data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importaciones esenciales\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: '/datasets/HISTORICO_PRODUCTOS.csv'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[2], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m#Cargamos lo datos históricos (datos crudos)\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/datasets/HISTORICO_PRODUCTOS.csv\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      3\u001b[0m df_org \u001b[38;5;241m=\u001b[39m df\u001b[38;5;241m.\u001b[39mcopy(\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m      4\u001b[0m df\n",
      "File \u001b[0;32m~/miniconda3/envs/cnc/lib/python3.9/site-packages/pandas/io/parsers/readers.py:948\u001b[0m, in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001b[0m\n\u001b[1;32m    935\u001b[0m kwds_defaults \u001b[38;5;241m=\u001b[39m _refine_defaults_read(\n\u001b[1;32m    936\u001b[0m     dialect,\n\u001b[1;32m    937\u001b[0m     delimiter,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    944\u001b[0m     dtype_backend\u001b[38;5;241m=\u001b[39mdtype_backend,\n\u001b[1;32m    945\u001b[0m )\n\u001b[1;32m    946\u001b[0m kwds\u001b[38;5;241m.\u001b[39mupdate(kwds_defaults)\n\u001b[0;32m--> 948\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/cnc/lib/python3.9/site-packages/pandas/io/parsers/readers.py:611\u001b[0m, in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    608\u001b[0m _validate_names(kwds\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnames\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m))\n\u001b[1;32m    610\u001b[0m \u001b[38;5;66;03m# Create the parser.\u001b[39;00m\n\u001b[0;32m--> 611\u001b[0m parser \u001b[38;5;241m=\u001b[39m \u001b[43mTextFileReader\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    613\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunksize \u001b[38;5;129;01mor\u001b[39;00m iterator:\n\u001b[1;32m    614\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m parser\n",
      "File \u001b[0;32m~/miniconda3/envs/cnc/lib/python3.9/site-packages/pandas/io/parsers/readers.py:1448\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m   1445\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moptions[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m kwds[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m   1447\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles: IOHandles \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m-> 1448\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_engine\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/cnc/lib/python3.9/site-packages/pandas/io/parsers/readers.py:1705\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[0;34m(self, f, engine)\u001b[0m\n\u001b[1;32m   1703\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m mode:\n\u001b[1;32m   1704\u001b[0m         mode \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m-> 1705\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;241m=\u001b[39m \u001b[43mget_handle\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1706\u001b[0m \u001b[43m    \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1707\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1708\u001b[0m \u001b[43m    \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1709\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcompression\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1710\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmemory_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmemory_map\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1711\u001b[0m \u001b[43m    \u001b[49m\u001b[43mis_text\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_text\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1712\u001b[0m \u001b[43m    \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding_errors\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstrict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1713\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstorage_options\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1714\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1715\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1716\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles\u001b[38;5;241m.\u001b[39mhandle\n",
      "File \u001b[0;32m~/miniconda3/envs/cnc/lib/python3.9/site-packages/pandas/io/common.py:863\u001b[0m, in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m    858\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(handle, \u001b[38;5;28mstr\u001b[39m):\n\u001b[1;32m    859\u001b[0m     \u001b[38;5;66;03m# Check whether the filename is to be opened in binary mode.\u001b[39;00m\n\u001b[1;32m    860\u001b[0m     \u001b[38;5;66;03m# Binary mode does not support 'encoding' and 'newline'.\u001b[39;00m\n\u001b[1;32m    861\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mencoding \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m ioargs\u001b[38;5;241m.\u001b[39mmode:\n\u001b[1;32m    862\u001b[0m         \u001b[38;5;66;03m# Encoding\u001b[39;00m\n\u001b[0;32m--> 863\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[1;32m    864\u001b[0m \u001b[43m            \u001b[49m\u001b[43mhandle\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    865\u001b[0m \u001b[43m            \u001b[49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    866\u001b[0m \u001b[43m            \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mioargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    867\u001b[0m \u001b[43m            \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    868\u001b[0m \u001b[43m            \u001b[49m\u001b[43mnewline\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    869\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    870\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    871\u001b[0m         \u001b[38;5;66;03m# Binary mode\u001b[39;00m\n\u001b[1;32m    872\u001b[0m         handle \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mopen\u001b[39m(handle, ioargs\u001b[38;5;241m.\u001b[39mmode)\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/datasets/HISTORICO_PRODUCTOS.csv'"
     ]
    }
   ],
   "source": [
    "#Cargamos lo datos históricos (datos crudos)\n",
    "df = pd.read_csv('./datasets/HISTORICO_PRODUCTOS.csv')\n",
    "df_org = df.copy(True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Recortamos para que la fecha de emisión no incluya la hora, ya que puede ser imprecisa\n",
    "df['FE_EMIT'] = df['FE_EMIT'].str[:11]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creamos una función que pasa de una fecha a un número desde el nacimiento de Cristo\n",
    "def date_to_num(date:str):\n",
    "    year = int(date[:4])\n",
    "    month = int(date[5:7])\n",
    "    day = int(date[8:])\n",
    "    return year*365+month*30+day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Aplicamos las funciones para pasar las fechas relevantes a un escalar\n",
    "df['FE_ENTREGA'] = df['FE_ENTREGA'].apply(lambda x: date_to_num(x))\n",
    "df['FE_EMIT'] = df['FE_EMIT'].apply(lambda x: date_to_num(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LÓGICA 1 (descontinuada)\n",
    "\n",
    "Si FE_EMIT1<FE_ENTREGA2<FE_ENTREGA1 el producto 2 existió en simúltaneo con el producto 1  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def simultaneo(fe_emit1:int, fe_entrega1:int, fe_emit2:int, fe_entrega2:int):\n",
    "    return (fe_emit1<=fe_emit2 and fe_emit2<fe_entrega1) or (fe_emit1<fe_entrega2 and fe_entrega2<fe_entrega1) or (fe_emit1>=fe_emit2 and fe_entrega1<=fe_entrega2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "empty = np.full(len(df), np.nan)\n",
    "df.insert(3, 'SIMULTANEO', empty)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cop = df.copy(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop_duplicates('PEDIDO')\n",
    "df.loc[:, 'SIMULTANEO'] = df.loc[:, 'SIMULTANEO'].apply(lambda x: np.full(len(df), np.nan))\n",
    "#df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Con pandas\n",
    "\n",
    "for i in range(len(df)):\n",
    "    row1 = df.iloc[i]\n",
    "    for k in range(i, len(df)):\n",
    "        row2 = df.iloc[k]\n",
    "        simul = simultaneo(row1[5], row1[4], row2[5], row2[4])\n",
    "        df.iloc[i][3][k] = simul\n",
