docs/source/examples/fklearn_overview_dataset_generation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This is the notebook used to generate the dataset used on the FKLearn Tutorial.ipynb\n",
    "* The FKLearn Tutorial notebook was used to introduce FKLearn on Nubank's Data Science Meetup and the idea was to give an overall idea on how and why you should use FKLearn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:23.612860Z",
     "start_time": "2019-06-25T21:59:23.101094Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:23.881350Z",
     "start_time": "2019-06-25T21:59:23.615078Z"
    }
   },
   "outputs": [],
   "source": [
    "from scipy.stats import truncnorm\n",
    "\n",
    "def get_truncated_normal(mean=0, sd=1, low=0, upp=10):\n",
    "    return truncnorm(\n",
    "        (low - mean) / sd, (upp - mean) / sd, loc=mean, scale=sd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:23.885884Z",
     "start_time": "2019-06-25T21:59:23.883347Z"
    }
   },
   "outputs": [],
   "source": [
    "ids = range(0, 10000)\n",
    "months = range(1, 24)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:24.118833Z",
     "start_time": "2019-06-25T21:59:24.105571Z"
    }
   },
   "outputs": [],
   "source": [
    "unique_entries = np.array(np.meshgrid(ids, months)).T.reshape(-1, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:24.430219Z",
     "start_time": "2019-06-25T21:59:24.425045Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(230000, 2)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_entries.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:24.721722Z",
     "start_time": "2019-06-25T21:59:24.716303Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.        , 1.07177346, 1.11612317, 1.14869835, 1.17461894,\n",
       "        1.1962312 , 1.21481404, 1.23114441, 1.24573094, 1.25892541,\n",
       "        1.27098162, 1.28208885, 1.29239222, 1.30200545, 1.31101942,\n",
       "        1.31950791, 1.32753167, 1.33514136, 1.34237965, 1.34928285,\n",
       "        1.35588211, 1.36220437, 1.36827308]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.power(np.array([months]), 0.1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:25.105626Z",
     "start_time": "2019-06-25T21:59:25.089013Z"
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "X = get_truncated_normal(5000, 2000, 300, 20000)\n",
    "income_by_id = X.rvs(len(ids))\n",
    "income_by_id = np.repeat(income_by_id, len(months))\n",
    "income_wrong_entry = np.random.binomial(1, 1 - 0.05, unique_entries.shape[0]).astype(bool)\n",
    "income_array = np.where(income_wrong_entry == True, income_by_id.reshape(1, -1), 9999999)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:25.462962Z",
     "start_time": "2019-06-25T21:59:25.458780Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 230000)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "income_array.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:26.127692Z",
     "start_time": "2019-06-25T21:59:25.869042Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([8.5100e+02, 2.4150e+03, 3.8180e+03, 5.8880e+03, 9.3610e+03,\n",
       "        1.2420e+04, 1.6031e+04, 1.9228e+04, 2.1091e+04, 2.3276e+04,\n",
       "        2.2448e+04, 2.1942e+04, 2.0263e+04, 1.4789e+04, 1.2236e+04,\n",
       "        9.2230e+03, 5.8420e+03, 3.9100e+03, 2.3230e+03, 1.2880e+03,\n",
       "        7.3600e+02, 2.7600e+02, 9.2000e+01, 1.8400e+02, 2.3000e+01,\n",
       "        2.3000e+01, 2.3000e+01, 0.0000e+00, 0.0000e+00, 0.0000e+00,\n",
       "        0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00,\n",
       "        0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00]),\n",
       " array([    0,   500,  1000,  1500,  2000,  2500,  3000,  3500,  4000,\n",
       "         4500,  5000,  5500,  6000,  6500,  7000,  7500,  8000,  8500,\n",
       "         9000,  9500, 10000, 10500, 11000, 11500, 12000, 12500, 13000,\n",
       "        13500, 14000, 14500, 15000, 15500, 16000, 16500, 17000, 17500,\n",
       "        18000, 18500, 19000, 19500]),\n",
       " <a list of 39 Patch objects>)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(income_by_id, bins = range(0, 20000, 500)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:26.308523Z",
     "start_time": "2019-06-25T21:59:26.254913Z"
    }
   },
   "outputs": [],
   "source": [
    "customer_creation_date = []\n",
    "for m_id in np.random.choice(len(months) * 31, len(ids)):\n",
    "    customer_creation_date.append(np.datetime64(\"2017-01-01\") + np.timedelta64(int(m_id), 'D'))\n",
    "customer_creation_date = np.repeat(np.array(customer_creation_date), len(months))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:26.719755Z",
     "start_time": "2019-06-25T21:59:26.703813Z"
    }
   },
   "outputs": [],
   "source": [
    "phone_branches = [\"samsung\", \"motorola\", \"iphone\", \"lg\"]\n",
    "random_phone = np.random.choice(4, len(ids), p=[0.15, 0.3, 0.25, 0.3])\n",
    "cellphone_branch = [phone_branches[i] for i in random_phone]\n",
    "cellphone_branch = np.repeat(cellphone_branch, len(months))\n",
    "phone_factor = [0.7, 0.3, 0.9, 0.45]\n",
    "cellphone_factor = [phone_factor[i] for i in random_phone]\n",
    "cellphone_factor = np.repeat(cellphone_factor, len(months))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:27.078433Z",
     "start_time": "2019-06-25T21:59:27.074227Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.45, 0.45, 0.45, ..., 0.3 , 0.3 , 0.3 ])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cellphone_factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:27.432774Z",
     "start_time": "2019-06-25T21:59:27.393815Z"
    }
   },
   "outputs": [],
   "source": [
    "bureau_missing = np.random.binomial(1, 1 - 0.1, unique_entries.shape[0]).astype(bool)\n",
    "Y = get_truncated_normal(500, 250, 0, 1000)\n",
    "bureau_score = Y.rvs(unique_entries.shape[0])\n",
    "monthly_factor = np.tile(np.power(np.array(months), 0.2), len(ids))\n",
    "bureau_score = np.where(bureau_missing == True, bureau_score, np.nan) / monthly_factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:27.765478Z",
     "start_time": "2019-06-25T21:59:27.761644Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([395.94580788, 415.29087644, 159.24609131, ..., 433.25966177,\n",
       "       297.1819245 ,          nan])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bureau_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:28.472736Z",
     "start_time": "2019-06-25T21:59:28.221968Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 2219.,  2924.,  3928.,  4948.,  6192.,  7456.,  8735., 10123.,\n",
       "        11212., 11909., 12934., 13351., 12961., 12877., 12282., 11558.,\n",
       "        10431.,  9236.,  8037.,  7139.,  5836.,  4894.,  3652.,  2821.,\n",
       "         2063.,  1654.,  1256.,  1029.,   817.,   572.,   480.,   375.,\n",
       "          275.,   240.,   206.,   132.,    78.,    86.,    69.]),\n",
       " array([  0,  25,  50,  75, 100, 125, 150, 175, 200, 225, 250, 275, 300,\n",
       "        325, 350, 375, 400, 425, 450, 475, 500, 525, 550, 575, 600, 625,\n",
       "        650, 675, 700, 725, 750, 775, 800, 825, 850, 875, 900, 925, 950,\n",
       "        975]),\n",
       " <a list of 39 Patch objects>)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(bureau_score, bins = range(0, 1000, 25)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:28.632142Z",
     "start_time": "2019-06-25T21:59:28.625782Z"
    }
   },
   "outputs": [],
   "source": [
    "willingness_to_spend = np.repeat(np.random.normal(500, 200, len(ids)), len(months))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:29.040703Z",
     "start_time": "2019-06-25T21:59:29.036549Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([933.87350032, 933.87350032, 933.87350032, ..., 238.32311792,\n",
       "       238.32311792, 238.32311792])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "willingness_to_spend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:29.570115Z",
     "start_time": "2019-06-25T21:59:29.331929Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00,\n",
       "        0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00, 0.0000e+00,\n",
       "        0.0000e+00, 0.0000e+00, 0.0000e+00, 2.3000e+01, 0.0000e+00,\n",
       "        2.3000e+01, 4.6000e+01, 2.3000e+02, 4.6000e+02, 6.2100e+02,\n",
       "        1.1730e+03, 2.4610e+03, 4.1400e+03, 6.0030e+03, 7.9580e+03,\n",
       "        1.1868e+04, 1.4789e+04, 1.9044e+04, 2.0493e+04, 2.3276e+04,\n",
       "        2.3184e+04, 2.2379e+04, 1.8860e+04, 1.5571e+04, 1.2167e+04,\n",
       "        9.5680e+03, 5.9570e+03, 4.3930e+03, 2.2540e+03, 1.4030e+03,\n",
       "        9.6600e+02, 3.9100e+02, 1.8400e+02, 2.3000e+01, 6.9000e+01,\n",
       "        0.0000e+00, 2.3000e+01, 0.0000e+00, 0.0000e+00]),\n",
       " array([-1000,  -950,  -900,  -850,  -800,  -750,  -700,  -650,  -600,\n",
       "         -550,  -500,  -450,  -400,  -350,  -300,  -250,  -200,  -150,\n",
       "         -100,   -50,     0,    50,   100,   150,   200,   250,   300,\n",
