Kakao_dashboard_Amazon.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rc\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "['C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\businessreport\\\\DE.csv', 'C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\businessreport\\\\ES.csv', 'C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\businessreport\\\\FR.csv', 'C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\businessreport\\\\IT.csv', 'C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\businessreport\\\\NL.csv', 'C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\businessreport\\\\UK.csv']\n['C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\adreport\\\\DE_Sponsored Products Search term report.xlsx', 'C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\adreport\\\\UK_Sponsored Products Search term report.xlsx']\n"
    }
   ],
   "source": [
    "amz_business_report_base_dir = \"C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\businessreport\"\n",
    "amz_ad_report_base_dir = \"C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\adreport\"\n",
    "amz_business_report_name = os.listdir(\"C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\businessreport\")\n",
    "amz_ad_report_name = os.listdir(\"C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\Amazon\\\\adreport\")\n",
    "\n",
    "amz_business_report_full_dir = []\n",
    "amz_ad_report_full_dir = []\n",
    "\n",
    "\n",
    "for i in range(len(amz_business_report_name)):\n",
    "    amz_business_report_full_dir.append(os.path.join(amz_business_report_base_dir,amz_business_report_name[i]))\n",
    "\n",
    "for i in range(len(amz_ad_report_name)):\n",
    "    amz_ad_report_full_dir.append(os.path.join(amz_ad_report_base_dir,amz_ad_report_name[i]))\n",
    "\n",
    "print(amz_business_report_full_dir)\n",
    "print(amz_ad_report_full_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "['DE.csv', 'ES.csv', 'FR.csv', 'IT.csv', 'NL.csv', 'UK.csv']"
     },
     "metadata": {},
     "execution_count": 35
    }
   ],
   "source": [
    "amz_business_report_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "business_report_DE = pd.read_csv(amz_business_report_full_dir[0])\n",
    "business_report_DE['Country'] = amz_business_report_name[0][:2]\n",
    "\n",
    "business_report_ES = pd.read_csv(amz_business_report_full_dir[1])\n",
    "business_report_ES['Country'] = amz_business_report_name[1][:2]\n",
    "\n",
    "business_report_FR = pd.read_csv(amz_business_report_full_dir[2])\n",
    "business_report_FR['Country'] = amz_business_report_name[2][:2]\n",
    "\n",
    "business_report_IT = pd.read_csv(amz_business_report_full_dir[3])\n",
    "business_report_IT['Country'] = amz_business_report_name[3][:2]\n",
    "\n",
