11.5.1.모델 성능 향상을 위한 파생 변수 생성.ipynb

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   "source": [
    "# 필요한 패키지 설치\n",
    "import math\n",
    "from sklearn import preprocessing\n",
    "import datetime\n",
    "from datetime import timedelta\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "plt.rcParams['figure.dpi'] = 300"
   ]
  },
  {
   "cell_type": "code",
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       "   Unnamed: 0        Date  Customer_ID  Transaction_ID SKU_Category    SKU  \\\n",
       "0           1  02/01/2016         2547               1          X52  0EM7L   \n",
       "1           2  02/01/2016          822               2          2ML  68BRQ   \n",
       "2           3  02/01/2016         3686               3          0H2  CZUZX   \n",
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       "4           5  02/01/2016         9200               5          0H2  K8EHH   \n",
       "\n",
       "   Quantity  Sales_Amount  \n",
       "0       1.0          3.13  \n",
       "1       1.0          5.46  \n",
       "2       1.0          6.35  \n",
       "3       1.0          5.59  \n",
       "4       1.0          6.88  "
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   "source": [
    "# 데이터 불러오기\n",
    "# https://www.kaggle.com/datasets/marian447/retail-store-sales-transactions\n",
    "df = pd.read_csv(\"datasets/scanner_data.csv\")\n",
    "\n",
    "# 데이터 샘플 확인\n",
    "df.head()"
   ]
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       "        Unnamed: 0        Date  Customer_ID  Transaction_ID SKU_Category  \\\n",
       "131701      131702  04/07/2016        20203           32900          IEV   \n",
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       "\n",
       "          SKU  Quantity  Sales_Amount  Unit_amount  All_amount  \n",
       "131701  FO112       3.0          6.46     2.153333       19.38  \n",
       "131702  I36F2       1.0          4.50     4.500000        4.50  \n",
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       "131705  QM9BP       1.0         13.68    13.680000       13.68  "
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   "source": [
    "# 두 개의 변수 결합한 파생변수 생성\n",
    "\n",
    "# 구매 상품당 가격 컬럼 생성\n",
    "df['Unit_amount'] = df['Sales_Amount']/df['Quantity']\n",
    "\n",
    "# 총 구매가격 컬럼 생성\n",
    "df['All_amount'] = \\\n",
    "df[['Quantity', 'Sales_Amount']].apply(lambda series: series.prod(), axis=1)\n",
    "\n",
    "df.tail()"
   ]
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       "        Unnamed: 0        Date  Customer_ID  Transaction_ID SKU_Category  \\\n",
       "131701      131702  04/07/2016        20203           32900          IEV   \n",
       "131702      131703  04/07/2016        20203           32900          N8U   \n",
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       "131705      131706  04/07/2016        20203           32900          Q4N   \n",
       "\n",
       "          SKU  Quantity  Sales_Amount  Unit_amount  All_amount  \\\n",
       "131701  FO112       3.0          6.46     2.153333       19.38   \n",
       "131702  I36F2       1.0          4.50     4.500000        4.50   \n",
       "131703  4X8P4       1.0          5.19     5.190000        5.19   \n",
       "131704  ZVTO4       1.0          4.57     4.570000        4.57   \n",
       "131705  QM9BP       1.0         13.68    13.680000       13.68   \n",
       "\n",
       "        Sales_Amount_log  Sales_Amount_log2  Sales_Amount_sqrt  \\\n",
       "131701         -0.204581           2.009555           2.731300   \n",
       "131702         -0.592329           1.704748           2.345208   \n",
       "131703         -0.441982           1.822935           2.487971   \n",
       "131704         -0.576240           1.717395           2.360085   \n",
       "131705          0.656548           2.686486           3.831449   \n",
       "\n",
       "        Sales_Amount_pow  \n",
       "131701           41.7316  \n",
       "131702           20.2500  \n",
       "131703           26.9361  \n",
       "131704           20.8849  \n",
       "131705          187.1424  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 로그, 제곱근, 제곱 변환 파생변수 생성\n",
    "\n",
    "# 방법1.Sales_Amount 컬럼 로그 적용 (+1)\n",
    "df['Sales_Amount_log'] = preprocessing.scale(np.log(df['Sales_Amount']+1))\n",
    "\n",
    "# 방법2.Sales_Amount 컬럼 로그 적용 (+1)\n",
    "df['Sales_Amount_log2'] = df[['Sales_Amount']].apply(lambda x: np.log(x+1))    \n",
    "\n",
    "# Sales_Amount 컬럼 제곱근 적용 (+1)\n",
    "df['Sales_Amount_sqrt'] = np.sqrt(df['Sales_Amount']+1)\n",
    "\n",