       "          350,   400,   450,   500,   550,   600,   650,   700,   750,\n",
       "          800,   850,   900,   950,  1000,  1050,  1100,  1150,  1200,\n",
       "         1250,  1300,  1350,  1400,  1450]),\n",
       " <a list of 49 Patch objects>)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAD8CAYAAACcjGjIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAEBlJREFUeJzt3X+oZOV9x/H3p1olpAmucRVR6ZqwlNhCrbnoQiDYpKyr/rEGIpg/6mKFLUGhhRa6af4wJA1sCmmpkFpMs0RLG2PTBpdk081WEkIhGq+t8Ues3RuzjZtd3LVrbEogqe23f8xz08k+c/feO/funfvj/YJhznznOec+z+yMH59zzpxJVSFJ0rCfm3QHJEmrj+EgSeoYDpKkjuEgSeoYDpKkjuEgSeoYDpKkjuEgSeoYDpKkzrmT7sC4LrrootqyZcukuyFJa8qTTz75SlVtnq/dmg2HLVu2MD09PeluSNKakuTfF9LO3UqSpI7hIEnqGA6SpI7hIEnqGA6SpI7hIEnqGA6SpI7hIEnqGA6SpM6a/Ya0pIEte740sn5k780r3BOtJ4aDtE4ZGloKdytJkjqGgySpYzhIkjqGgySpYzhIkjqGgySp46ms0gYz1ymu4Gmu+n/OHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHX/PQVojzvQ7DNJym3fmkOSKJF9N8nyS55L8TqtfmORQksPtflOrJ8m9SWaSPJ3kmqFt7WrtDyfZNVR/R5Jn2jr3JsnZGKwkaWEWslvpdeD3qurtwDbgriRXAXuAR6tqK/BoewxwI7C13XYD98EgTIB7gOuAa4F7ZgOltdk9tN6OpQ9NkjSuecOhqo5X1T+35R8CzwOXATuBB1qzB4Bb2vJO4MEaeAy4IMmlwA3Aoao6VVWvAoeAHe25N1fVN6qqgAeHtiVJmoBFHZBOsgX4NeBx4JKqOg6DAAEubs0uA14aWu1oq52pfnREXZI0IQsOhyS/APwd8LtV9Z9najqiVmPUR/Vhd5LpJNMnT56cr8uSpDEtKByS/DyDYPjrqvr7Vn657RKi3Z9o9aPAFUOrXw4cm6d++Yh6p6rur6qpqpravHnzQrouSRrDQs5WCvBp4Pmq+pOhp/YDs2cc7QIeGarf3s5a2ga81nY7HQS2J9nUDkRvBw62536YZFv7W7cPbUuSNAEL+Z7DO4HfBJ5J8lSr/SGwF3g4yZ3A94Bb23MHgJuAGeBHwB0AVXUqyUeBJ1q7j1TVqbb8AeAzwBuAL7ebJGlC5g2HqvonRh8XAHjPiPYF3DXHtvYB+0bUp4Ffma8vkqSV4eUzJEkdw0GS1DEcJEkdL7wnrTJeYE+rgTMHSVLHmYOkn5pr1nJk780r3BNNmjMHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdQwHSVLHcJAkdc6ddAckrX5b9nxpZP3I3ptXuCdaKc4cJEmdecMhyb4kJ5I8O1T7cJLvJ3mq3W4aeu6DSWaSvJDkhqH6jlabSbJnqH5lkseTHE7yuSTnLecAJUmLt5CZw2eAHSPqf1pVV7fbAYAkVwG3Ab/c1vnzJOckOQf4JHAjcBXw/tYW4ONtW1uBV4E7lzIgSdLSzRsOVfV14NQCt7cTeKiqflxV3wVmgGvbbaaqXqyqnwAPATuTBHg38Pm2/gPALYscgyRpmS3lmMPdSZ5uu502tdplwEtDbY622lz1twA/qKrXT6uPlGR3kukk0ydPnlxC1yVJZzJuONwHvA24GjgOfKLVM6JtjVEfqarur6qpqpravHnz4nosSVqwsU5lraqXZ5eTfAr4Ynt4FLhiqOnlwLG2PKr+CnBBknPb7GG4vbRuzXVqqLRajDVzSHLp0MP3ArNnMu0HbktyfpIrga3AN4EngK3tzKTzGBy03l9VBXwVeF9bfxfwyDh9kiQtn3lnDkk+C1wPXJTkKHAPcH2SqxnsAjoC/DZAVT2X5GHg28DrwF1V9T9tO3cDB4FzgH1V9Vz7E38APJTkj4B/AT69bKOTJI1l3nCoqvePKM/5H/Cq+hjwsRH1A8CBEfUXGZzNJElaJfyGtCSpYzhIkjqGgySpYzhIkjqGgySpYzhIkjqGgySpYzhIkjqGgySpYzhIkjqGgySpYzhIkjqGgySpYzhIkjqGgySpYzhIkjqGgySpYzhIkjqGgySpYzhIkjrnTroDktauLXu+NLJ+ZO/NK9wTLTdnDpKkjjMH6Sya6/+spdXOmYMkqWM4SJI6hoMkqWM4SJI6hoMkqWM4SJI6hoMkqWM4SJI6hoMkqWM4SJI6hoMkqWM4SJI684ZDkn1JTiR5dqh2YZJDSQ63+02tniT3JplJ8nSSa4bW2dXaH06ya6j+jiTPtHXuTZLlHqQkaXEWMnP4DLDjtNoe4NGq2go82h4D3AhsbbfdwH0wCBPgHuA64FrgntlAaW12D613+t+SJK2wecOhqr4OnDqtvBN4oC0/ANwyVH+wBh4DLkhyKXADcKiqTlXVq8AhYEd77s1V9Y2qKuDBoW1JkiZk3GMOl1TVcYB2f3GrXwa8NNTuaKudqX50RF2SNEHLfUB61PGCGqM+euPJ7iTTSaZPnjw5ZhclSfMZNxxebruEaPcnWv0ocMVQu8uBY/PULx9RH6mq7q+qqaqa2rx585hdlyTNZ9xw2A/MnnG0C3hkqH57O2tpG/Ba2+10ENieZFM7EL0dONie+2GSbe0spduHtiVJmpB5f0M6yWeB64GLkhxlcNbRXuDhJHcC3wNubc0PADcBM8CPgDsAqupUko8CT7R2H6mq2YPcH2BwRtQbgC+3myRpgjI4SWjtmZqaqunp6Ul3QzqjLXu+NOkurDpH9t486S5saEmerKqp+dr5DWlJUsdwkCR1DAdJUsdwkCR1DAdJUsdwkCR1DAdJUsdwkCR1DAdJUsdwkCR1DAdJUsdwkCR1DAdJUmfeS3ZLmp9XX9V648xBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHX/sR1oEf9RHG4XhIGlFzRWwR/bevMI90Zm4W0mS1DEcJEkdw0GS1DEcJEmdJYVDkiNJnknyVJLpVrswyaEkh9v9plZPknuTzCR5Osk1Q9vZ1dofTrJraUOSJC3Vcswcfr2qrq6qqfZ4D/BoVW0FHm2PAW4EtrbbbuA+GIQJcA9wHXAtcM9soEiSJuNs7FbaCTzQlh8AbhmqP1gDjwEXJLkUuAE4VFWnqupV4BCw4yz0S5K0QEsNhwK+kuTJJLtb7ZKqOg7Q7i9u9cuAl4bWPdpqc9U7SXYnmU4yffLkySV2XZI0l6V+Ce6dVXUsycXAoST/eoa2GVGrM9T7YtX9wP0AU1NTI9tIkpZuSTOHqjrW7k8AX2BwzODltruIdn+iNT8KXDG0+uXAsTPUJUkTMnY4JHljkjfNLgPbgWeB/cDsGUe7gEfa8n7g9nbW0jbgtbbb6SCwPcmmdiB6e6tJkiZkKbuVLgG+kGR2O39TVf+Q5Ang4SR3At8Dbm3tDwA3ATPAj4A7AKrqVJKPAk+0dh+pqlNL6JckaYnGDoeqehH41RH1/wDeM6JewF1zbGsfsG/cvkiSlpdXZZW0Kni11tXFy2dIkjrOHKQR/FEfbXTOHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktTxkt3asLwstzQ3Zw6SpI4zB0mrmj8fOhnOHCRJHcNBktQxHCRJHcNBktQxHCRJHcNBktTxVFZJa5KnuJ5dzhwkSR1nDlr3vEyGtHjOHCRJHWcOktaVM80UPR6xcM4cJEkdw0GS1HG3ktYNDzxLy8eZgySps2pmDkl2AH8GnAP8ZVXtnXCXtEo5Q9C4/OLcwq2KmUOSc4BPAjcCVwHvT3LVZHslSRvXapk5XAvMVNWLAEkeAnYC355orzRRzhC0UpxR9FZLOFwGvDT0+Chw3YT6ohVkAGgt2ghhslrCISNq1TVKdgO728P/SvLCmH/vIuCVMdddyxz3xuK4lygfP7vtl9lCx/2LC9nYagmHo8AVQ48vB46d3qiq7gfuX+ofSzJdVVNL3c5a47g3Fse9sSz3uFfFAWngCWBrkiuTnAfcBuyfcJ8kacNaFTOHqno9yd3AQQansu6rqucm3C1J2rBWRTgAVNUB4MAK/bkl75paoxz3xuK4N5ZlHXequuO+kqQNbrUcc5AkrSLrLhyS3JrkuST/m2TqtOc+mGQmyQtJbhiq72i1mSR7hupXJnk8yeEkn2sHy9eEJB9O8v0kT7XbTUPPLep1WMvW45iGJTmS5Jn2bzzdahcmOdTet4eSbGr1JLm3vRZPJ7lmsr1fuCT7kpxI8uxQbdHjTLKrtT+cZNckxrIYc4x7ZT7bVbWubsDbgV8CvgZMDdWvAr4FnA9cCXyHwcHvc9ryW4HzWpur2joPA7e15b8APjDp8S3idfgw8Psj6ot+HdbqbT2OacQYjwAXnVb7Y2BPW94DfLwt3wR8mcH3irYBj0+6/4sY57uAa4Bnxx0ncCHwYrvf1JY3TXpsY4x7RT7b627mUFXPV9WoL8ftBB6qqh9X1XeBGQaX7fjppTuq6ifAQ8DOJAHeDXy+rf8AcMvZH8FZt6jXYYL9XA7rcUwLsZPB+xV+9n27E3iwBh4DLkhy6SQ6uFhV9XXg1GnlxY7zBuBQVZ2qqleBQ8COs9/78c0x7rks62d73YXDGYy6RMdlZ6i/BfhBVb1+Wn0tubtNq/fNTrlZ/Ouwlq3HMZ2ugK8kebJdQQDgkqo6DtDuL2719fZ6LHac62n8Z/2zvSbDIck/Jnl2xO1MaTjXJToWW1815nkd7gPeBlwNHAc+MbvaiE2tifGOYT2O6XTvrKprGFzR+K4k7zpD243wesD6f4+vyGd71XzPYTGq6jfGWO1Ml+gYVX+FwXT03DZ7GHlJj0la6OuQ5FPAF9vDxb4Oa9mCLsuyllXVsXZ/IskXGOxCeDnJpVV1vO1OOdGar7fXY7HjPApcf1r9ayvQz2VVVS/PLp/Nz/aanDmMaT9wW5Lzk1wJbAW+yRyX7qjBEZ6vAu9r6+8CHplAv8dy2r7k9wKzZzss6nVYyT6fBetxTD+V5I1J3jS7DGxn8O+8n8H7FX72fbsfuL2dzbMNeG12t8watdhxHgS2J9nUdsVsb7U1ZcU+25M+Gn8Wju6/l0GC/hh4GTg49NyHGBy1fwG4cah+E/Bv7bkPDdXf2l7cGeBvgfMnPb5FvA5/BTwDPN3eCJeO+zqs5dt6HNPQ2N7K4MyTbwHPzY6PwfGyR4HD7f7CVg+DH9X6TntvTE2q72OM9bMMdqH8d/t83znOOIHfap/nGeCOSY9rzHGvyGfbb0hLkjobabeSJGmBDAdJUsdwkCR1DAdJUsdwkCR1DAdJUsdwkCR1DAdJUuf/AAh+5pPrRTP5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(willingness_to_spend, bins = range(-1000, 1500, 50)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T22:22:17.842954Z",
     "start_time": "2019-06-25T22:22:17.830669Z"
    }
   },
   "outputs": [],
   "source": [
    "noise_feature = np.random.normal(1000, 100, unique_entries.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T22:22:18.870780Z",
     "start_time": "2019-06-25T22:22:18.839556Z"
    }
   },
   "outputs": [],
   "source": [
    "a = (willingness_to_spend)\n",
    "a_norm = (a - a.min()) / (a.max() - a.min())\n",
    "b = (income_array)\n",
    "b_norm = (b - b.min()) / (b.max() - b.min())\n",
    "c = cellphone_factor * willingness_to_spend\n",
    "c_norm = (c - c.min()) / (c.max() - c.min())\n",
    "d = (np.where(np.isnan(bureau_score), 300.0, bureau_score))\n",
    "d_norm = (d - d.min()) / (d.max() - d.min())\n",
    "# e = np.random.normal(1, 0.3, unique_entries.shape[0])\n",
    "W = get_truncated_normal(2000, 100, 0, 50000)\n",
    "spend = (a_norm + b_norm + c_norm + d_norm) * W.rvs(unique_entries.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:30.565435Z",
     "start_time": "2019-06-25T21:59:30.561163Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[6476.47307951, 4740.97909678, 3348.94742391, ..., 2367.47238387,\n",
       "        4354.480922  , 3508.97334522]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:30.948825Z",
     "start_time": "2019-06-25T21:59:30.944950Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 230000)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spend.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T21:59:31.302057Z",
     "start_time": "2019-06-25T21:59:31.298500Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 230000)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "income_array.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T22:22:24.066535Z",
     "start_time": "2019-06-25T22:22:23.990860Z"
    }
   },
   "outputs": [],
   "source": [
    "initial_df = (pd.DataFrame(\n",
    "    unique_entries, columns=[\"id\", \"month\"]\n",
    ").assign(\n",
    "       income=income_array.T,\n",
    "       created_at=customer_creation_date.T,\n",
    "       phone_type=cellphone_branch.T,\n",
    "       bureau_score=bureau_score.T,\n",
    "       spend_desire=willingness_to_spend.T,\n",
    "       random_noise=noise_feature.T,\n",
    "       monthly_spend=spend.T,\n",
    "       month_date=lambda df: df.month * 31 + np.datetime64(\"2017-01-01\")\n",
    ")\n",
    ".loc[lambda df: df.month_date >= df.created_at])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T22:22:26.893906Z",
     "start_time": "2019-06-25T22:22:26.751159Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1a24b54940>]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(sorted(initial_df.month.unique()), initial_df.groupby(\"month\").agg({\"bureau_score\": \"mean\"}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T22:22:28.383555Z",
     "start_time": "2019-06-25T22:22:28.345723Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>month</th>\n",
       "      <th>income</th>\n",
       "      <th>created_at</th>\n",
       "      <th>phone_type</th>\n",
       "      <th>bureau_score</th>\n",
       "      <th>spend_desire</th>\n",
       "      <th>random_noise</th>\n",
       "      <th>monthly_spend</th>\n",
       "      <th>month_date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1139.988267</td>\n",