    "        df.iloc[k][3][i] = simul"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Con numpy MUCHO MÁS RÁPIDO!!\n",
    "data = df.to_numpy()\n",
    "for i in range(len(df)):\n",
    "    row1 = data[i]\n",
    "    for k in range(i, len(df)):\n",
    "        row2 = data[k]\n",
    "        simul = simultaneo(row1[5], row1[4], row2[5], row2[4])\n",
    "        data[i][3][k] = simul\n",
    "        data[k][3][i] = simul"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data=data, columns=df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "611.0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum([i for i in df.iloc[0][3]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simultaneo(df.iloc[0][5], df.iloc[0][4], df.iloc[1][5], df.iloc[1][4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simultaneo(df.iloc[0][5], df.iloc[0][4], df.iloc[3][5], df.iloc[3][4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CG_PROD</th>\n",
       "      <th>DES_PROD</th>\n",
       "      <th>CANT</th>\n",
       "      <th>SIMULTANEO</th>\n",
       "      <th>FE_ENTREGA</th>\n",
       "      <th>FE_EMIT</th>\n",
       "      <th>FE_CIERRE</th>\n",
       "      <th>PEDIDO</th>\n",
       "      <th>FECHA_PREVISTA_FABRICACION</th>\n",
       "      <th>FECHA_INICIO_REAL_FABRICACION</th>\n",
       "      <th>TOT_DOL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2636F2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"F2\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60603</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1756.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2636F2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"F2\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60604</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1756.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2638G1R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"G3\" 150(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60643</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2262.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2638G1R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"G3\" 150(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60644</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2262.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2638H2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"H3\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60629</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2005.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>606</th>\n",
       "      <td>2838F4R2RAM1017</td>\n",
       "      <td>2800 1.1/2\"F3\" 900(RF)x300(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738519</td>\n",
       "      <td>738461</td>\n",
       "      <td>2023-04-11 13:52:21.773</td>\n",
       "      <td>60278</td>\n",
       "      <td>2023-04-11 07:10:47.777</td>\n",
       "      <td>2023-04-11 13:52:01.487</td>\n",
       "      <td>3503.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>607</th>\n",
       "      <td>1617A1R1RSM1010</td>\n",
       "      <td>1600 1/2\" x 1\" 150(RF) x 150(RF) Tob 1/2\"Std. ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738518</td>\n",
       "      <td>738477</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60369</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>895.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>608</th>\n",
       "      <td>1621B1R1RSM1010</td>\n",
       "      <td>1600 3/4\" x 1\" 150(RF) x 150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738518</td>\n",
       "      <td>738477</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60368</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>966.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>609</th>\n",
       "      <td>2842J1R1RSM1010</td>\n",
       "      <td>2800 2\"J3\" 150(RF)x150(RF) sellada</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738518</td>\n",
       "      <td>738477</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60370</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1996.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610</th>\n",
       "      <td>3515C3Z1</td>\n",
       "      <td>AC-500 1/2\" BSP H-H Punta eje libre g.indist.</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...</td>\n",
       "      <td>738516</td>\n",
       "      <td>738464</td>\n",
       "      <td>2023-04-05 12:13:11.807</td>\n",
       "      <td>60318</td>\n",
       "      <td>2023-04-05 07:06:20.797</td>\n",
       "      <td>2023-04-05 12:13:00.870</td>\n",
       "      <td>827.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>611 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             CG_PROD                                           DES_PROD CANT   \n",
       "0    2636F2R1RAM1017                     2600 1.1/2\"F2\" 300(RF)x150(RF)  1.0  \\\n",
       "1    2636F2R1RAM1017                     2600 1.1/2\"F2\" 300(RF)x150(RF)  1.0   \n",
       "2    2638G1R1RAM1017                     2600 1.1/2\"G3\" 150(RF)x150(RF)  1.0   \n",
       "3    2638G1R1RAM1017                     2600 1.1/2\"G3\" 150(RF)x150(RF)  1.0   \n",
       "4    2638H2R1RAM1017                     2600 1.1/2\"H3\" 300(RF)x150(RF)  1.0   \n",
       "..               ...                                                ...  ...   \n",
       "606  2838F4R2RAM1017                     2800 1.1/2\"F3\" 900(RF)x300(RF)  1.0   \n",
       "607  1617A1R1RSM1010  1600 1/2\" x 1\" 150(RF) x 150(RF) Tob 1/2\"Std. ...  1.0   \n",
       "608  1621B1R1RSM1010                   1600 3/4\" x 1\" 150(RF) x 150(RF)  1.0   \n",
       "609  2842J1R1RSM1010                 2800 2\"J3\" 150(RF)x150(RF) sellada  1.0   \n",
       "610         3515C3Z1      AC-500 1/2\" BSP H-H Punta eje libre g.indist.  1.0   \n",
       "\n",
       "                                            SIMULTANEO FE_ENTREGA FE_EMIT   \n",
       "0    [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738759  738513  \\\n",
       "1    [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738759  738513   \n",
       "2    [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738759  738513   \n",
       "3    [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738759  738513   \n",
       "4    [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738759  738513   \n",
       "..                                                 ...        ...     ...   \n",
       "606  [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738519  738461   \n",
       "607  [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738518  738477   \n",
       "608  [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738518  738477   \n",
       "609  [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738518  738477   \n",
       "610  [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, ...     738516  738464   \n",
       "\n",
       "                   FE_CIERRE PEDIDO FECHA_PREVISTA_FABRICACION   \n",
       "0                        NaN  60603                        NaN  \\\n",
       "1                        NaN  60604                        NaN   \n",
       "2                        NaN  60643                        NaN   \n",
       "3                        NaN  60644                        NaN   \n",
       "4                        NaN  60629                        NaN   \n",
       "..                       ...    ...                        ...   \n",
       "606  2023-04-11 13:52:21.773  60278    2023-04-11 07:10:47.777   \n",
       "607                      NaN  60369                        NaN   \n",
       "608                      NaN  60368                        NaN   \n",
       "609                      NaN  60370                        NaN   \n",
       "610  2023-04-05 12:13:11.807  60318    2023-04-05 07:06:20.797   \n",
       "\n",
       "    FECHA_INICIO_REAL_FABRICACION  TOT_DOL  \n",
       "0                             NaN  1756.25  \n",
       "1                             NaN  1756.25  \n",
       "2                             NaN  2262.56  \n",
       "3                             NaN  2262.56  \n",
       "4                             NaN  2005.02  \n",
       "..                            ...      ...  \n",
       "606       2023-04-11 13:52:01.487   3503.0  \n",