    "business_report_NL = pd.read_csv(amz_business_report_full_dir[4])\n",
    "business_report_NL['Country'] = amz_business_report_name[4][:2]\n",
    "\n",
    "business_report_GB = pd.read_csv(amz_business_report_full_dir[5])\n",
    "business_report_GB['Country'] = amz_business_report_name[5][:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(business_report_GB['Ordered Product Sales'])):\n",
    "    sale_string = business_report_GB['Ordered Product Sales'][i][1:]\n",
    "    business_report_GB['Ordered Product Sales'][i] = float(sale_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def currency (business_report_name, euro_currency):\n",
    "    for i in range(len(business_report_name['Ordered Product Sales'])):\n",
    "        currency_string = business_report_name['Ordered Product Sales'][i]\n",
    "        currency_number = currency_string[1:]\n",
    "        currency_float = float(currency_number)\n",
    "        change_currency = currency_float * euro_currency\n",
    "        business_report_name['Ordered Product Sales'][i] = round(change_currency, 2)\n",
    "\n",
    "\n",
    "currency(business_report_DE, 0.94)\n",
    "currency(business_report_FR, 0.94)\n",
    "currency(business_report_ES, 0.94)\n",
    "currency(business_report_IT, 0.94)\n",
    "currency(business_report_NL, 0.94)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_list = ['Date', 'Sessions', 'Ordered Product Sales','Total Order Items', 'Country']\n",
    "country_list = ['UK', 'DE', 'FR', 'ES', 'IT', 'NL']\n",
    "\n",
    "business_report_ALL = pd.concat([business_report_DE[columns_list],\n",
    "business_report_GB[columns_list],\n",
    "business_report_FR[columns_list],\n",
    "business_report_ES[columns_list],\n",
    "business_report_IT[columns_list],\n",
    "business_report_NL[columns_list]]\n",
    ",axis = 0)\n",
    "\n",
    "Session_country = pd.pivot_table(business_report_ALL, index = 'Date', columns='Country', values = 'Sessions', aggfunc = np.sum)\n",
    "Session_country = Session_country[country_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "orders_country = pd.pivot_table(business_report_ALL, index = 'Date', columns='Country', values = 'Total Order Items', aggfunc = np.sum, margins= False)\n",
    "orders_country = orders_country[country_list]\n",
    "orders_country = orders_country.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "sales_country = pd.pivot_table(business_report_ALL, index = 'Date', columns='Country', values = 'Ordered Product Sales', aggfunc = np.sum)\n",
    "sales_country = sales_country[country_list]\n",
    "sales_country.index = pd.to_datetime(sales_country.index, format = '%d/%m/%Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "de_raw = pd.read_excel(amz_ad_report_full_dir[0])\n",