       "      <td>3044.984797</td>\n",
       "      <td>2017-12-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>259.050372</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>949.164731</td>\n",
       "      <td>2911.910942</td>\n",
       "      <td>2018-01-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>295.523138</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>829.196293</td>\n",
       "      <td>2867.779678</td>\n",
       "      <td>2018-02-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>260.729691</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1001.109359</td>\n",
       "      <td>3160.060523</td>\n",
       "      <td>2018-03-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>396.889624</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>997.938315</td>\n",
       "      <td>3420.741792</td>\n",
       "      <td>2018-04-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>78.479225</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1032.025854</td>\n",
       "      <td>2484.013650</td>\n",
       "      <td>2018-05-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>79.617325</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>969.913448</td>\n",
       "      <td>2454.602869</td>\n",
       "      <td>2018-06-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>177.472256</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>766.796672</td>\n",
       "      <td>2803.507917</td>\n",
       "      <td>2018-07-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>189.046991</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>907.258777</td>\n",
       "      <td>2580.205489</td>\n",
       "      <td>2018-08-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>296.367569</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1063.450859</td>\n",
       "      <td>3232.765577</td>\n",
       "      <td>2018-09-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>106.914660</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1095.115641</td>\n",
       "      <td>2722.341319</td>\n",
       "      <td>2018-10-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>111.076808</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>964.705725</td>\n",
       "      <td>2334.885221</td>\n",
       "      <td>2018-11-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>204.017107</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>999.699641</td>\n",
       "      <td>2862.418232</td>\n",
       "      <td>2018-12-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>3.919847e+03</td>\n",
       "      <td>2018-10-31</td>\n",
       "      <td>samsung</td>\n",
       "      <td>51.622959</td>\n",
       "      <td>661.945869</td>\n",
       "      <td>716.221137</td>\n",
       "      <td>2415.757986</td>\n",
       "      <td>2018-11-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>3.919847e+03</td>\n",
       "      <td>2018-10-31</td>\n",
       "      <td>samsung</td>\n",
       "      <td>335.759979</td>\n",
       "      <td>661.945869</td>\n",
       "      <td>817.390238</td>\n",
       "      <td>2539.717872</td>\n",
       "      <td>2018-12-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>934.655776</td>\n",
       "      <td>2215.079016</td>\n",
       "      <td>2018-03-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>140.761112</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>834.796711</td>\n",
       "      <td>1855.797279</td>\n",
       "      <td>2018-04-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>191.061416</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>999.442880</td>\n",
       "      <td>2135.130741</td>\n",
       "      <td>2018-05-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>258.865637</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1006.651873</td>\n",
       "      <td>2278.116638</td>\n",
       "      <td>2018-06-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>233.545889</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1053.284574</td>\n",
       "      <td>2277.614906</td>\n",
       "      <td>2018-07-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>74.862513</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1124.678558</td>\n",
       "      <td>1797.577610</td>\n",
       "      <td>2018-08-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>331.113763</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1082.653241</td>\n",
       "      <td>2380.970903</td>\n",
       "      <td>2018-09-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>313.764030</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>851.352016</td>\n",
       "      <td>2384.972242</td>\n",
       "      <td>2018-10-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2</td>\n",
       "      <td>22</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>946.388351</td>\n",
       "      <td>2334.708744</td>\n",
       "      <td>2018-11-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>264.382012</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1078.967846</td>\n",
       "      <td>2324.311034</td>\n",
       "      <td>2018-12-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>336.382952</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>1086.431562</td>\n",
       "      <td>1576.195080</td>\n",
       "      <td>2018-03-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>294.471077</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>977.412880</td>\n",
       "      <td>1569.622583</td>\n",
       "      <td>2018-04-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>217.297753</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>832.223156</td>\n",
       "      <td>1388.277215</td>\n",
       "      <td>2018-05-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>233.320385</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>1100.760524</td>\n",
       "      <td>1489.505004</td>\n",
       "      <td>2018-06-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>NaN</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>956.273725</td>\n",
       "      <td>1557.915921</td>\n",
       "      <td>2018-07-13</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>229966</th>\n",
       "      <td>9998</td>\n",
       "      <td>13</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>394.733451</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>865.889465</td>\n",
       "      <td>2787.969664</td>\n",
       "      <td>2018-02-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229967</th>\n",
       "      <td>9998</td>\n",
       "      <td>14</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>103.497621</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1016.677574</td>\n",
       "      <td>2439.669647</td>\n",
       "      <td>2018-03-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229968</th>\n",
       "      <td>9998</td>\n",
       "      <td>15</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>324.048521</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1008.213981</td>\n",
       "      <td>2620.098144</td>\n",
       "      <td>2018-04-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229969</th>\n",
       "      <td>9998</td>\n",
       "      <td>16</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>285.229650</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>942.462260</td>\n",
       "      <td>2596.108281</td>\n",
       "      <td>2018-05-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229970</th>\n",
       "      <td>9998</td>\n",
       "      <td>17</td>\n",
       "      <td>9.999999e+06</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>279.223919</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>936.814390</td>\n",
       "      <td>4387.542945</td>\n",
       "      <td>2018-06-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229971</th>\n",
       "      <td>9998</td>\n",
       "      <td>18</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>434.538705</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1104.925121</td>\n",
       "      <td>2856.148411</td>\n",
       "      <td>2018-07-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229972</th>\n",
       "      <td>9998</td>\n",
       "      <td>19</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>228.848144</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>991.911761</td>\n",
       "      <td>2430.254018</td>\n",
       "      <td>2018-08-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229973</th>\n",
       "      <td>9998</td>\n",
       "      <td>20</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>222.192479</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>895.700387</td>\n",
       "      <td>2713.008033</td>\n",
       "      <td>2018-09-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229974</th>\n",
       "      <td>9998</td>\n",
       "      <td>21</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>472.168078</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>999.813229</td>\n",