       "607                           NaN    895.4  \n",
       "608                           NaN    966.9  \n",
       "609                           NaN   1996.5  \n",
       "610       2023-04-05 12:13:00.870    827.2  \n",
       "\n",
       "[611 rows x 11 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[np.asarray([i for i in df.iloc[0][3]], dtype=bool)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array(['2600', '2800', '1800', 'AC-350 ', '1700', '2100', '2400',\n",
       "        'AC/R-50', '1600', 'AR-30 1', 'AR-30 2', 'AR-20 1', '9300', '1100',\n",
       "        '3000', '2805', 'Junta c', '2405', '1804', '1900', '1500', '1400',\n",
       "        'AR-20 2', 'VA-1000', '9200', '9100', '1200', 'AC/R-35', 'AR-50 1',\n",
       "        '1805', 'AC-500 ', 'AR-10 1', 'VA-3000', 'AC-900 ', 'AR-10 3',\n",
       "        '6800', 'AC/R-90', 'CALENTA', 'AR-30 4', 'AR-20 6', 'AR-10 4',\n",
       "        'AR-70 1', 'AR-30 3', 'AR-70 3', 'VA-1400', 'AR-40 1', 'VA-1200',\n",
       "        'PILOTO ', 'ACR-900', 'Filtro ', 'AC-200 ', 'AR-90 1'],\n",
       "       dtype=object),\n",
       " 52]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['DES_PROD'].str[:4].unique()\n",
    "PRODUCTS = ['2600', '2800', '1800', '1700', '2100', '2400', '1600', '9300', '1100', '3000', '2805', '2405', '1804', '1900', '1500', '1400', '9200', '9100', '1200', '1805', '6800']\n",
    "NAME_LEN = 7\n",
    "[df['DES_PROD'].apply(lambda x: x[:4] if x[:4] in PRODUCTS else x).str[:NAME_LEN].unique(), \n",
    " len(df['DES_PROD'].apply(lambda x: x[:4] if x[:4] in PRODUCTS else x).str[:NAME_LEN].unique())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(index=(df[df['FE_EMIT']==df['FE_ENTREGA']].index), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "501"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('HISTORICO_SIMUL.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CG_PROD</th>\n",
       "      <th>DES_PROD</th>\n",
       "      <th>CANT</th>\n",
       "      <th>FE_ENTREGA</th>\n",
       "      <th>FE_EMIT</th>\n",
       "      <th>FE_CIERRE</th>\n",
       "      <th>PEDIDO</th>\n",
       "      <th>FECHA_PREVISTA_FABRICACION</th>\n",
       "      <th>FECHA_INICIO_REAL_FABRICACION</th>\n",
       "      <th>TOT_DOL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2636F2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"F2\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2023-12-04</td>\n",
       "      <td>2023-03-28 11:27:43.360</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60603</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1756.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2636F2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"F2\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2023-12-04</td>\n",
       "      <td>2023-03-28 11:27:43.987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60604</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1756.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2638G1R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"G3\" 150(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2023-12-04</td>\n",
       "      <td>2023-03-28 11:28:07.730</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60643</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2262.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2638G1R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"G3\" 150(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2023-12-04</td>\n",
       "      <td>2023-03-28 11:28:08.310</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60644</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2262.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2638H2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"H3\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2023-12-04</td>\n",
       "      <td>2023-03-28 11:27:59.260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60629</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2005.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3505</th>\n",
       "      <td>2142H2R1RAM1013</td>\n",
       "      <td>2100 2\"H3\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2019-10-17</td>\n",
       "      <td>2020-01-10 11:04:06.967</td>\n",
       "      <td>2020-01-24 00:00:00.000</td>\n",
       "      <td>55960</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1503.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3506</th>\n",
       "      <td>2142J1R1RAM1012</td>\n",
       "      <td>2100 2\"J3\" 150(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2019-10-17</td>\n",
       "      <td>2020-01-13 08:15:30.187</td>\n",
       "      <td>2020-01-24 00:00:00.000</td>\n",
       "      <td>55955</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1384.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3507</th>\n",
       "      <td>2142J2R1RAM1012</td>\n",
       "      <td>2100 2\"J3\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2019-10-17</td>\n",
       "      <td>2020-01-10 11:04:12.380</td>\n",
       "      <td>2020-01-28 13:54:49.903</td>\n",
       "      <td>55957</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1398.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3508</th>\n",
       "      <td>2842J1R1RFM1010</td>\n",
       "      <td>2800 2\"J3\" 150(RF)x150(RF) Con Palanca</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2019-03-06</td>\n",
       "      <td>2020-01-28 09:26:21.813</td>\n",
       "      <td>NaN</td>\n",
       "      <td>56407</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3509</th>\n",
       "      <td>2842J1R1RFM1010</td>\n",
       "      <td>2800 2\"J3\" 150(RF)x150(RF) Con Palanca</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2019-03-06</td>\n",
       "      <td>2020-01-28 09:26:22.180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>56408</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3506 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              CG_PROD                                DES_PROD  CANT  \\\n",
       "0     2636F2R1RAM1017          2600 1.1/2\"F2\" 300(RF)x150(RF)   1.0   \n",
       "1     2636F2R1RAM1017          2600 1.1/2\"F2\" 300(RF)x150(RF)   1.0   \n",
       "2     2638G1R1RAM1017          2600 1.1/2\"G3\" 150(RF)x150(RF)   1.0   \n",
       "3     2638G1R1RAM1017          2600 1.1/2\"G3\" 150(RF)x150(RF)   1.0   \n",
       "4     2638H2R1RAM1017          2600 1.1/2\"H3\" 300(RF)x150(RF)   1.0   \n",
       "...               ...                                     ...   ...   \n",
       "3505  2142H2R1RAM1013              2100 2\"H3\" 300(RF)x150(RF)   1.0   \n",
       "3506  2142J1R1RAM1012              2100 2\"J3\" 150(RF)x150(RF)   1.0   \n",
       "3507  2142J2R1RAM1012              2100 2\"J3\" 300(RF)x150(RF)   1.0   \n",
       "3508  2842J1R1RFM1010  2800 2\"J3\" 150(RF)x150(RF) Con Palanca   1.0   \n",
       "3509  2842J1R1RFM1010  2800 2\"J3\" 150(RF)x150(RF) Con Palanca   1.0   \n",
       "\n",
       "      FE_ENTREGA                  FE_EMIT                FE_CIERRE  PEDIDO  \\\n",
       "0     2023-12-04  2023-03-28 11:27:43.360                      NaN   60603   \n",
       "1     2023-12-04  2023-03-28 11:27:43.987                      NaN   60604   \n",
       "2     2023-12-04  2023-03-28 11:28:07.730                      NaN   60643   \n",
       "3     2023-12-04  2023-03-28 11:28:08.310                      NaN   60644   \n",
       "4     2023-12-04  2023-03-28 11:27:59.260                      NaN   60629   \n",
       "...          ...                      ...                      ...     ...   \n",
       "3505  2019-10-17  2020-01-10 11:04:06.967  2020-01-24 00:00:00.000   55960   \n",
       "3506  2019-10-17  2020-01-13 08:15:30.187  2020-01-24 00:00:00.000   55955   \n",
       "3507  2019-10-17  2020-01-10 11:04:12.380  2020-01-28 13:54:49.903   55957   \n",
       "3508  2019-03-06  2020-01-28 09:26:21.813                      NaN   56407   \n",
       "3509  2019-03-06  2020-01-28 09:26:22.180                      NaN   56408   \n",
       "\n",
       "     FECHA_PREVISTA_FABRICACION FECHA_INICIO_REAL_FABRICACION  TOT_DOL  \n",
       "0                           NaN                           NaN  1756.25  \n",