    "uk_raw = pd.read_excel(amz_ad_report_full_dir[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_list = ['Date','Currency', 'Spend','Impressions', 'Clicks', '7 Day Total Orders (#)']\n",
    "\n",
    "de_report = de_raw[columns_list]\n",
    "uk_report = uk_raw[columns_list]\n",
    "\n",
    "de_report['Country']  = 'DE'\n",
    "uk_report['Country']  = 'UK'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def currency_2 (ad_report_name, euro_currency):\n",
    "    for i in range(len(ad_report_name['Spend'])):\n",
    "        ad_report_name['Spend'][i] =  ad_report_name['Spend'][i]* euro_currency\n",
    "        all_float = ad_report_name['Spend'][i]\n",
    "        rounded_2 = round(all_float, 2)\n",
    "        ad_report_name['Spend'][i] = rounded_2\n",
    "\n",
    "currency_2(de_report, 0.94)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "amazonppc_all = pd.concat([de_report, uk_report], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.dates import DateFormatter\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "amazonppc_country = pd.pivot_table(amazonppc_all, values='Spend', columns='Country', index = 'Date', aggfunc=sum)\n",
    "amazonppc_country  = amazonppc_country[['UK', 'DE']]\n",
    "# amazonppc_country.index = pd.to_datetime(amazonppc_country.index, format = '%Y-%m-%d')\n",
    "# pd.DatetimeIndex(amazonppc_country.index).normalize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "sales_all = pd.pivot_table(business_report_ALL, index = 'Date', values = 'Ordered Product Sales', aggfunc = np.sum )\n",
    "sales_all.index = pd.to_datetime(sales_all.index, format = '%d/%m/%Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "amazonppc_spend = pd.pivot_table(amazonppc_all, values='Spend', index = 'Date', aggfunc=sum)\n",
    "amazon_merge = pd.concat([amazonppc_spend, sales_all], axis = 1)\n",
    "\n",
    "amazon_merge['roas'] = 0\n",
    "\n",
    "for i in range(len(amazon_merge['roas'])):\n",
    "    roas = round(amazon_merge['Ordered Product Sales'][i]/amazon_merge['Spend'][i],2)\n",
    "    amazon_merge['roas'][i] = roas\n",
    "\n",
    "amazon_merge.index = pd.to_datetime(amazon_merge.index, format = '%Y-%m-%d')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "from matplotlib.dates import DateFormatter\n",
    "import matplotlib.dates as mdates\n",
    "import seaborn as sns\n",
    "\n",
    "ax = amazonppc_country.plot.bar(stacked=True, color=sns.color_palette(\"ch:2.5,-.2,dark=.3\"))\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(amazon_merge['roas'].values, marker = 'o', linestyle = '-', color='c', linewidth = 3, markersize = 12)\n",
    "\n",
    "plt.title('Amazon PPC Budget & ROAS', fontsize = 20)\n",
    "\n",
    "ax.set_xlabel('Date', fontsize =20)\n",
    "ax.set_ylabel('Budget(£)', fontsize =20)\n",
    "ax2.set_ylabel('ROAS', fontsize= 20)\n",
    "\n",
    "#축값 표시 없애고 싶을 때\n",
