    "insta = pd.read_excel('/Users/hankiho/Downloads/라비림_청소기.xlsx', sheet_name = 'insta')\n",
    "df = pd.read_excel('/Users/hankiho/Downloads/라비림_청소기.xlsx', sheet_name = 'sales')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "10a9eaf8-5ed1-44fe-87de-1b67cca33a2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def group_buying_graph(amount_df, insta, sales_prd_name, insta_prd_name):\n",
    "\n",
    "    insta = insta[insta['일자'].notnull()]\n",
    "    insta['일자'] = insta['일자'].apply(lambda x:x.replace('/','-'))\n",
    "\n",
    "    d = df[df['orderGoodSimple'] == sales_prd_name]\n",
    "    q = d.groupby('orderPayDate')['orderPrice'].sum().reset_index(name = 'amt')\n",
    "\n",
    "    insta['일자'] = insta['일자'].apply(lambda x:x.strip())\n",
    "    insta = insta[insta['제품명'] == insta_prd_name]\n",
    "    df_5stage = insta.groupby(['일자','5 stage']).size().reset_index(name = 'cnt').fillna(0)\n",
    "\n",
    "    max_dates = max(min(insta['일자']), max(insta['일자']), min(q['orderPayDate']), max(d['orderPayDate']))\n",
    "    min_dates = min(min(insta['일자']), max(insta['일자']), min(q['orderPayDate']), max(d['orderPayDate']))\n",
    "    dates_df = pd.DataFrame(pd.date_range(min_dates, max_dates), columns = ['orderPayDate'])\n",
    "    dates_df['orderPayDate'] = dates_df['orderPayDate'].apply(lambda x:x.strftime('%Y-%m-%d'))\n",
    "    q = pd.merge(dates_df, q, how = 'outer').fillna(0)\n",
    "\n",
    "\n",
    "    merge_df = pd.merge(q, df_5stage, left_on = 'orderPayDate', right_on = '일자', how = 'outer').fillna(0).drop('일자',1)[['orderPayDate','5 stage','cnt','amt']]\n",
    "\n",
    "    display(merge_df[merge_df['cnt'] == 0])\n",
    "    merge_df = merge_df[merge_df['cnt'] != 0]\n",
    "    \n",
    "    print('홍보기간: {0}일'.format(merge_df.shape[0]))\n",
    "    print('피드갯수: {0}개'.format(merge_df['cnt'].sum()))\n",
    "    print('판매량: {:,}원'.format(merge_df['amt'].sum()))\n",
    "    top_3_location = ','.join(df['recvAddr1'].apply(lambda x:x.split(' ')[0]).value_counts()[:3].index)\n",
    "    print ('상위 구매지역(Top_3): {0}'.format(top_3_location))\n",
    "    \n",
    "    plt.rcParams[\"figure.figsize\"] = (15, 5)\n",
    "\n",
    "    color_dct = {'show':'crimson',\n",
    "                'push':'darksalmon',\n",
    "                'open':'chartreuse',\n",
    "                'ing':'dodgerblue',\n",
    "                'close':'navy'}\n",
    "\n",
    "    ax1 = pd.pivot_table(data = merge_df,\n",
    "                index = 'orderPayDate', columns = '5 stage', \n",
    "                values = 'cnt').fillna(0).plot.bar(stacked=True, color = color_dct)\n",
    "    ax1.set_ylabel('인스타그램 피드수')\n",
    "    ax1.legend(bbox_to_anchor= (1.5, 0.5))\n",
    "\n",
    "    ax2 = ax1.twinx()\n",
    "    ax2 = sns.pointplot(data = merge_df, x = 'orderPayDate', y = 'amt', color = 'yellow')\n",
    "    ax2.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))\n",
    "    ax2.set_ylabel('판매량')\n",
    "    plt.xticks(rotation = '90')\n",
    "    plt.title('공구 플로우 현황 ({0})\\n'.format(insta['제품명'].unique()[0]), fontsize = 15)\n",
    "    plt.tight_layout()\n",
    "    # plt.savefig('{0}.png'.format(insta_prd))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e41f9731-0f85-4655-96b6-1b328eb48b52",
   "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>orderPayDate</th>\n",
       "      <th>5 stage</th>\n",
       "      <th>cnt</th>\n",
       "      <th>amt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-07-07</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-07-09</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2021-07-11</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-07-14</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2021-07-22</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   orderPayDate 5 stage  cnt  amt\n",
       "1    2021-07-07       0  0.0  0.0\n",
       "3    2021-07-09       0  0.0  0.0\n",
       "5    2021-07-11       0  0.0  0.0\n",
       "8    2021-07-14       0  0.0  0.0\n",
       "17   2021-07-22       0  0.0  0.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "홍보기간: 15일\n",
      "피드갯수: 42.0개\n",
      "판매량: 104,976,000.0원\n",
      "상위 구매지역(Top_3): 경기,서울,대구\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "group_buying_graph(df, insta, '비쎌 크로스웨이브 맥스 3.0 2765S', '비쎌크로스웨이브')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dcbfdb44-a679-4841-b6e6-0185ed09a3bb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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