       "1                           NaN                           NaN  1756.25  \n",
       "2                           NaN                           NaN  2262.56  \n",
       "3                           NaN                           NaN  2262.56  \n",
       "4                           NaN                           NaN  2005.02  \n",
       "...                         ...                           ...      ...  \n",
       "3505                        NaN                           NaN  1503.36  \n",
       "3506                        NaN                           NaN  1384.32  \n",
       "3507                        NaN                           NaN  1398.72  \n",
       "3508                        NaN                           NaN     0.00  \n",
       "3509                        NaN                           NaN     0.00  \n",
       "\n",
       "[3506 rows x 10 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_org.drop_duplicates('PEDIDO')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(CG_PROD                                         2636F2R1RAM1017\n",
       " DES_PROD                         2600 1.1/2\"F2\" 300(RF)x150(RF)\n",
       " CANT                                                        1.0\n",
       " FE_ENTREGA                                           2023-12-04\n",
       " FE_EMIT                                 2023-03-28 11:27:43.360\n",
       " FE_CIERRE                                                   NaN\n",
       " PEDIDO                                                    60603\n",
       " FECHA_PREVISTA_FABRICACION                                  NaN\n",
       " FECHA_INICIO_REAL_FABRICACION                               NaN\n",
       " TOT_DOL                                                 1756.25\n",
       " Name: 0, dtype: object,\n",
       " CG_PROD                                     2666Q1R1RBB3117\n",
       " DES_PROD                         2600 6\"Q8\" 150(RF)x150(RF)\n",
       " CANT                                                    1.0\n",
       " FE_ENTREGA                                       2023-05-28\n",
       " FE_EMIT                             2023-02-28 07:17:56.483\n",
       " FE_CIERRE                           2023-06-21 15:18:10.490\n",
       " PEDIDO                                                60395\n",
       " FECHA_PREVISTA_FABRICACION          2023-06-21 11:27:40.537\n",
       " FECHA_INICIO_REAL_FABRICACION       2023-06-21 15:17:41.180\n",
       " TOT_DOL                                              8436.8\n",
       " Name: 500, dtype: object)"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_org.iloc[0], df_org.iloc[500]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array(['2600', '2800', '1800', 'AC-3', '1700', '2100', '2400', 'AC/R',\n",
       "        '1600', 'AR-3', 'AR-2', '9300', '1100', '3000', '2805', 'Junt',\n",
       "        '2405', '1804', '1900', '1500', '1400', 'VA-1', '9200', '9100',\n",
       "        '1200', 'AR-5', '1805', 'AC-5', 'AR-1', 'VA-3', 'AC-9', '6800',\n",
       "        'CALE', 'AR-7', 'AR-4', 'PILO', 'ACR-', 'Filt', 'AC-2', 'AR-9'],\n",
       "       dtype=object),\n",
       " array(['2600 1.', '2800 1.', '2600 3\"', '1800 1\"', '2800 6\"', 'AC-350 ',\n",
       "        '1800 2\"', '2800 3\"', '1700 3/', '1800 1/', '1800 3/', '2100 1\"',\n",
       "        '2100 1.', '1800 1.', '2800 1\"', '1700 1/', '2400 3\"', '2800 2\"',\n",
       "        'AC/R-50', '2600 1\"', '1700 1\"', '1800 AP', '2800 4\"', '1600 3/',\n",
       "        'AR-30 1', 'AR-30 2', 'AR-20 1', '9300 8\"', '1100 3/', '9300 6\"',\n",
       "        '3000 VA', '2805 2\"', '2400 1.', 'Junta c', '1800 2.', '2405 1.',\n",
       "        '1600 1\"', '2100 4\"', '2600 4\"', '1804 1\"', '1804 1/', '1900 3/',\n",
       "        '2600 2\"', '1500 1/', '1400 1/', 'AR-20 2', 'VA-1000', '9200 3\"',\n",
       "        '9300 4\"', '2600 6\"', '2800 8\"', '1400 3/', '1600 1/', '9100 1/',\n",
       "        '1200 1/', 'AC/R-35', 'AR-50 1', '1805 1/', 'AC-500 ', 'AR-10 1',\n",
       "        'VA-3000', 'AC-900 ', '2100 3\"', '2800 2.', 'AR-10 3', '1700 1.',\n",
       "        '2400 2\"', '6800 1.', '9100 1\"', 'AC/R-90', 'CALENTA', '1700 AP',\n",
       "        '1805 3/', '1400 1\"', 'AR-30 4', '9100 3/', '1800 3\"', 'AR-20 6',\n",
       "        'AR-10 4', 'AR-70 1', 'AR-30 3', '2100 2\"', '1800  A', '1900 1/',\n",
       "        '1200 1\"', 'AR-70 3', '2805 4\"', '1700 2\"', '9100 1.', '1500 3/',\n",
       "        'VA-1400', 'AR-40 1', 'VA-1200', '1200 3/', '1804 2.', '2600 8\"',\n",
       "        '9200 2\"', 'PILOTO ', 'ACR-900', 'Filtro ', 'AC-200 ', 'AR-90 1',\n",
       "        '1500 1\"'], dtype=object))"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_org['DES_PROD'].str[:4].unique(), df_org['DES_PROD'].str[:7].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('HISTORICO_SIMUL_1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>CG_PROD</th>\n",
       "      <th>DES_PROD</th>\n",
       "      <th>CANT</th>\n",
       "      <th>SIMULTANEO</th>\n",
       "      <th>FE_ENTREGA</th>\n",
       "      <th>FE_EMIT</th>\n",
       "      <th>FE_CIERRE</th>\n",
       "      <th>PEDIDO</th>\n",
       "      <th>FECHA_PREVISTA_FABRICACION</th>\n",
       "      <th>FECHA_INICIO_REAL_FABRICACION</th>\n",
       "      <th>TOT_DOL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2636F2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"F2\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60603</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1756.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2638G1R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"G3\" 150(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60643</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2262.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>2638H2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"H3\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60629</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2005.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>2838H1R1RSM1014</td>\n",
       "      <td>2800 1.1/2\"H3\" 150(RF)x150(RF) sellada</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 1. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738742</td>\n",
       "      <td>738597</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61272</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1480.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14</td>\n",
       "      <td>2651K1R1RBM1016</td>\n",
       "      <td>2600 3\"K4\" 150(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738718</td>\n",
       "      <td>738534</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60765</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3355.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>724</th>\n",
       "      <td>3477</td>\n",
       "      <td>2128E3R1RAM1013</td>\n",
       "      <td>2100 1\"E2\" 600(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737352</td>\n",
       "      <td>737352</td>\n",
       "      <td>2020-01-24 00:00:00.000</td>\n",
       "      <td>55962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1158.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>3482</td>\n",
       "      <td>1821X9M9HKM1310</td>\n",
       "      <td>1800 3/4\"x1\" NPT(M)xNPT(H) Palanca Sellada</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737345</td>\n",
       "      <td>737345</td>\n",
       "      <td>2020-01-28 00:00:00.000</td>\n",
       "      <td>56269</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>440.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>726</th>\n",
       "      <td>3499</td>\n",
       "      <td>2836F3R1RAM3113</td>\n",
       "      <td>2800 1.1/2\"F2\" 600(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "      <td>2020-03-04 00:00:00.000</td>\n",
       "      <td>56238</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2390.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>727</th>\n",
       "      <td>3500</td>\n",
       "      <td>3515C3Z1</td>\n",
       "      <td>AC-500 1/2\" BSP H-H Punta eje libre g.indist.</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "      <td>2020-01-20 00:00:00.000</td>\n",
       "      <td>56244</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>683.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>3503</td>\n",