    "# Sales_Amount 컬럼 제곱 적용\n",
    "df['Sales_Amount_pow'] = pow(df[['Sales_Amount']],2)\n",
    "\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '31/01/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/02/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '31/03/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/04/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '31/05/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/06/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '31/08/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/09/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '31/10/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/11/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '13/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '14/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '15/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '16/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '17/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '18/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '19/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '20/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '21/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '22/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '23/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '24/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '31/12/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '25/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '26/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '27/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '28/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '29/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '30/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n",
      "C:\\Users\\angry\\anaconda3\\lib\\site-packages\\pandas\\core\\tools\\datetimes.py:1047: UserWarning: Parsing '31/07/2016' in DD/MM/YYYY format. Provide format or specify infer_datetime_format=True for consistent parsing.\n",
      "  cache_array = _maybe_cache(arg, format, cache, convert_listlike)\n"
     ]
    },
    {
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       "      <td>K8EHH</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.88</td>\n",
       "      <td>...</td>\n",
       "      <td>2.064328</td>\n",
       "      <td>2.807134</td>\n",
       "      <td>47.3344</td>\n",
       "      <td>2016-02-01</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.880000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0        Date  Customer_ID  Transaction_ID SKU_Category    SKU  \\\n",
       "0           1  02/01/2016         2547               1          X52  0EM7L   \n",
       "1           2  02/01/2016          822               2          2ML  68BRQ   \n",
       "2           3  02/01/2016         3686               3          0H2  CZUZX   \n",
       "3           4  02/01/2016         3719               4          0H2  549KK   \n",
       "4           5  02/01/2016         9200               5          0H2  K8EHH   \n",
       "\n",
       "   Quantity  Sales_Amount  Unit_amount  All_amount  ...  Sales_Amount_log2  \\\n",
       "0       1.0          3.13         3.13        3.13  ...           1.418277   \n",
       "1       1.0          5.46         5.46        5.46  ...           1.865629   \n",
       "2       1.0          6.35         6.35        6.35  ...           1.994700   \n",
       "3       1.0          5.59         5.59        5.59  ...           1.885553   \n",
       "4       1.0          6.88         6.88        6.88  ...           2.064328   \n",
       "\n",
       "   Sales_Amount_sqrt  Sales_Amount_pow      Date2  Year  Month  Year_1_m  \\\n",
       "0           2.032240            9.7969 2016-02-01  2016      2      2016   \n",
       "1           2.541653           29.8116 2016-02-01  2016      2      2016   \n",
       "2           2.711088           40.3225 2016-02-01  2016      2      2016   \n",
       "3           2.567100           31.2481 2016-02-01  2016      2      2016   \n",
       "4           2.807134           47.3344 2016-02-01  2016      2      2016   \n",
       "\n",
       "   Month_1_m     sum      mean  \n",
       "0          2   24.76  6.190000  \n",
       "1          2    5.46  5.460000  \n",
       "2          2   73.17  5.628462  \n",
       "3          2  171.15  8.150000  \n",
       "4          2    6.88  6.880000  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 월 합계, 평균 구매금액 변수 생성\n",
    "\n",
    "# date 컬럼 날짜형식 변환\n",
    "df['Date2']= pd.to_datetime(df['Date'], infer_datetime_format=True) \n",