       "      <td>2877.605278</td>\n",
       "      <td>2018-10-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229975</th>\n",
       "      <td>9998</td>\n",
       "      <td>22</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>315.973050</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1007.066609</td>\n",
       "      <td>2742.294489</td>\n",
       "      <td>2018-11-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229976</th>\n",
       "      <td>9998</td>\n",
       "      <td>23</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>351.939005</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1024.544743</td>\n",
       "      <td>2690.467294</td>\n",
       "      <td>2018-12-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229981</th>\n",
       "      <td>9999</td>\n",
       "      <td>5</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>535.589626</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>928.305709</td>\n",
       "      <td>2131.044250</td>\n",
       "      <td>2017-06-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229982</th>\n",
       "      <td>9999</td>\n",
       "      <td>6</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>495.595018</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>956.751764</td>\n",
       "      <td>2199.817043</td>\n",
       "      <td>2017-07-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229983</th>\n",
       "      <td>9999</td>\n",
       "      <td>7</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>283.991075</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>939.329302</td>\n",
       "      <td>1663.512745</td>\n",
       "      <td>2017-08-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229984</th>\n",
       "      <td>9999</td>\n",
       "      <td>8</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>322.510656</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1192.457400</td>\n",
       "      <td>1720.711685</td>\n",
       "      <td>2017-09-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229985</th>\n",
       "      <td>9999</td>\n",
       "      <td>9</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>219.439185</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>863.324305</td>\n",
       "      <td>1427.658077</td>\n",
       "      <td>2017-10-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229986</th>\n",
       "      <td>9999</td>\n",
       "      <td>10</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>573.838047</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>992.516111</td>\n",
       "      <td>2145.163885</td>\n",
       "      <td>2017-11-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229987</th>\n",
       "      <td>9999</td>\n",
       "      <td>11</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>298.403830</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1007.786207</td>\n",
       "      <td>1652.139410</td>\n",
       "      <td>2017-12-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229988</th>\n",
       "      <td>9999</td>\n",
       "      <td>12</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>381.954312</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>997.821963</td>\n",
       "      <td>1668.924825</td>\n",
       "      <td>2018-01-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229989</th>\n",
       "      <td>9999</td>\n",
       "      <td>13</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>444.736416</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>907.488679</td>\n",
       "      <td>2013.678091</td>\n",
       "      <td>2018-02-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229990</th>\n",
       "      <td>9999</td>\n",
       "      <td>14</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>348.825753</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1017.164196</td>\n",
       "      <td>1857.592133</td>\n",
       "      <td>2018-03-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229991</th>\n",
       "      <td>9999</td>\n",
       "      <td>15</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>129.942796</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>973.744805</td>\n",
       "      <td>1198.114179</td>\n",
       "      <td>2018-04-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229992</th>\n",
       "      <td>9999</td>\n",
       "      <td>16</td>\n",
       "      <td>9.999999e+06</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>223.670064</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>998.105372</td>\n",
       "      <td>3618.688650</td>\n",
       "      <td>2018-05-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229993</th>\n",
       "      <td>9999</td>\n",
       "      <td>17</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>307.816191</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1031.266520</td>\n",
       "      <td>1651.539584</td>\n",
       "      <td>2018-06-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229994</th>\n",
       "      <td>9999</td>\n",
       "      <td>18</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>246.119892</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1023.319029</td>\n",
       "      <td>1583.706825</td>\n",
       "      <td>2018-07-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229995</th>\n",
       "      <td>9999</td>\n",
       "      <td>19</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>122.151234</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1155.941675</td>\n",
       "      <td>1360.819971</td>\n",
       "      <td>2018-08-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229996</th>\n",
       "      <td>9999</td>\n",
       "      <td>20</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>348.065944</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1004.350395</td>\n",
       "      <td>1685.613058</td>\n",
       "      <td>2018-09-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229997</th>\n",
       "      <td>9999</td>\n",
       "      <td>21</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>433.259662</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1129.281883</td>\n",
       "      <td>1870.543429</td>\n",
       "      <td>2018-10-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229998</th>\n",
       "      <td>9999</td>\n",
       "      <td>22</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>297.181925</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1130.956199</td>\n",
       "      <td>1569.323027</td>\n",
       "      <td>2018-11-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229999</th>\n",
       "      <td>9999</td>\n",
       "      <td>23</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>NaN</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1066.198167</td>\n",
       "      <td>1806.356185</td>\n",
       "      <td>2018-12-15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>119957 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id  month        income created_at phone_type  bureau_score  \\\n",
       "10         0     11  2.662664e+03 2017-11-24         lg           NaN   \n",
       "11         0     12  2.662664e+03 2017-11-24         lg    259.050372   \n",
       "12         0     13  2.662664e+03 2017-11-24         lg    295.523138   \n",
       "13         0     14  2.662664e+03 2017-11-24         lg    260.729691   \n",
       "14         0     15  2.662664e+03 2017-11-24         lg    396.889624   \n",
       "15         0     16  2.662664e+03 2017-11-24         lg     78.479225   \n",
       "16         0     17  2.662664e+03 2017-11-24         lg     79.617325   \n",
       "17         0     18  2.662664e+03 2017-11-24         lg    177.472256   \n",
       "18         0     19  2.662664e+03 2017-11-24         lg    189.046991   \n",
       "19         0     20  2.662664e+03 2017-11-24         lg    296.367569   \n",
       "20         0     21  2.662664e+03 2017-11-24         lg    106.914660   \n",
       "21         0     22  2.662664e+03 2017-11-24         lg    111.076808   \n",
       "22         0     23  2.662664e+03 2017-11-24         lg    204.017107   \n",
       "44         1     22  3.919847e+03 2018-10-31    samsung     51.622959   \n",
       "45         1     23  3.919847e+03 2018-10-31    samsung    335.759979   \n",
       "59         2     14  7.822244e+03 2018-02-19         lg           NaN   \n",
       "60         2     15  7.822244e+03 2018-02-19         lg    140.761112   \n",
       "61         2     16  7.822244e+03 2018-02-19         lg    191.061416   \n",
       "62         2     17  7.822244e+03 2018-02-19         lg    258.865637   \n",
       "63         2     18  7.822244e+03 2018-02-19         lg    233.545889   \n",
       "64         2     19  7.822244e+03 2018-02-19         lg     74.862513   \n",
       "65         2     20  7.822244e+03 2018-02-19         lg    331.113763   \n",
       "66         2     21  7.822244e+03 2018-02-19         lg    313.764030   \n",