       "      <td>3620V7H1</td>\n",
       "      <td>VA-1000 3/4\" BSP H-H punta de eje libre giro h...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737304</td>\n",
       "      <td>737304</td>\n",
       "      <td>2020-01-20 00:00:00.000</td>\n",
       "      <td>56227</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1943.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>729 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0          CG_PROD  \\\n",
       "0             0  2636F2R1RAM1017   \n",
       "1             2  2638G1R1RAM1017   \n",
       "2             4  2638H2R1RAM1017   \n",
       "3            10  2838H1R1RSM1014   \n",
       "4            14  2651K1R1RBM1016   \n",
       "..          ...              ...   \n",
       "724        3477  2128E3R1RAM1013   \n",
       "725        3482  1821X9M9HKM1310   \n",
       "726        3499  2836F3R1RAM3113   \n",
       "727        3500  3515C3Z1          \n",
       "728        3503  3620V7H1          \n",
       "\n",
       "                                              DES_PROD  CANT  \\\n",
       "0                       2600 1.1/2\"F2\" 300(RF)x150(RF)   1.0   \n",
       "1                       2600 1.1/2\"G3\" 150(RF)x150(RF)   1.0   \n",
       "2                       2600 1.1/2\"H3\" 300(RF)x150(RF)   1.0   \n",
       "3               2800 1.1/2\"H3\" 150(RF)x150(RF) sellada   1.0   \n",
       "4                           2600 3\"K4\" 150(RF)x150(RF)   1.0   \n",
       "..                                                 ...   ...   \n",
       "724                         2100 1\"E2\" 600(RF)x150(RF)   1.0   \n",
       "725         1800 3/4\"x1\" NPT(M)xNPT(H) Palanca Sellada   1.0   \n",
       "726                     2800 1.1/2\"F2\" 600(RF)x150(RF)   1.0   \n",
       "727      AC-500 1/2\" BSP H-H Punta eje libre g.indist.   1.0   \n",
       "728  VA-1000 3/4\" BSP H-H punta de eje libre giro h...   1.0   \n",
       "\n",
       "                                            SIMULTANEO  FE_ENTREGA  FE_EMIT  \\\n",
       "0    [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738759   738513   \n",
       "1    [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738759   738513   \n",
       "2    [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738759   738513   \n",
       "3    [0. 0. 0. 1. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738742   738597   \n",
       "4    [0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738718   738534   \n",
       "..                                                 ...         ...      ...   \n",
       "724  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737352   737352   \n",
       "725  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737345   737345   \n",
       "726  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737318   737318   \n",
       "727  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737318   737318   \n",
       "728  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737304   737304   \n",
       "\n",
       "                   FE_CIERRE  PEDIDO FECHA_PREVISTA_FABRICACION  \\\n",
       "0                        NaN   60603                        NaN   \n",
       "1                        NaN   60643                        NaN   \n",
       "2                        NaN   60629                        NaN   \n",
       "3                        NaN   61272                        NaN   \n",
       "4                        NaN   60765                        NaN   \n",
       "..                       ...     ...                        ...   \n",
       "724  2020-01-24 00:00:00.000   55962                        NaN   \n",
       "725  2020-01-28 00:00:00.000   56269                        NaN   \n",
       "726  2020-03-04 00:00:00.000   56238                        NaN   \n",
       "727  2020-01-20 00:00:00.000   56244                        NaN   \n",
       "728  2020-01-20 00:00:00.000   56227                        NaN   \n",
       "\n",
       "    FECHA_INICIO_REAL_FABRICACION  TOT_DOL  \n",
       "0                             NaN  1756.25  \n",
       "1                             NaN  2262.56  \n",
       "2                             NaN  2005.02  \n",
       "3                             NaN  1480.80  \n",
       "4                             NaN  3355.80  \n",
       "..                            ...      ...  \n",
       "724                           NaN  1158.72  \n",
       "725                           NaN   440.00  \n",
       "726                           NaN  2390.00  \n",
       "727                           NaN   683.00  \n",
       "728                           NaN  1943.20  \n",
       "\n",
       "[729 rows x 12 columns]"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('HISTORICO_SIMUL.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "del df['Unnamed: 0']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>CG_PROD</th>\n",
       "      <th>DES_PROD</th>\n",
       "      <th>CANT</th>\n",
       "      <th>SIMULTANEO</th>\n",
       "      <th>FE_ENTREGA</th>\n",
       "      <th>FE_EMIT</th>\n",
       "      <th>FE_CIERRE</th>\n",
       "      <th>PEDIDO</th>\n",
       "      <th>FECHA_PREVISTA_FABRICACION</th>\n",
       "      <th>FECHA_INICIO_REAL_FABRICACION</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2636F2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"F2\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1756.25</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2638G1R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"G3\" 150(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60643</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2262.56</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>2638H2R1RAM1017</td>\n",
       "      <td>2600 1.1/2\"H3\" 300(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738759</td>\n",
       "      <td>738513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60629</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2005.02</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>2838H1R1RSM1014</td>\n",
       "      <td>2800 1.1/2\"H3\" 150(RF)x150(RF) sellada</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 1. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738742</td>\n",
       "      <td>738597</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61272</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1480.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14</td>\n",
       "      <td>2651K1R1RBM1016</td>\n",
       "      <td>2600 3\"K4\" 150(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...</td>\n",
       "      <td>738718</td>\n",
       "      <td>738534</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60765</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3355.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>724</th>\n",
       "      <td>3477</td>\n",
       "      <td>2128E3R1RAM1013</td>\n",
       "      <td>2100 1\"E2\" 600(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737352</td>\n",
       "      <td>737352</td>\n",
       "      <td>2020-01-24 00:00:00.000</td>\n",
       "      <td>55962</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1158.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>3482</td>\n",
       "      <td>1821X9M9HKM1310</td>\n",
       "      <td>1800 3/4\"x1\" NPT(M)xNPT(H) Palanca Sellada</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737345</td>\n",
       "      <td>737345</td>\n",
       "      <td>2020-01-28 00:00:00.000</td>\n",
       "      <td>56269</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>440.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>726</th>\n",
       "      <td>3499</td>\n",
       "      <td>2836F3R1RAM3113</td>\n",
       "      <td>2800 1.1/2\"F2\" 600(RF)x150(RF)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "      <td>2020-03-04 00:00:00.000</td>\n",
       "      <td>56238</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2390.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>727</th>\n",
       "      <td>3500</td>\n",
       "      <td>3515C3Z1</td>\n",
       "      <td>AC-500 1/2\" BSP H-H Punta eje libre g.indist.</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "      <td>2020-01-20 00:00:00.000</td>\n",