    "\n",
    "# 연도 컬럼 생성\n",
    "df['Year'] = df['Date2'].dt.year\n",
    "\n",
    "# 월 컬럼 생성\n",
    "df['Month'] = df['Date2'].dt.month\n",
    "\n",
    "#연월별, 고객별 매출 합계, 평균 컬럼 생성\n",
    "df_sm = df.groupby(['Year', \n",
    "                    'Month', \n",
    "                    'Customer_ID'])['Sales_Amount'].agg(['sum','mean']).reset_index()\n",
    "\n",
    "# 기존 일별 테이블에 평균 테이블 조인\n",
    "df2 = pd.merge(df, df_sm, how='left')\n",
    "\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>Customer_ID</th>\n",
       "      <th>Transaction_ID</th>\n",
       "      <th>SKU_Category</th>\n",
       "      <th>SKU</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Sales_Amount</th>\n",
       "      <th>Unit_amount</th>\n",
       "      <th>All_amount</th>\n",
       "      <th>...</th>\n",
       "      <th>Sales_Amount_sqrt</th>\n",
       "      <th>Sales_Amount_pow</th>\n",
       "      <th>Date2</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>sum</th>\n",
       "      <th>mean</th>\n",
       "      <th>Sales_Amount_Diff</th>\n",
       "      <th>Sales_Amount_UD</th>\n",
       "      <th>Sales_Amount_Rto</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>2547</td>\n",
       "      <td>1</td>\n",
       "      <td>X52</td>\n",
       "      <td>0EM7L</td>\n",
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       "      <td>3.13</td>\n",
       "      <td>3.13</td>\n",
       "      <td>3.13</td>\n",
       "      <td>...</td>\n",
       "      <td>2.032240</td>\n",
       "      <td>9.7969</td>\n",
       "      <td>2016-02-01</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>24.76</td>\n",
       "      <td>6.190000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>0.505654</td>\n",
       "      <td>0.126414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>822</td>\n",
       "      <td>2</td>\n",
       "      <td>2ML</td>\n",
       "      <td>68BRQ</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.46</td>\n",
       "      <td>...</td>\n",
       "      <td>2.541653</td>\n",
       "      <td>29.8116</td>\n",
       "      <td>2016-02-01</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.460000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>3686</td>\n",
       "      <td>3</td>\n",
       "      <td>0H2</td>\n",
       "      <td>CZUZX</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.35</td>\n",
       "      <td>6.35</td>\n",
       "      <td>6.35</td>\n",
       "      <td>...</td>\n",
       "      <td>2.711088</td>\n",
       "      <td>40.3225</td>\n",
       "      <td>2016-02-01</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>73.17</td>\n",
       "      <td>5.628462</td>\n",
       "      <td>-0.721538</td>\n",
       "      <td>1.128195</td>\n",
       "      <td>0.086784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>3719</td>\n",
       "      <td>4</td>\n",
       "      <td>0H2</td>\n",
       "      <td>549KK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.59</td>\n",
       "      <td>5.59</td>\n",
       "      <td>5.59</td>\n",
       "      <td>...</td>\n",
       "      <td>2.567100</td>\n",
       "      <td>31.2481</td>\n",
       "      <td>2016-02-01</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>171.15</td>\n",
       "      <td>8.150000</td>\n",
       "      <td>2.560000</td>\n",
       "      <td>0.685890</td>\n",
       "      <td>0.032661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>9200</td>\n",
       "      <td>5</td>\n",
       "      <td>0H2</td>\n",
       "      <td>K8EHH</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.88</td>\n",
       "      <td>...</td>\n",
       "      <td>2.807134</td>\n",
       "      <td>47.3344</td>\n",
       "      <td>2016-02-01</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.880000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0        Date  Customer_ID  Transaction_ID SKU_Category    SKU  \\\n",
       "0           1  02/01/2016         2547               1          X52  0EM7L   \n",
       "1           2  02/01/2016          822               2          2ML  68BRQ   \n",
       "2           3  02/01/2016         3686               3          0H2  CZUZX   \n",
       "3           4  02/01/2016         3719               4          0H2  549KK   \n",
       "4           5  02/01/2016         9200               5          0H2  K8EHH   \n",
       "\n",
       "   Quantity  Sales_Amount  Unit_amount  All_amount  ...  Sales_Amount_sqrt  \\\n",
       "0       1.0          3.13         3.13        3.13  ...           2.032240   \n",