       "67         2     22  7.822244e+03 2018-02-19         lg           NaN   \n",
       "68         2     23  7.822244e+03 2018-02-19         lg    264.382012   \n",
       "82         3     14  6.710126e+03 2018-02-26   motorola    336.382952   \n",
       "83         3     15  6.710126e+03 2018-02-26   motorola    294.471077   \n",
       "84         3     16  6.710126e+03 2018-02-26   motorola    217.297753   \n",
       "85         3     17  6.710126e+03 2018-02-26   motorola    233.320385   \n",
       "86         3     18  6.710126e+03 2018-02-26   motorola           NaN   \n",
       "...      ...    ...           ...        ...        ...           ...   \n",
       "229966  9998     13  4.302987e+03 2017-11-20         lg    394.733451   \n",
       "229967  9998     14  4.302987e+03 2017-11-20         lg    103.497621   \n",
       "229968  9998     15  4.302987e+03 2017-11-20         lg    324.048521   \n",
       "229969  9998     16  4.302987e+03 2017-11-20         lg    285.229650   \n",
       "229970  9998     17  9.999999e+06 2017-11-20         lg    279.223919   \n",
       "229971  9998     18  4.302987e+03 2017-11-20         lg    434.538705   \n",
       "229972  9998     19  4.302987e+03 2017-11-20         lg    228.848144   \n",
       "229973  9998     20  4.302987e+03 2017-11-20         lg    222.192479   \n",
       "229974  9998     21  4.302987e+03 2017-11-20         lg    472.168078   \n",
       "229975  9998     22  4.302987e+03 2017-11-20         lg    315.973050   \n",
       "229976  9998     23  4.302987e+03 2017-11-20         lg    351.939005   \n",
       "229981  9999      5  5.870300e+03 2017-05-14   motorola    535.589626   \n",
       "229982  9999      6  5.870300e+03 2017-05-14   motorola    495.595018   \n",
       "229983  9999      7  5.870300e+03 2017-05-14   motorola    283.991075   \n",
       "229984  9999      8  5.870300e+03 2017-05-14   motorola    322.510656   \n",
       "229985  9999      9  5.870300e+03 2017-05-14   motorola    219.439185   \n",
       "229986  9999     10  5.870300e+03 2017-05-14   motorola    573.838047   \n",
       "229987  9999     11  5.870300e+03 2017-05-14   motorola    298.403830   \n",
       "229988  9999     12  5.870300e+03 2017-05-14   motorola    381.954312   \n",
       "229989  9999     13  5.870300e+03 2017-05-14   motorola    444.736416   \n",
       "229990  9999     14  5.870300e+03 2017-05-14   motorola    348.825753   \n",
       "229991  9999     15  5.870300e+03 2017-05-14   motorola    129.942796   \n",
       "229992  9999     16  9.999999e+06 2017-05-14   motorola    223.670064   \n",
       "229993  9999     17  5.870300e+03 2017-05-14   motorola    307.816191   \n",
       "229994  9999     18  5.870300e+03 2017-05-14   motorola    246.119892   \n",
       "229995  9999     19  5.870300e+03 2017-05-14   motorola    122.151234   \n",
       "229996  9999     20  5.870300e+03 2017-05-14   motorola    348.065944   \n",
       "229997  9999     21  5.870300e+03 2017-05-14   motorola    433.259662   \n",
       "229998  9999     22  5.870300e+03 2017-05-14   motorola    297.181925   \n",
       "229999  9999     23  5.870300e+03 2017-05-14   motorola           NaN   \n",
       "\n",
       "        spend_desire  random_noise  monthly_spend month_date  \n",
       "10        933.873500   1139.988267    3044.984797 2017-12-08  \n",
       "11        933.873500    949.164731    2911.910942 2018-01-08  \n",
       "12        933.873500    829.196293    2867.779678 2018-02-08  \n",
       "13        933.873500   1001.109359    3160.060523 2018-03-11  \n",
       "14        933.873500    997.938315    3420.741792 2018-04-11  \n",
       "15        933.873500   1032.025854    2484.013650 2018-05-12  \n",
       "16        933.873500    969.913448    2454.602869 2018-06-12  \n",
       "17        933.873500    766.796672    2803.507917 2018-07-13  \n",
       "18        933.873500    907.258777    2580.205489 2018-08-13  \n",
       "19        933.873500   1063.450859    3232.765577 2018-09-13  \n",
       "20        933.873500   1095.115641    2722.341319 2018-10-14  \n",
       "21        933.873500    964.705725    2334.885221 2018-11-14  \n",
       "22        933.873500    999.699641    2862.418232 2018-12-15  \n",
       "44        661.945869    716.221137    2415.757986 2018-11-14  \n",
       "45        661.945869    817.390238    2539.717872 2018-12-15  \n",
       "59        538.113849    934.655776    2215.079016 2018-03-11  \n",
       "60        538.113849    834.796711    1855.797279 2018-04-11  \n",
       "61        538.113849    999.442880    2135.130741 2018-05-12  \n",
       "62        538.113849   1006.651873    2278.116638 2018-06-12  \n",
       "63        538.113849   1053.284574    2277.614906 2018-07-13  \n",
       "64        538.113849   1124.678558    1797.577610 2018-08-13  \n",
       "65        538.113849   1082.653241    2380.970903 2018-09-13  \n",
       "66        538.113849    851.352016    2384.972242 2018-10-14  \n",
       "67        538.113849    946.388351    2334.708744 2018-11-14  \n",
       "68        538.113849   1078.967846    2324.311034 2018-12-15  \n",
       "82        219.718444   1086.431562    1576.195080 2018-03-11  \n",
       "83        219.718444    977.412880    1569.622583 2018-04-11  \n",
       "84        219.718444    832.223156    1388.277215 2018-05-12  \n",
       "85        219.718444   1100.760524    1489.505004 2018-06-12  \n",
       "86        219.718444    956.273725    1557.915921 2018-07-13  \n",
       "...              ...           ...            ...        ...  \n",
       "229966    741.394048    865.889465    2787.969664 2018-02-08  \n",
       "229967    741.394048   1016.677574    2439.669647 2018-03-11  \n",
       "229968    741.394048   1008.213981    2620.098144 2018-04-11  \n",
       "229969    741.394048    942.462260    2596.108281 2018-05-12  \n",
       "229970    741.394048    936.814390    4387.542945 2018-06-12  \n",
       "229971    741.394048   1104.925121    2856.148411 2018-07-13  \n",
       "229972    741.394048    991.911761    2430.254018 2018-08-13  \n",
       "229973    741.394048    895.700387    2713.008033 2018-09-13  \n",
       "229974    741.394048    999.813229    2877.605278 2018-10-14  \n",
       "229975    741.394048   1007.066609    2742.294489 2018-11-14  \n",
       "229976    741.394048   1024.544743    2690.467294 2018-12-15  \n",
       "229981    238.323118    928.305709    2131.044250 2017-06-05  \n",
       "229982    238.323118    956.751764    2199.817043 2017-07-06  \n",
       "229983    238.323118    939.329302    1663.512745 2017-08-06  \n",
       "229984    238.323118   1192.457400    1720.711685 2017-09-06  \n",
       "229985    238.323118    863.324305    1427.658077 2017-10-07  \n",
       "229986    238.323118    992.516111    2145.163885 2017-11-07  \n",
       "229987    238.323118   1007.786207    1652.139410 2017-12-08  \n",
       "229988    238.323118    997.821963    1668.924825 2018-01-08  \n",
       "229989    238.323118    907.488679    2013.678091 2018-02-08  \n",
       "229990    238.323118   1017.164196    1857.592133 2018-03-11  \n",
       "229991    238.323118    973.744805    1198.114179 2018-04-11  \n",
       "229992    238.323118    998.105372    3618.688650 2018-05-12  \n",
       "229993    238.323118   1031.266520    1651.539584 2018-06-12  \n",
       "229994    238.323118   1023.319029    1583.706825 2018-07-13  \n",
       "229995    238.323118   1155.941675    1360.819971 2018-08-13  \n",
       "229996    238.323118   1004.350395    1685.613058 2018-09-13  \n",
       "229997    238.323118   1129.281883    1870.543429 2018-10-14  \n",
       "229998    238.323118   1130.956199    1569.323027 2018-11-14  \n",
       "229999    238.323118   1066.198167    1806.356185 2018-12-15  \n",
       "\n",
       "[119957 rows x 10 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "initial_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T22:23:05.754326Z",
     "start_time": "2019-06-25T22:22:36.871187Z"
    }
   },
   "outputs": [],
   "source": [
    "with_target_df = (initial_df.groupby(\"id\", as_index=False).apply(lambda df: df\n",
    "                                .assign(\n",
    "                                       avg_last_2_months_spend=lambda x: x.monthly_spend.rolling(2).mean(),\n",
    "                                       target=lambda x: x.avg_last_2_months_spend.shift(-2)))\n",
    "                 .reset_index(drop=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-25T22:23:05.798846Z",
     "start_time": "2019-06-25T22:23:05.756379Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>month</th>\n",
       "      <th>income</th>\n",
       "      <th>created_at</th>\n",
       "      <th>phone_type</th>\n",
       "      <th>bureau_score</th>\n",
       "      <th>spend_desire</th>\n",
       "      <th>random_noise</th>\n",
       "      <th>monthly_spend</th>\n",
       "      <th>month_date</th>\n",
       "      <th>avg_last_2_months_spend</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1139.988267</td>\n",
       "      <td>3044.984797</td>\n",