       "      <td>56244</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>683.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>728</th>\n",
       "      <td>3503</td>\n",
       "      <td>3620V7H1</td>\n",
       "      <td>VA-1000 3/4\" BSP H-H punta de eje libre giro h...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...</td>\n",
       "      <td>737304</td>\n",
       "      <td>737304</td>\n",
       "      <td>2020-01-20 00:00:00.000</td>\n",
       "      <td>56227</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1943.20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>729 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0          CG_PROD  \\\n",
       "0             0  2636F2R1RAM1017   \n",
       "1             2  2638G1R1RAM1017   \n",
       "2             4  2638H2R1RAM1017   \n",
       "3            10  2838H1R1RSM1014   \n",
       "4            14  2651K1R1RBM1016   \n",
       "..          ...              ...   \n",
       "724        3477  2128E3R1RAM1013   \n",
       "725        3482  1821X9M9HKM1310   \n",
       "726        3499  2836F3R1RAM3113   \n",
       "727        3500  3515C3Z1          \n",
       "728        3503  3620V7H1          \n",
       "\n",
       "                                              DES_PROD  CANT  \\\n",
       "0                       2600 1.1/2\"F2\" 300(RF)x150(RF)   1.0   \n",
       "1                       2600 1.1/2\"G3\" 150(RF)x150(RF)   1.0   \n",
       "2                       2600 1.1/2\"H3\" 300(RF)x150(RF)   1.0   \n",
       "3               2800 1.1/2\"H3\" 150(RF)x150(RF) sellada   1.0   \n",
       "4                           2600 3\"K4\" 150(RF)x150(RF)   1.0   \n",
       "..                                                 ...   ...   \n",
       "724                         2100 1\"E2\" 600(RF)x150(RF)   1.0   \n",
       "725         1800 3/4\"x1\" NPT(M)xNPT(H) Palanca Sellada   1.0   \n",
       "726                     2800 1.1/2\"F2\" 600(RF)x150(RF)   1.0   \n",
       "727      AC-500 1/2\" BSP H-H Punta eje libre g.indist.   1.0   \n",
       "728  VA-1000 3/4\" BSP H-H punta de eje libre giro h...   1.0   \n",
       "\n",
       "                                            SIMULTANEO  FE_ENTREGA  FE_EMIT  \\\n",
       "0    [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738759   738513   \n",
       "1    [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738759   738513   \n",
       "2    [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738759   738513   \n",
       "3    [0. 0. 0. 1. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738742   738597   \n",
       "4    [0. 0. 0. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ...      738718   738534   \n",
       "..                                                 ...         ...      ...   \n",
       "724  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737352   737352   \n",
       "725  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737345   737345   \n",
       "726  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737318   737318   \n",
       "727  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737318   737318   \n",
       "728  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. ...      737304   737304   \n",
       "\n",
       "                   FE_CIERRE  PEDIDO FECHA_PREVISTA_FABRICACION  \\\n",
       "0                        NaN   60603                        NaN   \n",
       "1                        NaN   60643                        NaN   \n",
       "2                        NaN   60629                        NaN   \n",
       "3                        NaN   61272                        NaN   \n",
       "4                        NaN   60765                        NaN   \n",
       "..                       ...     ...                        ...   \n",
       "724  2020-01-24 00:00:00.000   55962                        NaN   \n",
       "725  2020-01-28 00:00:00.000   56269                        NaN   \n",
       "726  2020-03-04 00:00:00.000   56238                        NaN   \n",
       "727  2020-01-20 00:00:00.000   56244                        NaN   \n",
       "728  2020-01-20 00:00:00.000   56227                        NaN   \n",
       "\n",
       "    FECHA_INICIO_REAL_FABRICACION  TOT_DOL  \n",
       "0                             NaN  1756.25  \n",
       "1                             NaN  2262.56  \n",
       "2                             NaN  2005.02  \n",
       "3                             NaN  1480.80  \n",
       "4                             NaN  3355.80  \n",
       "..                            ...      ...  \n",
       "724                           NaN  1158.72  \n",
       "725                           NaN   440.00  \n",
       "726                           NaN  2390.00  \n",
       "727                           NaN   683.00  \n",
       "728                           NaN  1943.20  \n",
       "\n",
       "[729 rows x 12 columns]"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lógica 2 (vigente)\n",
    "\n",
    "Si FE_EMIT2<FE_ENTREGA1 el producto 2 existió en simúltaneo con el producto 1, estando los productos ordenados por FE_ENTREGA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lo primero que hacemos es limpiar el dataset eliminando los pedidos repetidos\n",
    "dt = df.drop_duplicates('PEDIDO')\n",
    "dt = dt[['PEDIDO', 'FE_EMIT', 'FE_ENTREGA']].copy(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>3504</th>\n",
       "      <td>55961</td>\n",
       "      <td>737340</td>\n",
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       "    <tr>\n",
       "      <th>3507</th>\n",
       "      <td>55957</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60629</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60644</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>60643</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60604</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>60603</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3506 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PEDIDO  FE_EMIT  FE_ENTREGA\n",
       "3509   56408   737358      737031\n",
       "3508   56407   737358      737031\n",
       "3506   55955   737343      737252\n",
       "3504   55961   737340      737252\n",
       "3507   55957   737340      737252\n",
       "...      ...      ...         ...\n",
       "4      60629   738513      738759\n",
       "3      60644   738513      738759\n",
       "2      60643   738513      738759\n",
       "1      60604   738513      738759\n",
       "0      60603   738513      738759\n",
       "\n",
       "[3506 rows x 3 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Luego ordenamos el dataset según las fechas de entrega que ya fueron convertidas a días\n",
    "dt.sort_values('FE_ENTREGA', inplace=True)\n",
    "dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 56227, 737304, 737304],\n",
       "       [ 56226, 737305, 737305],\n",
       "       [ 56231, 737306, 737306],\n",
       "       ...,\n",
       "       [ 60643, 738513, 738759],\n",
       "       [ 60604, 738513, 738759],\n",
       "       [ 60603, 738513, 738759]], dtype=int64)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Creamos un arreglo X donde se almacenarán los ejemplos de entrenamiento (la secuencia temporal de los productos hechos)\n",
    "X = []\n",
    "data = dt.to_numpy() \n",
    "dt = dt.drop(dt[data[:, 1]>data[:,2]].index) #Eliminamos datos anómalos en los que la fecha de entrega se dió antes que la fecha de emisión\n",
    "data = dt.to_numpy() #Convertimos los datos a numpy para mayor velocidad y simpleza\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PEDIDO</th>\n",
       "      <th>FE_EMIT</th>\n",
       "      <th>FE_ENTREGA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3503</th>\n",
       "      <td>56227</td>\n",
       "      <td>737304</td>\n",
       "      <td>737304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3502</th>\n",
       "      <td>56226</td>\n",
       "      <td>737305</td>\n",
       "      <td>737305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3501</th>\n",
       "      <td>56231</td>\n",
       "      <td>737306</td>\n",
       "      <td>737306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3499</th>\n",