       "1       1.0          5.46         5.46        5.46  ...           2.541653   \n",
       "2       1.0          6.35         6.35        6.35  ...           2.711088   \n",
       "3       1.0          5.59         5.59        5.59  ...           2.567100   \n",
       "4       1.0          6.88         6.88        6.88  ...           2.807134   \n",
       "\n",
       "   Sales_Amount_pow      Date2  Year Month     sum      mean  \\\n",
       "0            9.7969 2016-02-01  2016     2   24.76  6.190000   \n",
       "1           29.8116 2016-02-01  2016     2    5.46  5.460000   \n",
       "2           40.3225 2016-02-01  2016     2   73.17  5.628462   \n",
       "3           31.2481 2016-02-01  2016     2  171.15  8.150000   \n",
       "4           47.3344 2016-02-01  2016     2    6.88  6.880000   \n",
       "\n",
       "   Sales_Amount_Diff  Sales_Amount_UD  Sales_Amount_Rto  \n",
       "0           3.060000         0.505654          0.126414  \n",
       "1           0.000000         1.000000          1.000000  \n",
       "2          -0.721538         1.128195          0.086784  \n",
       "3           2.560000         0.685890          0.032661  \n",
       "4           0.000000         1.000000          1.000000  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 월 평균 구매금액 대비 일 별 구매금액 차이 변수 생성\n",
    "df2['Sales_Amount_Diff'] = df2['mean'] - df2['Sales_Amount']\n",
    "\n",
    "# 월 평균 구매금액 대비 일 별 구매금액 비율 변수 생성\n",
    "df2['Sales_Amount_UD'] = df2['Sales_Amount'] / df2['mean']\n",
    "    \n",
    "# 월 총 구매금액 대비 일 별 구매금액 비율 변수 생성\n",
    "df2['Sales_Amount_Rto'] = df2['Sales_Amount']/df2['sum']\n",
    "    \n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>Customer_ID</th>\n",
       "      <th>Transaction_ID</th>\n",
       "      <th>SKU_Category</th>\n",
       "      <th>SKU</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Sales_Amount</th>\n",
       "      <th>Unit_amount</th>\n",
       "      <th>All_amount</th>\n",
       "      <th>...</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>sum</th>\n",
       "      <th>mean</th>\n",
       "      <th>Sales_Amount_Diff</th>\n",
       "      <th>Sales_Amount_UD</th>\n",
       "      <th>Sales_Amount_Rto</th>\n",
       "      <th>Date2_1_m</th>\n",
       "      <th>sum_1_m</th>\n",
       "      <th>mean_1_m</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>2547</td>\n",
       "      <td>1</td>\n",
       "      <td>X52</td>\n",
       "      <td>0EM7L</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.13</td>\n",
       "      <td>3.13</td>\n",
       "      <td>3.13</td>\n",
       "      <td>...</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>24.76</td>\n",
       "      <td>6.190000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>0.505654</td>\n",
       "      <td>0.126414</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>14.32</td>\n",
       "      <td>4.773333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>822</td>\n",
       "      <td>2</td>\n",
       "      <td>2ML</td>\n",
       "      <td>68BRQ</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.46</td>\n",
       "      <td>...</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.460000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>14.05</td>\n",
       "      <td>3.512500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>3686</td>\n",
       "      <td>3</td>\n",
       "      <td>0H2</td>\n",
       "      <td>CZUZX</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.35</td>\n",
       "      <td>6.35</td>\n",
       "      <td>6.35</td>\n",
       "      <td>...</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>73.17</td>\n",
       "      <td>5.628462</td>\n",
       "      <td>-0.721538</td>\n",
       "      <td>1.128195</td>\n",
       "      <td>0.086784</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>107.83</td>\n",
       "      <td>7.188667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>3719</td>\n",
       "      <td>4</td>\n",
       "      <td>0H2</td>\n",
       "      <td>549KK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.59</td>\n",
       "      <td>5.59</td>\n",
       "      <td>5.59</td>\n",
       "      <td>...</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>171.15</td>\n",
       "      <td>8.150000</td>\n",
       "      <td>2.560000</td>\n",
       "      <td>0.685890</td>\n",
       "      <td>0.032661</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>13.21</td>\n",
       "      <td>6.605000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>9200</td>\n",
       "      <td>5</td>\n",