       "      <td>2017-12-08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2889.845310</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>259.050372</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>949.164731</td>\n",
       "      <td>2911.910942</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>2978.447870</td>\n",
       "      <td>3013.920100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>295.523138</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>829.196293</td>\n",
       "      <td>2867.779678</td>\n",
       "      <td>2018-02-08</td>\n",
       "      <td>2889.845310</td>\n",
       "      <td>3290.401158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>260.729691</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1001.109359</td>\n",
       "      <td>3160.060523</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>3013.920100</td>\n",
       "      <td>2952.377721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>396.889624</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>997.938315</td>\n",
       "      <td>3420.741792</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>3290.401158</td>\n",
       "      <td>2469.308259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>78.479225</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1032.025854</td>\n",
       "      <td>2484.013650</td>\n",
       "      <td>2018-05-12</td>\n",
       "      <td>2952.377721</td>\n",
       "      <td>2629.055393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>79.617325</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>969.913448</td>\n",
       "      <td>2454.602869</td>\n",
       "      <td>2018-06-12</td>\n",
       "      <td>2469.308259</td>\n",
       "      <td>2691.856703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>177.472256</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>766.796672</td>\n",
       "      <td>2803.507917</td>\n",
       "      <td>2018-07-13</td>\n",
       "      <td>2629.055393</td>\n",
       "      <td>2906.485533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>19</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>189.046991</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>907.258777</td>\n",
       "      <td>2580.205489</td>\n",
       "      <td>2018-08-13</td>\n",
       "      <td>2691.856703</td>\n",
       "      <td>2977.553448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>296.367569</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1063.450859</td>\n",
       "      <td>3232.765577</td>\n",
       "      <td>2018-09-13</td>\n",
       "      <td>2906.485533</td>\n",
       "      <td>2528.613270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>106.914660</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>1095.115641</td>\n",
       "      <td>2722.341319</td>\n",
       "      <td>2018-10-14</td>\n",
       "      <td>2977.553448</td>\n",
       "      <td>2598.651727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>111.076808</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>964.705725</td>\n",
       "      <td>2334.885221</td>\n",
       "      <td>2018-11-14</td>\n",
       "      <td>2528.613270</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>2.662664e+03</td>\n",
       "      <td>2017-11-24</td>\n",
       "      <td>lg</td>\n",
       "      <td>204.017107</td>\n",
       "      <td>933.873500</td>\n",
       "      <td>999.699641</td>\n",
       "      <td>2862.418232</td>\n",
       "      <td>2018-12-15</td>\n",
       "      <td>2598.651727</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>3.919847e+03</td>\n",
       "      <td>2018-10-31</td>\n",
       "      <td>samsung</td>\n",
       "      <td>51.622959</td>\n",
       "      <td>661.945869</td>\n",
       "      <td>716.221137</td>\n",
       "      <td>2415.757986</td>\n",
       "      <td>2018-11-14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>3.919847e+03</td>\n",
       "      <td>2018-10-31</td>\n",
       "      <td>samsung</td>\n",
       "      <td>335.759979</td>\n",
       "      <td>661.945869</td>\n",
       "      <td>817.390238</td>\n",
       "      <td>2539.717872</td>\n",
       "      <td>2018-12-15</td>\n",
       "      <td>2477.737929</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>934.655776</td>\n",
       "      <td>2215.079016</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1995.464010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>140.761112</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>834.796711</td>\n",
       "      <td>1855.797279</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>2035.438148</td>\n",
       "      <td>2206.623689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>191.061416</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>999.442880</td>\n",
       "      <td>2135.130741</td>\n",
       "      <td>2018-05-12</td>\n",
       "      <td>1995.464010</td>\n",
       "      <td>2277.865772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>258.865637</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1006.651873</td>\n",
       "      <td>2278.116638</td>\n",
       "      <td>2018-06-12</td>\n",
       "      <td>2206.623689</td>\n",
       "      <td>2037.596258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>233.545889</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1053.284574</td>\n",
       "      <td>2277.614906</td>\n",
       "      <td>2018-07-13</td>\n",
       "      <td>2277.865772</td>\n",
       "      <td>2089.274257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>74.862513</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1124.678558</td>\n",
       "      <td>1797.577610</td>\n",
       "      <td>2018-08-13</td>\n",
       "      <td>2037.596258</td>\n",
       "      <td>2382.971573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>331.113763</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1082.653241</td>\n",
       "      <td>2380.970903</td>\n",
       "      <td>2018-09-13</td>\n",
       "      <td>2089.274257</td>\n",
       "      <td>2359.840493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>313.764030</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>851.352016</td>\n",
       "      <td>2384.972242</td>\n",
       "      <td>2018-10-14</td>\n",
       "      <td>2382.971573</td>\n",
       "      <td>2329.509889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2</td>\n",
       "      <td>22</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>946.388351</td>\n",
       "      <td>2334.708744</td>\n",
       "      <td>2018-11-14</td>\n",
       "      <td>2359.840493</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "      <td>7.822244e+03</td>\n",
       "      <td>2018-02-19</td>\n",
       "      <td>lg</td>\n",
       "      <td>264.382012</td>\n",
       "      <td>538.113849</td>\n",
       "      <td>1078.967846</td>\n",
       "      <td>2324.311034</td>\n",
       "      <td>2018-12-15</td>\n",
       "      <td>2329.509889</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>336.382952</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>1086.431562</td>\n",
       "      <td>1576.195080</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1478.949899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>294.471077</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>977.412880</td>\n",
       "      <td>1569.622583</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>1572.908831</td>\n",
       "      <td>1438.891110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>217.297753</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>832.223156</td>\n",
       "      <td>1388.277215</td>\n",
       "      <td>2018-05-12</td>\n",
       "      <td>1478.949899</td>\n",
       "      <td>1523.710463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>233.320385</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>1100.760524</td>\n",
       "      <td>1489.505004</td>\n",
       "      <td>2018-06-12</td>\n",
       "      <td>1438.891110</td>\n",
       "      <td>1409.380176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "      <td>6.710126e+03</td>\n",
       "      <td>2018-02-26</td>\n",
       "      <td>motorola</td>\n",
       "      <td>NaN</td>\n",
       "      <td>219.718444</td>\n",
       "      <td>956.273725</td>\n",
       "      <td>1557.915921</td>\n",
       "      <td>2018-07-13</td>\n",
       "      <td>1523.710463</td>\n",
       "      <td>1282.434410</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>119927</th>\n",
       "      <td>9998</td>\n",
       "      <td>13</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>394.733451</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>865.889465</td>\n",
       "      <td>2787.969664</td>\n",
       "      <td>2018-02-08</td>\n",
       "      <td>2741.752199</td>\n",
       "      <td>2529.883896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119928</th>\n",
       "      <td>9998</td>\n",