       "      <td>56238</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3500</th>\n",
       "      <td>56244</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60629</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60644</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>60643</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60604</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>60603</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3415 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PEDIDO  FE_EMIT  FE_ENTREGA\n",
       "3503   56227   737304      737304\n",
       "3502   56226   737305      737305\n",
       "3501   56231   737306      737306\n",
       "3499   56238   737318      737318\n",
       "3500   56244   737318      737318\n",
       "...      ...      ...         ...\n",
       "4      60629   738513      738759\n",
       "3      60644   738513      738759\n",
       "2      60643   738513      738759\n",
       "1      60604   738513      738759\n",
       "0      60603   738513      738759\n",
       "\n",
       "[3415 rows x 3 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True, ...,  True,  True,  True])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Esta verificación lo único que hace es chequear que el último \n",
    "elemento fue el último en ser entregado, \n",
    "por ello esta lleno de True ya que todos los productos que lo \n",
    "preceden tuvieron fechas de inicio previas a la fecha de cierre del último\n",
    "\"\"\"\n",
    "data[0:len(dt), 1]<=data[len(dt)-1, 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "Para todo el dataset lo que se hace es buscar los productos que hayan sido producidos previo la fecha de cierre del elemento i\n",
    "A su vez, al avanzar de producto se verifica que la fecha de entrega de ese producto sea única, si no lo es lo que se hace es\n",
    "buscar el primer producto que tenga esa fecha de entrega e incluir de ahí en adelante (ya que de otra forma productos entregados\n",
    "el mismo día tendrían diferentes ventanas cuando en realidad esto no sucedio de este modo). De ser única la fecha de entrega lo que\n",
    "se hace es simplemente indexar de ahí en adelante ya que los productos previos ya fueron entregados, por lo que el modelo no debería\n",
    "de importarle.\n",
    "\"\"\"\n",
    "for i in range(len(dt)):\n",
    "    index = np.argmax(data[:, 2]==data[i, 2])\n",
    "    X.append(np.concatenate(([False for j in range(index)], data[index:, 1]<=data[i, 2])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Lo que se hace es simplemente mapear las máscaras de simultaneo a los pedidos\n",
    "pedidos = [dt[np.asarray(i, dtype=bool)]['PEDIDO'].to_numpy() for i in X]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Se inserta una columna en el df que dice los productos que coexistieron\n",
    "dt.insert(3, 'SIMUL', value = pedidos)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PEDIDO</th>\n",
       "      <th>FE_EMIT</th>\n",
       "      <th>FE_ENTREGA</th>\n",
       "      <th>SIMUL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3503</th>\n",
       "      <td>56227</td>\n",
       "      <td>737304</td>\n",
       "      <td>737304</td>\n",
       "      <td>[56227]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3502</th>\n",
       "      <td>56226</td>\n",
       "      <td>737305</td>\n",
       "      <td>737305</td>\n",
       "      <td>[56226]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3501</th>\n",
       "      <td>56231</td>\n",
       "      <td>737306</td>\n",
       "      <td>737306</td>\n",
       "      <td>[56231]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3499</th>\n",
       "      <td>56238</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "      <td>[56238, 56244]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3500</th>\n",
       "      <td>56244</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "      <td>[56238, 56244]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60629</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[60634, 60633, 60632, 60631, 60630, 60629, 606...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60644</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[60634, 60633, 60632, 60631, 60630, 60629, 606...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>60643</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[60634, 60633, 60632, 60631, 60630, 60629, 606...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60604</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[60634, 60633, 60632, 60631, 60630, 60629, 606...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>60603</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[60634, 60633, 60632, 60631, 60630, 60629, 606...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3415 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PEDIDO  FE_EMIT  FE_ENTREGA  \\\n",
       "3503   56227   737304      737304   \n",
       "3502   56226   737305      737305   \n",
       "3501   56231   737306      737306   \n",
       "3499   56238   737318      737318   \n",
       "3500   56244   737318      737318   \n",
       "...      ...      ...         ...   \n",
       "4      60629   738513      738759   \n",
       "3      60644   738513      738759   \n",
       "2      60643   738513      738759   \n",
       "1      60604   738513      738759   \n",
       "0      60603   738513      738759   \n",
       "\n",
       "                                                  SIMUL  \n",
       "3503                                            [56227]  \n",
       "3502                                            [56226]  \n",
       "3501                                            [56231]  \n",
       "3499                                     [56238, 56244]  \n",
       "3500                                     [56238, 56244]  \n",
       "...                                                 ...  \n",
       "4     [60634, 60633, 60632, 60631, 60630, 60629, 606...  \n",
       "3     [60634, 60633, 60632, 60631, 60630, 60629, 606...  \n",
       "2     [60634, 60633, 60632, 60631, 60630, 60629, 606...  \n",
       "1     [60634, 60633, 60632, 60631, 60630, 60629, 606...  \n",
       "0     [60634, 60633, 60632, 60631, 60630, 60629, 606...  \n",
       "\n",
       "[3415 rows x 4 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Esta función resume todo lo hecho hasta el momento\n",
    "def logica2():\n",
    "    global dt\n",
    "    dt = df.drop_duplicates('PEDIDO').copy(True)\n",
    "    dt = dt[['PEDIDO', 'FE_EMIT', 'FE_ENTREGA']].copy(True)\n",
    "    dt.sort_values('FE_ENTREGA', inplace=True)\n",
    "    X = []\n",
    "    data = dt.to_numpy() \n",
    "    dt = dt.drop(dt[data[:, 1]>data[:,2]].index)\n",
    "    data = dt.to_numpy()\n",
    "    for i in range(len(dt)):\n",
    "        index = np.argmax(data[:, 2]==data[i, 2])\n",
    "        X.append(np.concatenate(([False for j in range(index)], data[index:, 1]<=data[i, 2])))\n",
    "    pedidos = [dt[np.asarray(i, dtype=bool)]['PEDIDO'].to_numpy() for i in X]\n",
    "    dt.insert(3, 'SIMUL', value = pedidos)\n",
    "    print(\"Hecho!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hecho!\n"
     ]
    }
   ],
   "source": [
    "logica2()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Postprocesamiento"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "feat_map = {\"other\":0, \"1200\":1, \"1300\":2, \"1400\":3, \"1600\":4, \"1700\":5, \"1800\":6, \"1900\":7, \"2100\":8, \"2400\":9, \n",
    "            \"2405\":9, \"2600\":10, \"2800\":11, \"2805\":11, \"AR-10\":12, \"AR-20\":12, \"AR-30\":12, \"AR-40\":12, \n",
    "            \"AR-50\":12, \"AR-70\":12, \"AR-90\":12}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Inserto una columna destinada a preservar la descripción del producto que luego será de utilidad\n",
    "dt.insert(4 ,'DES', np.zeros(len(dt)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Llenamos la columna de descripción con los datos que corresponden\n",
    "dt['DES'] = dt['PEDIDO'].apply(lambda x: [df[df['PEDIDO']==x].DES_PROD.iloc[0]])\n",
    "#dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creamos variables auxiliares a usar después\n",
    "data = dt.to_numpy()\n",