       "      <td>0H2</td>\n",
       "      <td>K8EHH</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.88</td>\n",
       "      <td>...</td>\n",
       "      <td>2016</td>\n",
       "      <td>2</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.880000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.880000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0        Date  Customer_ID  Transaction_ID SKU_Category    SKU  \\\n",
       "0           1  02/01/2016         2547               1          X52  0EM7L   \n",
       "1           2  02/01/2016          822               2          2ML  68BRQ   \n",
       "2           3  02/01/2016         3686               3          0H2  CZUZX   \n",
       "3           4  02/01/2016         3719               4          0H2  549KK   \n",
       "4           5  02/01/2016         9200               5          0H2  K8EHH   \n",
       "\n",
       "   Quantity  Sales_Amount  Unit_amount  All_amount  ...  Year  Month     sum  \\\n",
       "0       1.0          3.13         3.13        3.13  ...  2016      2   24.76   \n",
       "1       1.0          5.46         5.46        5.46  ...  2016      2    5.46   \n",
       "2       1.0          6.35         6.35        6.35  ...  2016      2   73.17   \n",
       "3       1.0          5.59         5.59        5.59  ...  2016      2  171.15   \n",
       "4       1.0          6.88         6.88        6.88  ...  2016      2    6.88   \n",
       "\n",
       "       mean Sales_Amount_Diff  Sales_Amount_UD  Sales_Amount_Rto  Date2_1_m  \\\n",
       "0  6.190000          3.060000         0.505654          0.126414 2016-02-29   \n",
       "1  5.460000          0.000000         1.000000          1.000000 2016-02-29   \n",
       "2  5.628462         -0.721538         1.128195          0.086784 2016-02-29   \n",
       "3  8.150000          2.560000         0.685890          0.032661 2016-02-29   \n",
       "4  6.880000          0.000000         1.000000          1.000000 2016-02-29   \n",
       "\n",
       "   sum_1_m  mean_1_m  \n",
       "0    14.32  4.773333  \n",
       "1    14.05  3.512500  \n",
       "2   107.83  7.188667  \n",
       "3    13.21  6.605000  \n",
       "4     6.88  6.880000  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 전 월 값 파생변수 생성\n",
    "\n",
    "# 4주 뒤 시점 컬럼 생성\n",
    "df2['Date2_1_m'] = df2['Date2'] + timedelta(weeks=4)\n",
    "\n",
    "# # 4주 뒤 시점연도 컬럼 생성\n",
    "df['Year_1_m'] = df2['Date2_1_m'].dt.year\n",
    "\n",
    "# # 4주 뒤 시점월 컬럼 생성\n",
    "df['Month_1_m'] = df2['Date2_1_m'].dt.month\n",
    "\n",
    "# 4주 전 구매금액 연월별, 고객별 매출 평균 컬럼 생성\n",
    "df_Mn_1 = df.groupby(['Year_1_m', \n",
    "                      'Month_1_m', \n",
    "                      'Customer_ID'])['Sales_Amount'].agg(['sum',\n",
    "                                                           'mean']).reset_index()\n",
    "\n",
    "# 조인을 위한 컬럼명 변경 \n",
    "df_Mn_1.rename(columns={'Year_1_m':'Year', \n",
    "                        'Month_1_m':'Month', \n",
    "                        'sum':\"sum_1_m\", \n",
    "                        'mean':'mean_1_m'}, inplace=True)\n",
    "\n",
    "df2 = pd.merge(df2, df_Mn_1, how='left')\n",
    "\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Date</th>\n",
       "      <th>Customer_ID</th>\n",
       "      <th>Transaction_ID</th>\n",
       "      <th>SKU_Category</th>\n",
       "      <th>SKU</th>\n",
       "      <th>Quantity</th>\n",
       "      <th>Sales_Amount</th>\n",
       "      <th>Unit_amount</th>\n",
       "      <th>All_amount</th>\n",
       "      <th>...</th>\n",
       "      <th>sum</th>\n",
       "      <th>mean</th>\n",
       "      <th>Sales_Amount_Diff</th>\n",
       "      <th>Sales_Amount_UD</th>\n",
       "      <th>Sales_Amount_Rto</th>\n",
       "      <th>Date2_1_m</th>\n",
       "      <th>sum_1_m</th>\n",
       "      <th>mean_1_m</th>\n",
       "      <th>Mn_diff_1_mean</th>\n",
       "      <th>Mn_diff_1_sum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>2547</td>\n",
       "      <td>1</td>\n",
       "      <td>X52</td>\n",
       "      <td>0EM7L</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.13</td>\n",
       "      <td>3.13</td>\n",
       "      <td>3.13</td>\n",
       "      <td>...</td>\n",
       "      <td>24.76</td>\n",
       "      <td>6.190000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>0.505654</td>\n",
       "      <td>0.126414</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>14.32</td>\n",
       "      <td>4.773333</td>\n",
       "      <td>1.416667</td>\n",