    "ax.axes.xaxis.set_visible(False)\n",
    "ax.axes.yaxis.set_visible(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "ax = orders_country.plot.bar(stacked=True, color=sns.color_palette(\"muted\"))\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(amazon_merge['roas'].values, marker = 'o', linestyle = '-', color='c', linewidth = 3, markersize = 12)\n",
    "\n",
    "plt.title('Amazon Ordes by Country & ROAS', fontsize = 20)\n",
    "# plt.rc('xtick',labelsize=20)\n",
    "# plt.rc('ytick',labelsize=20)\n",
    "plt.xticks(fontsize = 15)\n",
    "ax.set_xlabel('Date', fontsize=20)\n",
    "ax.set_ylabel('Orders', fontsize =20)\n",
    "ax2.set_ylabel('ROAS', fontsize= 20)\n",
    "\n",
    "#축값 표시 없애고 싶을 때\n",
    "ax.axes.xaxis.set_visible(False)\n",
    "ax.axes.yaxis.set_visible(False)\n",
    "ax2.axes.yaxis.set_visible(False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 1440x720 with 0 Axes>"
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 1440x720 with 1 Axes>",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 1440x720 with 0 Axes>"
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 1440x720 with 1 Axes>",
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WrnR+z9Vab0syJ8lnktzZ3bwknS6aQ2ut563FMFulEzaN91rlMdW11tOTHJxOUHRPOlOsHk4nWDgxyWtqrRPtSpmQWust6QQPJyX5Qjph1W+TTEsntFmU5Ookb0+yR631J2OMcVY6wcm/pvNErqlJ/i3Jh5K8OMvv8UTquzWdn9Wx6fx87krn3m+a5NYkV6Vz7/Zb6dQ3JTk3yXXd4zbt1nVbOmHSq7o/j7GMLLr81nH2b5/lP+eRfzeu7s/DFuOMMzL+VbVWixADwFoqa56aDgDA01EpZesk/5FOJ9bvdkO+yb5GSfLzJLslOaDWak0bAFhLOm0AAAZUt9vpw0lKkjN7dJmj0glsvi6wAYB1o9MGAGCAdZ+E9dN0Fmrevdb6y0kce5MkC5K8IMle3WmCAMBa2pBPrwAAoDG11iWllOOSHJhklySTFtqk82j3Lye5VWADAOtOpw0AAABAg9ap02b69Ol15syZPSoFAAAAYPDMnz///lrrKk/kXKfQZubMmZk3b97kVQUAAAAw4EopYz7B0dOjAAAAABoktAEAAABokNAGAAAAoEFCGwAAAIAGCW0AAAAAGrROT48CAAAAGPHQQw/l3nvvzRNPPNHvUpo0derU7LDDDtlmm20mdL7QBgAAAFhnDz30UO65557stNNO2WKLLVJK6XdJTam15tFHH80dd9yRJBMKbkyPAgAAANbZvffem5122ilbbrmlwGYMpZRsueWW2WmnnXLvvfdOaAyhDQAAALDOnnjiiWyxxRb9LqN5W2yxxYSnjwltAAAAgAnRYbNm63OPhDYAAAAADRLaAAAAADRIaAMAAAD01d133503velN2W233bLHHnvkta99bX72s59N2vg33HBDvvvd707aeBuK0AYAAADom1prDj/88Bx44IH5xS9+kZ/85Cf50Ic+lHvuuWfSrrG60Gbp0qWTdp3JJrQBAAAA+uab3/xmpk6dmpNPPnnZtr322iuveMUr8t73vje/93u/l9mzZ+fKK69M0glgDjvssGXHvvOd78yll16aJJk5c2bOPffcvOQlL8ns2bNzyy23ZNGiRbnkkkvy8Y9/PHvttVe+/e1v5/jjj8/pp5+egw46KO9973vz3Oc+N/fdd1+S5Kmnnsruu++e+++/f8PdhHEM9bsAAAAAYHD9+Mc/zt57773K9q985Sv54Q9/mB/96Ee5//7789KXvjT777//GsebPn16fvCDH+Siiy7Kxz72sXz605/OySefnGc84xk544wzkiSf+cxn8rOf/SzXXnttpkyZkm233TaXX3553v3ud+faa6/NnnvumenTp0/697qudNoAAAAAzfnOd76TN7/5zZkyZUpmzJiRAw44IDfddNMaz3vDG96QJNl7772zaNGicY878sgjM2XKlCTJiSeemM9//vNJks9+9rM54YQT1v8bmARCGwAAAKBvXvjCF2b+/PmrbK+1jnn80NBQnnrqqWWflyxZssL+zTbbLEkyZcqU1a5Xs9VWWy37euedd86MGTNy/fXX5/vf/37+8A//cJ2+h14R2gAAAAB9c/DBB+exxx7Lpz71qWXbbrrppmy33Xa58sor8+STT+a+++7LjTfemH322SfPec5z8pOf/CSPPfZYFi9enOuuu26N19h6663z8MMPr/aYt7/97TnmmGNy1FFHLevA6TehDQAAANA3pZRcddVVueaaa7LbbrvlhS98YYaHh/OWt7wlL3rRi7Lnnnvm4IMPzkc+8pHsuOOO2XnnnXPUUUflRS96Ud761rfmxS9+8Rqv8brXvS5XXXXVsoWIx/JHf/RH+c1vftPM1KgkKeO1G41lzpw5dd68eT0sBwAAANgYLFy4MLNmzep3GZNm3rx5Oe2008YNddbHmu5VKWV+rXXOyts9PQoAAAAYaB/+8Idz8cUX5/LLL+93KSswPQoAAAAYaGeddVZuu+22vOIVr+h3KSsQ2gAAAAA0qCfTo84/+rBeDJv3XPnVnowLAAAA0BqdNgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAwEA68MADc8QRR4y5b86cOTn++OOTJMcff3zmzJmzwv5HH300Bx98cLbffvv88Ic/7El9PXl6FAAAADCYZp71tb5cd9GH//MGu9bjjz+eww8/PPPnz88111yTvfbaqyfXEdoAAAAArKUnnngiRx55ZL7zne/k61//evbZZ5+eXUtoAwAAALAWnnzyybz1rW/NNddck6997Wv5/d///Z5eT2gDAAAAsAZPPfVUTjjhhFx99dW5+uqrc9BBB/X8mj0JbS597W29GDbv6cmoAAAAAKt388035+abb87f/u3f5pBDDtkg1/T0KAAAAIA12HXXXbPbbrvlox/9aH75y19ukGsKbQAAAICBNDQ0lCeffHLMfU8++WSGhpZPUNpuu+3yjW98I0uXLs0hhxySBx54oOf1CW0AAACAgfTMZz4zd99995j77rrrruywww4rbNt1113zz//8z7nzzjtz2GGH5ZFHHulpfUIbAAAAYCC98pWvzPz583PHHXessP373/9+7rnnnrzyla9c5Zy99tor//iP/5ibb745RxxxRJYuXdqz+oQ2AAAAwEA69thjs8suu2T//ffP5z73uVx//fW58MIL87rXvS4vf/nLc+ihh4553oEHHpjLL788X//613PiiSem1tqT+jzyGwAAABhIz3jGM3LjjTfm7LPPzllnnZVf/epXmTFjRo4++uh88IMfzCabjN/r8sY3vjEXXnhhTjnllMyYMSMf/ehHJ72+si5p0Jw5c+q8efPWeNzsy2avT03jWnDcgp6MCwAAAKybhQsXZtasWf0uY6OwpntVSplfa52z8nbTowAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABgltAAAAABoktAEAAABokNAGAAAAoEFCGwAAAIAGCW0AAAAAGiS0AQAAAGiQ0AYAAAAYWMPDwymlpJSSTTbZJNttt11e+tKX5pxzzsndd9+9wrEjx6382n333XtS21BPRgUAAAAG0/C0Pl138YRPnTZtWubOnZskWbx4cX7wgx/k4osvzic/+cnMnTs3e++997Jj3/Oe9+SII45Y4fzNN998wtdeHaENAAAAMNCGhoay7777Lvt86KGH5pRTTsn++++fo48+Oj/96U8zZcqUJMnMmTNXOLaXTI8CAAAAWMm2226bj3zkI/nFL36Ra665pi81CG0AAAAAxnDQQQdlaGgo3/ve95Zte+qpp7J06dIVXk899VRPri+0AQAAABjDZpttlunTp+eee+5Ztu1d73pXpk6dusLrxBNP7Mn1rWkDAAAAMI5a6wqf3/ve9+aoo45aYdv06dN7cm2hDQAAAMAYlixZkgceeCAzZsxYtm2XXXbJnDlzNsj1TY8CAAAAGMM3v/nNLF26NPvtt19fri+0AQAAAFjJgw8+mDPPPDO77757Xv3qV/elBtOjAAAAgIG2dOnSZU+IevjhhzN//vxcfPHFeeSRRzJ37txMmTJl2bGLFi1a4WlSSVJKycte9rJJr0toAwAAAEye4cX9rmCdLV68OPvtt19KKdlmm22y++6755hjjsmpp56aHXfccYVjzz///Jx//vkrbJsyZUqWLl066XUJbQAAAICBNTw8nOHh4bU6duUnSfWaNW0AAAAAGiS0AQAAAGiQ0AYAAACgQUIbAAAAgAYJbQAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABgltAAAAABoktAEAAAAG1vDwcEopq7xe/epXJ0lmzpy5bNumm26a5z73uTnzzDPz29/+tue1DfX8CgAAAMDAmH3Z7L5cd8FxCyZ87rRp0zJ37txVto14y1veklNPPTWPP/54vvWtb+UDH/hAHnjggXz605+e8DXXhtAGAAAAGGhDQ0PZd999x93/rGc9a9n+/fffP3fccUcuvfTSfPKTn8wmm/RuEpPpUQAAAADrYM8998xjjz2W++67r6fX0WkDAAAADLylS5eu8HnKlCkppYx57O23356tt94606dP72lNOm0AAACAgfbAAw9k6tSpK7yuu+66ZftrrVm6dGkeeeSRzJ07N5dccknOOeecTJkypad16bQBAAAABtq0adNy7bXXrrDt+c9//rKvL7jgglxwwQXLPh9++OE588wze16X0AYAAAAYaENDQ5kzZ864+4855pi8613vym9/+9tcdtll+dznPpeLL744p5xySm/r6unoAAAAABu5GTNmLAt1DjjggNx22215//vfn2OPPTZbbbVVz65rTRsAAACAdXDeeefl/vvvz2c+85meXkdoAwAAALAO9tlnn7zmNa/Jxz/+8Tz55JM9u05PpkctuPX2XgwLAAAA0IT3ve99OeCAA/KlL30