    "keys = feat_map.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#En esta parte lo que se hace es convertir todos los datos en tokens para que mi modelo luego los logre procesar sin problema\n",
    "\n",
    "for i in range(len(data)):\n",
    "    for j in range(len(data[i, 3])):\n",
    "        product_index = np.argmax(data[i, 3][j] == data[:, 0]) #Buscamos el índice del producto dentro de la lista de SIMUL según el pedido\n",
    "        product_name = data[product_index, 4][0] #Obtenemos la descripción/nombre del producto\n",
    "        #Encodeamos la secuencia\n",
    "        for k in keys:\n",
    "            if k in product_name: #Si la key está dentro de la descripción mapeamos a su correspondiente encodeo\n",
    "                data[i, 3][j] = feat_map[k]\n",
    "                break\n",
    "            else: #Si la key no está se encodea como other\n",
    "                data[i, 3][j] = feat_map['other']\n",
    "        \n",
    "\n",
    "\n",
    "for i in range(len(data)): \n",
    "    #Encodeamos la etiqueta Y (producto en cuestión)\n",
    "    for k in keys:\n",
    "        if k in data[i, 4][0]:\n",
    "            data[i, 4][0] = feat_map[k]\n",
    "            break\n",
    "        elif k==list(keys)[-1]:\n",
    "            data[i, 4][0] = feat_map['other']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PEDIDO</th>\n",
       "      <th>FE_EMIT</th>\n",
       "      <th>FE_ENTREGA</th>\n",
       "      <th>SIMUL</th>\n",
       "      <th>DES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3503</th>\n",
       "      <td>56227</td>\n",
       "      <td>737304</td>\n",
       "      <td>737304</td>\n",
       "      <td>[0]</td>\n",
       "      <td>[0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3502</th>\n",
       "      <td>56226</td>\n",
       "      <td>737305</td>\n",
       "      <td>737305</td>\n",
       "      <td>[6]</td>\n",
       "      <td>[6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3501</th>\n",
       "      <td>56231</td>\n",
       "      <td>737306</td>\n",
       "      <td>737306</td>\n",
       "      <td>[6]</td>\n",
       "      <td>[6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3499</th>\n",
       "      <td>56238</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "      <td>[11, 0]</td>\n",
       "      <td>[11]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3500</th>\n",
       "      <td>56244</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "      <td>[11, 0]</td>\n",
       "      <td>[0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60629</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60644</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>60643</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60604</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>60603</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3415 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PEDIDO  FE_EMIT  FE_ENTREGA                                     SIMUL  \\\n",
       "3503   56227   737304      737304                                       [0]   \n",
       "3502   56226   737305      737305                                       [6]   \n",
       "3501   56231   737306      737306                                       [6]   \n",
       "3499   56238   737318      737318                                   [11, 0]   \n",
       "3500   56244   737318      737318                                   [11, 0]   \n",
       "...      ...      ...         ...                                       ...   \n",
       "4      60629   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "3      60644   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "2      60643   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "1      60604   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "0      60603   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "\n",
       "       DES  \n",
       "3503   [0]  \n",
       "3502   [6]  \n",
       "3501   [6]  \n",
       "3499  [11]  \n",
       "3500   [0]  \n",
       "...    ...  \n",
       "4     [10]  \n",
       "3     [10]  \n",
       "2     [10]  \n",
       "1     [10]  \n",
       "0     [10]  \n",
       "\n",
       "[3415 rows x 5 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Reemplazamos los datos el df por los tokenizados\n",
    "dt['SIMUL'] = data[:, 3]\n",
    "dt['DES'] = data[:, 4]\n",
    "dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt.rename(columns = {'SIMUL':'X'}, inplace = True)\n",
    "dt.rename(columns = {'DES':'y'}, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Usuario\\AppData\\Local\\Temp\\ipykernel_28488\\786180116.py:1: PerformanceWarning: \n",
      "your performance may suffer as PyTables will pickle object types that it cannot\n",
      "map directly to c-types [inferred_type->mixed,key->block1_values] [items->Index(['X', 'y'], dtype='object')]\n",
      "\n",
      "  dt.to_hdf('data.h5', key='df', index=False)\n"
     ]
    }
   ],
   "source": [
    "dt.to_hdf('data.h5', key='df', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PEDIDO</th>\n",
       "      <th>FE_EMIT</th>\n",
       "      <th>FE_ENTREGA</th>\n",
       "      <th>X</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>3503</th>\n",
       "      <td>56227</td>\n",
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       "      <td>56226</td>\n",
       "      <td>737305</td>\n",
       "      <td>737305</td>\n",
       "      <td>[6]</td>\n",
       "      <td>[6]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3501</th>\n",
       "      <td>56231</td>\n",
       "      <td>737306</td>\n",
       "      <td>737306</td>\n",
       "      <td>[6]</td>\n",
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       "    <tr>\n",
       "      <th>3499</th>\n",
       "      <td>56238</td>\n",
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       "      <td>737318</td>\n",
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       "      <td>[11]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3500</th>\n",
       "      <td>56244</td>\n",
       "      <td>737318</td>\n",
       "      <td>737318</td>\n",
       "      <td>[11, 0]</td>\n",
       "      <td>[0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>60629</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60644</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>60643</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60604</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>60603</td>\n",
       "      <td>738513</td>\n",
       "      <td>738759</td>\n",
       "      <td>[10, 10, 10, 10, 10, 10, 10, 10, 10, 10]</td>\n",
       "      <td>[10]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3415 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      PEDIDO  FE_EMIT  FE_ENTREGA                                         X  \\\n",
       "3503   56227   737304      737304                                       [0]   \n",
       "3502   56226   737305      737305                                       [6]   \n",
       "3501   56231   737306      737306                                       [6]   \n",
       "3499   56238   737318      737318                                   [11, 0]   \n",
       "3500   56244   737318      737318                                   [11, 0]   \n",
       "...      ...      ...         ...                                       ...   \n",
       "4      60629   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "3      60644   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "2      60643   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "1      60604   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "0      60603   738513      738759  [10, 10, 10, 10, 10, 10, 10, 10, 10, 10]   \n",
       "\n",
       "         y  \n",
       "3503   [0]  \n",
       "3502   [6]  \n",
       "3501   [6]  \n",
       "3499  [11]  \n",
       "3500   [0]  \n",
       "...    ...  \n",
       "4     [10]  \n",
       "3     [10]  \n",
       "2     [10]  \n",
       "1     [10]  \n",
       "0     [10]  \n",
       "\n",
       "[3415 rows x 5 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_hdf('data.h5', 'df')"
   ]
  }
 ],
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