       "      <td>10.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>822</td>\n",
       "      <td>2</td>\n",
       "      <td>2ML</td>\n",
       "      <td>68BRQ</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.46</td>\n",
       "      <td>...</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.460000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>14.05</td>\n",
       "      <td>3.512500</td>\n",
       "      <td>1.947500</td>\n",
       "      <td>-8.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>3686</td>\n",
       "      <td>3</td>\n",
       "      <td>0H2</td>\n",
       "      <td>CZUZX</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.35</td>\n",
       "      <td>6.35</td>\n",
       "      <td>6.35</td>\n",
       "      <td>...</td>\n",
       "      <td>73.17</td>\n",
       "      <td>5.628462</td>\n",
       "      <td>-0.721538</td>\n",
       "      <td>1.128195</td>\n",
       "      <td>0.086784</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>107.83</td>\n",
       "      <td>7.188667</td>\n",
       "      <td>-1.560205</td>\n",
       "      <td>-34.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>3719</td>\n",
       "      <td>4</td>\n",
       "      <td>0H2</td>\n",
       "      <td>549KK</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.59</td>\n",
       "      <td>5.59</td>\n",
       "      <td>5.59</td>\n",
       "      <td>...</td>\n",
       "      <td>171.15</td>\n",
       "      <td>8.150000</td>\n",
       "      <td>2.560000</td>\n",
       "      <td>0.685890</td>\n",
       "      <td>0.032661</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>13.21</td>\n",
       "      <td>6.605000</td>\n",
       "      <td>1.545000</td>\n",
       "      <td>157.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>02/01/2016</td>\n",
       "      <td>9200</td>\n",
       "      <td>5</td>\n",
       "      <td>0H2</td>\n",
       "      <td>K8EHH</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.88</td>\n",
       "      <td>...</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.880000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2016-02-29</td>\n",
       "      <td>6.88</td>\n",
       "      <td>6.880000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0        Date  Customer_ID  Transaction_ID SKU_Category    SKU  \\\n",
       "0           1  02/01/2016         2547               1          X52  0EM7L   \n",
       "1           2  02/01/2016          822               2          2ML  68BRQ   \n",
       "2           3  02/01/2016         3686               3          0H2  CZUZX   \n",
       "3           4  02/01/2016         3719               4          0H2  549KK   \n",
       "4           5  02/01/2016         9200               5          0H2  K8EHH   \n",
       "\n",
       "   Quantity  Sales_Amount  Unit_amount  All_amount  ...     sum      mean  \\\n",
       "0       1.0          3.13         3.13        3.13  ...   24.76  6.190000   \n",
       "1       1.0          5.46         5.46        5.46  ...    5.46  5.460000   \n",
       "2       1.0          6.35         6.35        6.35  ...   73.17  5.628462   \n",
       "3       1.0          5.59         5.59        5.59  ...  171.15  8.150000   \n",
       "4       1.0          6.88         6.88        6.88  ...    6.88  6.880000   \n",
       "\n",
       "   Sales_Amount_Diff  Sales_Amount_UD Sales_Amount_Rto  Date2_1_m  sum_1_m  \\\n",
       "0           3.060000         0.505654         0.126414 2016-02-29    14.32   \n",
       "1           0.000000         1.000000         1.000000 2016-02-29    14.05   \n",
       "2          -0.721538         1.128195         0.086784 2016-02-29   107.83   \n",
       "3           2.560000         0.685890         0.032661 2016-02-29    13.21   \n",
       "4           0.000000         1.000000         1.000000 2016-02-29     6.88   \n",
       "\n",
       "   mean_1_m  Mn_diff_1_mean  Mn_diff_1_sum  \n",
       "0  4.773333        1.416667          10.44  \n",
       "1  3.512500        1.947500          -8.59  \n",
       "2  7.188667       -1.560205         -34.66  \n",
       "3  6.605000        1.545000         157.94  \n",
       "4  6.880000        0.000000           0.00  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 전 월과의 차이 파생변수 생성\n",
    "\n",
    "# 전 월 대비 구매금액 평균 차이 변수 생성\n",
    "df2['Mn_diff_1_mean'] = df2['mean'] - df2['mean_1_m']\n",
    "\n",
    "# 전 월 대비 총 구매금액 차이 변수 생성\n",
    "df2['Mn_diff_1_sum'] = df2['sum'] - df2['sum_1_m']\n",
    "\n",
    "df2.head()"
   ]
  }
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