pb37zm3tyjVJrXeuD58yZU+fNm7fmA4enrUdJqxt3cW/GBQAAANbJwoULM2vWrH6XsVFY070qpcyvta6yErLpUQAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAAAMrOHh4ZRSxnx94QtfSJLcdtttedvb3pZddtklm2++eXbeeee8/vWvz4033tjT2oZ6OjoAAAAwUBa+YFZfrjvrloUTPnfatGmZO3fuKtt33333/PrXv86+++6bZz3rWTnvvPPy7Gc/O4sWLcrVV1+df/mXf8n++++/PmWvltAGAAAAGGhDQ0PZd999x9z3qU99Kvfcc09+9KMfZYcddli2/YQTTkittad1mR4FAAAAMI4HH3wwm266abbffvtV9pVSenrtge+06VXb1vq0ZQEAAAAb1tKlS1fZNjQ0lJe85CV57LHH8ra3vS1nnHFGXvziF2eTTTZMD4xOGwAAAGCgPfDAA5k6deoqr0WLFuVVr3pVTjvttFx55ZWZM2dOtt1227zxjW/Mtdde2/O6Br7TBgAAABhs06ZNGzOEefazn50kueCCC/Knf/qn+Yd/+IfceOONmTt3bq666qpcdNFFOfnkk3tWl9AGAAAAGGhDQ0OZM2fOao/Zfffdc8YZZ+SMM87I/fffn0MOOSRnn312TjrppJ6tbWN6FAAAAMA6mD59ek444YT8+te/zr333tuz6whtAAAAAMZx3333jbn95z//eTbbbLNMmzatZ9c2PQoAAAAYaEuXLs33vve9VbbvvPPO+eIXv5jLL788xx57bPbcc8888cQTue6663LRRRfllFNOyeabb96zuoQ2AAAAwKSZdcvCfpewzhYvXpz99ttvle0f+MAH8oY3vCG33nprPvWpT+WXv/xlpkyZkt122y2f+MQn8id/8ic9rUtoAwAAAAys4eHhDA8Pr/aYCy+8cMMUsxJr2gAAAAA0SGgDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANEtoAAAAANEhoAwAAAAys4eHhTJ8+Pccff3xKKat9HX/88Ru0tqENejUAAADgae3Ck6/vy3XfccnB63X+X/7lX+bkk09e9vnss8/Ogw8+mIsuumjZtmc+85nrdY11JbQBAAAABt5uu+2W3Xbbbdnn7bffPk899VT23XffvtVkehQAAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOG+l0AAAAA8PTxjksO7ncJ62R4eDjDw8OrbP/7v//7DV/MSnTaAAAAADRIaAMAAADQoIGfHnXUX/TmFizoyagAAADAoNBpAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAAANreHg4pZQceuihq+w74ogjcuCBByZJbrjhhpRS8uMf/3iD1Ta0wa4EAAAAPO2df/Rhfbnue6786nqd/41vfCM33XRTXvrSl05SRetPpw0AAAAw0Lbffvu86EUvygc/+MF+l7ICoQ0AAAAw0EopOfvss3P11VdnwYIF/S5nGaENAAAAMPCOPPLIPO95z2uq20ZoAwAAAAy8TTbZJGeddVa+/OUv5+azUBkAAA/WSURBVGc/+1m/y0kitAEAAABIkhxzzDHZZZddct555/W7lCRCGwAAAIAkydDQUP78z/88X/jCF3Lbbbf1uxyhDQAAAMCIE088MTvssEP++q//ut+lCG0AAAAARmy22WY544wz8tnPfjZ33XVXX2sZ6uvVAQAAABpz0kkn5UMf+lC++93v5oADDlhh3zXXXJNbbrllhW177LFH9thjj0mvQ2gDAAAATJr3XPnVfpew3rbccsucdtppOeecc1bZd/rpp6+y7dxzz83w8PCk11FqrWt98Jw5c+q8efPWfODwtPUoaXXjLp70IWdfNnvSx0ySBcct6Mm4AAAA0IKFCxdm1qxZ/S5jo7Cme1VKmV9rnbPydmvaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANEtoAAAAAE7IuDzcaVOtzj4Q2AAAAwDqbOnVqHn300X6X0bxHH300U6dOndC5QhsAAABgne2www6544478sgjj+i4GUOtNY888kjuuOOO7LDDDhMaY2iSawIAAAAGwDbbbJMkufPOO/PEE0/0uZo2TZ06NTNmzFh2r9aV0AYAAACYkG222WbCgQRrZnoUAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhvpdQL8tuPX2fpcAAAAAsAqdNgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0KChfhcArL3zjz6sJ+O+58qv9mRcAAAAJk6nDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0KChfhcArL3Ntzu93yUAAACwgei0AQAAAGiQ0AYAAACgQUIbAAAAgAYJbQAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABgltAAAAABoktAEAAABokNAGAAAAoEFD/S4AWHvv2PHwHo28uEfjAgAAMFE6bQAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABgltAAAAABoktAEAAABokNAGAAAAoEFCGwAAAIAGCW0AAAAAGiS0AQAAAGiQ0AYAAACgQUIbAAAAgAYJbQAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABgltAAAAABoktAEAAABokNAGAAAAoEFD/S4AeJoantaDMRdP/pgAAACN0mkDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANGup3Aay9hS+Y1ZNxZ92ysCfjAgAAABOn0wYAAACgQUIbAAAAgAYJbQAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABgltAAAAABoktAEAAABokNAGAAAAoEFD/S6AtXfUX/Tmx7WgJ6MCAAAA60OnDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Z6MejMJVf0Ytgs6smoAAAAAO3RaQMAAADQIKENAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhvpdAGtvwa2397sEAAAAYAPRaQMAAADQIKENAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhvpdAEC/zb5s9qSPueC4BZM+JgAAMFh02gAAAAA0SGgDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANGup3AQDQbxeefP2kj/mOSw6e9DFh4Qtm9WTcWbcs7Mm4AMD60WkDAAAA0CChDQAAAECDTI8CBt6CW2/vdwkAAACr0GkDAAAA0CCdNgAATLrZl83uybgLjlvQk3EBoEUDH9rMXHJFT8Zd1JNRAQAAgEFhehQAAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDBv7pUQBAb1x48vWTPuY7Ljl40scEAGiVThsAAACABum0AQBg0i249fZ+lwAAGz2dNgAAAAAN0mkDAMBA68X6S4k1mABYfzptAAAAABoktAEAAABokNAGAAAAoEFCGwAAAIAGCW0AAAAAGiS0AQAAAGiQ0AYAAACgQUIbAAAAgAYJbQAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABg31uwAAANbOrDfd2e8SAIANSGgDAAy0hS+Y1ZNxZ92ysCfjAgCDw/QoAAAAgAbptAEAYKAdfMM7ejSybisA1o/Qht4YntajcRf3ZlwAAABojNAGgIF3yX7vmvQx35EFkz7mxqY33Qs6FwCAwWFNGwAAAIAGCW0AAAAAGiS0AQAAAGiQ0AYAAACgQUIbAAAAgAYJbQAAAAAaJLQBAAAAaNBQvwsA1t7MJVf0ZNxFPRkVYOMw60139rsEAIAxCW0AAAA2ErMvmz3pYy44bsGkjwlMDqENANATR/3F5P8zw68VAMAgsaYNAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgCxEDAAAAg214Wg/GXLzeQwhtAAAYaLPedGe/SwCAMZkeBQAAANAgoQ0AAABAg4Q2AAAAAA2ypg0AA2/Brbf3uwQAWCv+zoLBotMGAAAAoEFCGwAAAIAGCW0AAAAAGmRNGwbehSdf35Nx33HJwT0ZFwAAgMGg0wYAAACgQUIbAAAAgAYJbQAAAAAaJLQBAAAAaJDQBgAAAKBBnh7FwDv4hnf0aOSFPRoXAACAQaDTBgAAAKBBOm0AgJ5YcOvt/S4BAGCjptMGAAAAoEFCGwAAAIAGCW0AAAAAGiS0AQAAAGiQ0AYAAACgQUIbAAAAgAYJbQAAAAAaNNTvAqDfjvqL3vxnsKAnowIAADAodNoAAAAANEinDQAAMNiGp/VgzMWTPyYwcHTaAAAAADRIaAMAAADQIKENAAAAQIOsaQMAAAAbC2swDRShDQNvwa2397sEAAAAWIXpUQAAAAAN0mkD9MTMJVdM+piLJn1EAHqlF38PJP4uAGCw6LQBAAAAaJDQBgAAAKBBpkcBAAAw0Ba+YNakjznrloWTPiaDR6cNAAAAQIN02gAAbCQs7gsAg0WnDQAAAECDdNoAbERmXzZ70sdccNyCSR8TAOiNXnTcLZr0EYHJotMGAAAAoEE6bTYi5rEDwOTz9ysA0CqdNgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0KChfhcAAAAArJ2ZS66Y9DEXTfqITBadNgAAAAANEtoAAAAANEhoAwAAANAga9oAMPDMDQcAoEU6bQAAAAAaJLQBAAAAaJDpUQAAAAy0o/5i8n81XjDpIzKIdNoAAAAANEhoAwAAANAg06MYeL14akziyTEAAACsH502AAAAAA3SaQMAABuL4Wk9Gndxb8aFjcSCW2/vdwkwJp02AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQoKF+FwAAAMDT0PC0Hoy5ePLHhIbptAEAAABokE4bAABg0s2+bHZPxl1w3IKejAvQIp02AAAAAA0S2gAAAAA0SGgDAAAA0CBr2gDAxsSTOAAABoZOGwAAAIAGCW0AAAAAGmR6FDDwZi65YtLHXDTpIwIAAINGpw0AAABAg4Q2AAAAAA0yPQoAADYSvZjSm5jWC9AqoQ0AAAAw0Fpd59L0KAAAAIAGCW0AAAAAGmR6FADQE622GQMAbCyENgAADDSL+wLQKqENAL0xPK0HYy6e/DEBAKBR1rQBAAAAaJDQBgAAAKBBQhsAAACABlnTBgAAAJh0sy+bPeljLjhuwaSP2TKhDcBGZMGtt/e7BPrMY7QBAAaH6VEAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0a