resilientData_generation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "order_id=list(range(5000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "#supplier_id=[1,2,3,4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "OrderQuantity=[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(5000):\n",
    "    OrderQuantity.append(random.randint(100,1001))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "ExpectedDays=[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(5000):\n",
    "    if(100<=OrderQuantity[i]<=500):\n",
    "        ExpectedDays.append(random.randint(3,5))\n",
    "    else:\n",
    "        ExpectedDays.append(random.randint(6,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "ActualDays=[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(5000):\n",
    "    ActualDays.append(ExpectedDays[i]+random.choice([0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,3,4,5]))"
   ]
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  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "Status=[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i  in range(5000):\n",
    "    if(ExpectedDays[i]==ActualDays[i]):\n",
    "        Status.append(1)\n",
    "    else:\n",
    "        Status.append(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.DataFrame(\n",
    "    {'OrderId':order_id,\n",
    "     'OrderQuantity': OrderQuantity,\n",
    "     'ExpectedDays': ExpectedDays,\n",
    "     'ActualDays':ActualDays,\n",
    "     'Status':Status\n",
    "    })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "t=data.to_csv(\"data_new_4.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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