6ncBAAAAPP3MXHLFpI+5aNJHhLbptAEAAABokNAGAAAAoEGmRwEAAJNuwa2397sEgI2eThsAAACABgltAAAAABpkehQAADDQPOUIaJXQhp7oxV98ib/8AAAAGBymRwEAAAA0SGgDAAAA0CChDQAAAECDrGkDAADAQLMYNa3SaQMAAADQIKENAAAAQIOENgAAAAANEtoAAAAANEhoAwAAANAgoQ0AAABAg4Q2AAAAAA0S2gAAAAA0SGgDAAAA0CChDQAAAECDhDYAAAAADRrqdwEAAADA08/DCz/c7xI2ejptAAAAABoktAEAAABokNAGAAAAoEFCGwAAAIAGCW0AAAAAGuTpUQAbkZlLrpj0MRdN+ogAAMBk0GkDAAAA0CChDQAAAECDhDYAAAAADRLaAAAAADRIaAMAAADQIKENAAAAQIOENgAAAAANGup3AQA8Pc1ccsWkj7lo0kcEAIB26bQBAAAAaJDQBgAAAKBBQhsAAACABgltAAAAABoktAEAAABokKdHAQAAk64XTxFMPEkQGCw6bQAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABgltAAAAABoktAEAAABokNAGAAAAoEFCGwAAAIAGCW0AAAAAGiS0AQAAAGiQ0AYAAACgQUIbAAAAgAYJbQAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABgltAAAAABoktAEAAABokNAGAAAAoEFCGwAAAIAGCW0AAAAAGiS0AQAAAGiQ0AYAAACgQUIbAAAAgAYJbQAAAAAaJLQBAAAAaJDQBgAAAKBBQhsAAACABgltAP5v+3aIwzAQA0Dw7hHB+f+zivsIhwe1oNVKmYGWgfFKBgAACBJtAAAAAIJEGwAAAIAg0QYAAAAgSLQBAAAACBJtAAAAAIJEGwAAAIAg0QYAAAAgaM/M58t7v9dar9+dAwAAAPA458wc9+FX0QYAAACA//AeBQAAABAk2gAAAAAEiTYAAAAAQaINAAAAQJBoAwAAABAk2gAAAAAEiTYAAAAAQaINAAAAQJBoAwAAABB0AUeEiqbQD5vSAAAAAElFTkSuQmCC\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.rcParams['figure.figsize'] = [20, 10]\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = Session_country.plot.bar(stacked= True)\n",
    "#ax2 = ax.twinx()\n",
    "#ax2.plot(orders_country['All'].values, marker = 'o', linestyle = '-', color='c')\n",
    "plt.title('Amazon Session', fontsize = 25)\n",
    "plt.rc('legend', fontsize = 15)\n",
    "plt.xticks(fontsize = 15)\n",
    "plt.yticks(fontsize = 18)\n",
    "ax.set_xlabel('Date', fontsize =20)\n",
    "ax.set_ylabel('Session', fontsize =20)\n",
    "\n",
    "#축값 표시 없애고 싶을 때\n",
    "ax.axes.xaxis.set_visible(False)\n",
    "ax.axes.yaxis.set_visible(False)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = sales_country.plot.bar(stacked= True)\n",
    "plt.title('Amazon Sales(£)', fontsize = 25)\n",
    "plt.rc('legend', fontsize = 15)\n",
    "plt.xticks(fontsize = 15)\n",
    "plt.yticks(fontsize = 18)\n",
    "ax.set_xlabel('Date', fontsize =20)\n",
    "ax.set_ylabel('Sales(£)', fontsize =20)\n",
    "\n",
    "#축값 표시 없애고 싶을 때\n",
    "ax.axes.xaxis.set_visible(False)\n",
    "ax.axes.yaxis.set_visible(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "xlxs_dir = \"C:\\\\Users\\\\Joanna Kang\\\\Desktop\\\\TASK\\\\5. Data Anaylsis\\\\2020_July_trend\\\\200728_amazontotal.xlsx\"\n",
    "\n",
    "with pd.ExcelWriter(xlxs_dir) as writer:\n",
    "    Session_country.to_excel(writer, sheet_name = 'Amazon_session', index = True)\n",
    "    orders_country.to_excel(writer, sheet_name = 'Amazon_order', index = True)\n",
    "    sales_country.to_excel(writer, sheet_name = 'Amazon_sales', index = True)"
   ]
  }
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