       "      <td>14</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>103.497621</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1016.677574</td>\n",
       "      <td>2439.669647</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>2613.819656</td>\n",
       "      <td>2608.103212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119929</th>\n",
       "      <td>9998</td>\n",
       "      <td>15</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>324.048521</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1008.213981</td>\n",
       "      <td>2620.098144</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>2529.883896</td>\n",
       "      <td>3491.825613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119930</th>\n",
       "      <td>9998</td>\n",
       "      <td>16</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>285.229650</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>942.462260</td>\n",
       "      <td>2596.108281</td>\n",
       "      <td>2018-05-12</td>\n",
       "      <td>2608.103212</td>\n",
       "      <td>3621.845678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119931</th>\n",
       "      <td>9998</td>\n",
       "      <td>17</td>\n",
       "      <td>9.999999e+06</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>279.223919</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>936.814390</td>\n",
       "      <td>4387.542945</td>\n",
       "      <td>2018-06-12</td>\n",
       "      <td>3491.825613</td>\n",
       "      <td>2643.201214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119932</th>\n",
       "      <td>9998</td>\n",
       "      <td>18</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>434.538705</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1104.925121</td>\n",
       "      <td>2856.148411</td>\n",
       "      <td>2018-07-13</td>\n",
       "      <td>3621.845678</td>\n",
       "      <td>2571.631026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119933</th>\n",
       "      <td>9998</td>\n",
       "      <td>19</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>228.848144</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>991.911761</td>\n",
       "      <td>2430.254018</td>\n",
       "      <td>2018-08-13</td>\n",
       "      <td>2643.201214</td>\n",
       "      <td>2795.306656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119934</th>\n",
       "      <td>9998</td>\n",
       "      <td>20</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>222.192479</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>895.700387</td>\n",
       "      <td>2713.008033</td>\n",
       "      <td>2018-09-13</td>\n",
       "      <td>2571.631026</td>\n",
       "      <td>2809.949884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119935</th>\n",
       "      <td>9998</td>\n",
       "      <td>21</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>472.168078</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>999.813229</td>\n",
       "      <td>2877.605278</td>\n",
       "      <td>2018-10-14</td>\n",
       "      <td>2795.306656</td>\n",
       "      <td>2716.380892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119936</th>\n",
       "      <td>9998</td>\n",
       "      <td>22</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>315.973050</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1007.066609</td>\n",
       "      <td>2742.294489</td>\n",
       "      <td>2018-11-14</td>\n",
       "      <td>2809.949884</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119937</th>\n",
       "      <td>9998</td>\n",
       "      <td>23</td>\n",
       "      <td>4.302987e+03</td>\n",
       "      <td>2017-11-20</td>\n",
       "      <td>lg</td>\n",
       "      <td>351.939005</td>\n",
       "      <td>741.394048</td>\n",
       "      <td>1024.544743</td>\n",
       "      <td>2690.467294</td>\n",
       "      <td>2018-12-15</td>\n",
       "      <td>2716.380892</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119938</th>\n",
       "      <td>9999</td>\n",
       "      <td>5</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>535.589626</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>928.305709</td>\n",
       "      <td>2131.044250</td>\n",
       "      <td>2017-06-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1931.664894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119939</th>\n",
       "      <td>9999</td>\n",
       "      <td>6</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>495.595018</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>956.751764</td>\n",
       "      <td>2199.817043</td>\n",
       "      <td>2017-07-06</td>\n",
       "      <td>2165.430646</td>\n",
       "      <td>1692.112215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119940</th>\n",
       "      <td>9999</td>\n",
       "      <td>7</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>283.991075</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>939.329302</td>\n",
       "      <td>1663.512745</td>\n",
       "      <td>2017-08-06</td>\n",
       "      <td>1931.664894</td>\n",
       "      <td>1574.184881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119941</th>\n",
       "      <td>9999</td>\n",
       "      <td>8</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>322.510656</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1192.457400</td>\n",
       "      <td>1720.711685</td>\n",
       "      <td>2017-09-06</td>\n",
       "      <td>1692.112215</td>\n",
       "      <td>1786.410981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119942</th>\n",
       "      <td>9999</td>\n",
       "      <td>9</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>219.439185</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>863.324305</td>\n",
       "      <td>1427.658077</td>\n",
       "      <td>2017-10-07</td>\n",
       "      <td>1574.184881</td>\n",
       "      <td>1898.651647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119943</th>\n",
       "      <td>9999</td>\n",
       "      <td>10</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>573.838047</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>992.516111</td>\n",
       "      <td>2145.163885</td>\n",
       "      <td>2017-11-07</td>\n",
       "      <td>1786.410981</td>\n",
       "      <td>1660.532118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119944</th>\n",
       "      <td>9999</td>\n",
       "      <td>11</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>298.403830</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1007.786207</td>\n",
       "      <td>1652.139410</td>\n",
       "      <td>2017-12-08</td>\n",
       "      <td>1898.651647</td>\n",
       "      <td>1841.301458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119945</th>\n",
       "      <td>9999</td>\n",
       "      <td>12</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>381.954312</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>997.821963</td>\n",
       "      <td>1668.924825</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>1660.532118</td>\n",
       "      <td>1935.635112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119946</th>\n",
       "      <td>9999</td>\n",
       "      <td>13</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>444.736416</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>907.488679</td>\n",
       "      <td>2013.678091</td>\n",
       "      <td>2018-02-08</td>\n",
       "      <td>1841.301458</td>\n",
       "      <td>1527.853156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119947</th>\n",
       "      <td>9999</td>\n",
       "      <td>14</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>348.825753</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1017.164196</td>\n",
       "      <td>1857.592133</td>\n",
       "      <td>2018-03-11</td>\n",
       "      <td>1935.635112</td>\n",
       "      <td>2408.401414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119948</th>\n",
       "      <td>9999</td>\n",
       "      <td>15</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>129.942796</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>973.744805</td>\n",
       "      <td>1198.114179</td>\n",
       "      <td>2018-04-11</td>\n",
       "      <td>1527.853156</td>\n",
       "      <td>2635.114117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119949</th>\n",
       "      <td>9999</td>\n",
       "      <td>16</td>\n",
       "      <td>9.999999e+06</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>223.670064</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>998.105372</td>\n",
       "      <td>3618.688650</td>\n",
       "      <td>2018-05-12</td>\n",
       "      <td>2408.401414</td>\n",
       "      <td>1617.623205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119950</th>\n",
       "      <td>9999</td>\n",
       "      <td>17</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>307.816191</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1031.266520</td>\n",
       "      <td>1651.539584</td>\n",
       "      <td>2018-06-12</td>\n",
       "      <td>2635.114117</td>\n",
       "      <td>1472.263398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119951</th>\n",
       "      <td>9999</td>\n",
       "      <td>18</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>246.119892</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1023.319029</td>\n",
       "      <td>1583.706825</td>\n",
       "      <td>2018-07-13</td>\n",
       "      <td>1617.623205</td>\n",
       "      <td>1523.216514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119952</th>\n",
       "      <td>9999</td>\n",
       "      <td>19</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>122.151234</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1155.941675</td>\n",
       "      <td>1360.819971</td>\n",
       "      <td>2018-08-13</td>\n",
       "      <td>1472.263398</td>\n",
       "      <td>1778.078244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119953</th>\n",
       "      <td>9999</td>\n",
       "      <td>20</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>348.065944</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1004.350395</td>\n",
       "      <td>1685.613058</td>\n",
       "      <td>2018-09-13</td>\n",
       "      <td>1523.216514</td>\n",
       "      <td>1719.933228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119954</th>\n",
       "      <td>9999</td>\n",
       "      <td>21</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>433.259662</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1129.281883</td>\n",
       "      <td>1870.543429</td>\n",
       "      <td>2018-10-14</td>\n",
       "      <td>1778.078244</td>\n",
       "      <td>1687.839606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119955</th>\n",
       "      <td>9999</td>\n",
       "      <td>22</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>297.181925</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1130.956199</td>\n",
       "      <td>1569.323027</td>\n",
       "      <td>2018-11-14</td>\n",
       "      <td>1719.933228</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119956</th>\n",
       "      <td>9999</td>\n",
       "      <td>23</td>\n",
       "      <td>5.870300e+03</td>\n",
       "      <td>2017-05-14</td>\n",
       "      <td>motorola</td>\n",
       "      <td>NaN</td>\n",
       "      <td>238.323118</td>\n",
       "      <td>1066.198167</td>\n",
       "      <td>1806.356185</td>\n",
       "      <td>2018-12-15</td>\n",
       "      <td>1687.839606</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>119957 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id  month        income created_at phone_type  bureau_score  \\\n",
       "0          0     11  2.662664e+03 2017-11-24         lg           NaN   \n",
       "1          0     12  2.662664e+03 2017-11-24         lg    259.050372   \n",
       "2          0     13  2.662664e+03 2017-11-24         lg    295.523138   \n",
       "3          0     14  2.662664e+03 2017-11-24         lg    260.729691   \n",
       "4          0     15  2.662664e+03 2017-11-24         lg    396.889624   \n",
       "5          0     16  2.662664e+03 2017-11-24         lg     78.479225   \n",
       "6          0     17  2.662664e+03 2017-11-24         lg     79.617325   \n",
       "7          0     18  2.662664e+03 2017-11-24         lg    177.472256   \n",
       "8          0     19  2.662664e+03 2017-11-24         lg    189.046991   \n",
       "9          0     20  2.662664e+03 2017-11-24         lg    296.367569   \n",
       "10         0     21  2.662664e+03 2017-11-24         lg    106.914660   \n",
       "11         0     22  2.662664e+03 2017-11-24         lg    111.076808   \n",
       "12         0     23  2.662664e+03 2017-11-24         lg    204.017107   \n",
       "13         1     22  3.919847e+03 2018-10-31    samsung     51.622959   \n",
       "14         1     23  3.919847e+03 2018-10-31    samsung    335.759979   \n",
       "15         2     14  7.822244e+03 2018-02-19         lg           NaN   \n",
       "16         2     15  7.822244e+03 2018-02-19         lg    140.761112   \n",
       "17         2     16  7.822244e+03 2018-02-19         lg    191.061416   \n",
       "18         2     17  7.822244e+03 2018-02-19         lg    258.865637   \n",
       "19         2     18  7.822244e+03 2018-02-19         lg    233.545889   \n",
       "20         2     19  7.822244e+03 2018-02-19         lg     74.862513   \n",
       "21         2     20  7.822244e+03 2018-02-19         lg    331.113763   \n",
       "22         2     21  7.822244e+03 2018-02-19         lg    313.764030   \n",
       "23         2     22  7.822244e+03 2018-02-19         lg           NaN   \n",
       "24         2     23  7.822244e+03 2018-02-19         lg    264.382012   \n",
       "25         3     14  6.710126e+03 2018-02-26   motorola    336.382952   \n",
       "26         3     15  6.710126e+03 2018-02-26   motorola    294.471077   \n",
       "27         3     16  6.710126e+03 2018-02-26   motorola    217.297753   \n",
       "28         3     17  6.710126e+03 2018-02-26   motorola    233.320385   \n",
       "29         3     18  6.710126e+03 2018-02-26   motorola           NaN   \n",
       "...      ...    ...           ...        ...        ...           ...   \n",
       "119927  9998     13  4.302987e+03 2017-11-20         lg    394.733451   \n",
       "119928  9998     14  4.302987e+03 2017-11-20         lg    103.497621   \n",
       "119929  9998     15  4.302987e+03 2017-11-20         lg    324.048521   \n",
       "119930  9998     16  4.302987e+03 2017-11-20         lg    285.229650   \n",
       "119931  9998     17  9.999999e+06 2017-11-20         lg    279.223919   \n",
       "119932  9998     18  4.302987e+03 2017-11-20         lg    434.538705   \n",
       "119933  9998     19  4.302987e+03 2017-11-20         lg    228.848144   \n",
       "119934  9998     20  4.302987e+03 2017-11-20         lg    222.192479   \n",
       "119935  9998     21  4.302987e+03 2017-11-20         lg    472.168078   \n",
       "119936  9998     22  4.302987e+03 2017-11-20         lg    315.973050   \n",
       "119937  9998     23  4.302987e+03 2017-11-20         lg    351.939005   \n",
       "119938  9999      5  5.870300e+03 2017-05-14   motorola    535.589626   \n",
       "119939  9999      6  5.870300e+03 2017-05-14   motorola    495.595018   \n",
       "119940  9999      7  5.870300e+03 2017-05-14   motorola    283.991075   \n",
       "119941  9999      8  5.870300e+03 2017-05-14   motorola    322.510656   \n",
       "119942  9999      9  5.870300e+03 2017-05-14   motorola    219.439185   \n",
       "119943  9999     10  5.870300e+03 2017-05-14   motorola    573.838047   \n",
       "119944  9999     11  5.870300e+03 2017-05-14   motorola    298.403830   \n",
       "119945  9999     12  5.870300e+03 2017-05-14   motorola    381.954312   \n",
       "119946  9999     13  5.870300e+03 2017-05-14   motorola    444.736416   \n",
       "119947  9999     14  5.870300e+03 2017-05-14   motorola    348.825753   \n",
       "119948  9999     15  5.870300e+03 2017-05-14   motorola    129.942796   \n",
       "119949  9999     16  9.999999e+06 2017-05-14   motorola    223.670064   \n",
       "119950  9999     17  5.870300e+03 2017-05-14   motorola    307.816191   \n",
       "119951  9999     18  5.870300e+03 2017-05-14   motorola    246.119892   \n",
       "119952  9999     19  5.870300e+03 2017-05-14   motorola    122.151234   \n",
       "119953  9999     20  5.870300e+03 2017-05-14   motorola    348.065944   \n",
       "119954  9999     21  5.870300e+03 2017-05-14   motorola    433.259662   \n",
       "119955  9999     22  5.870300e+03 2017-05-14   motorola    297.181925   \n",
       "119956  9999     23  5.870300e+03 2017-05-14   motorola           NaN   \n",
       "\n",
       "        spend_desire  random_noise  monthly_spend month_date  \\\n",
       "0         933.873500   1139.988267    3044.984797 2017-12-08   \n",
       "1         933.873500    949.164731    2911.910942 2018-01-08   \n",
       "2         933.873500    829.196293    2867.779678 2018-02-08   \n",
       "3         933.873500   1001.109359    3160.060523 2018-03-11   \n",
       "4         933.873500    997.938315    3420.741792 2018-04-11   \n",
       "5         933.873500   1032.025854    2484.013650 2018-05-12   \n",
       "6         933.873500    969.913448    2454.602869 2018-06-12   \n",
       "7         933.873500    766.796672    2803.507917 2018-07-13   \n",
       "8         933.873500    907.258777    2580.205489 2018-08-13   \n",
       "9         933.873500   1063.450859    3232.765577 2018-09-13   \n",
       "10        933.873500   1095.115641    2722.341319 2018-10-14   \n",
       "11        933.873500    964.705725    2334.885221 2018-11-14   \n",
       "12        933.873500    999.699641    2862.418232 2018-12-15   \n",
       "13        661.945869    716.221137    2415.757986 2018-11-14   \n",
       "14        661.945869    817.390238    2539.717872 2018-12-15   \n",
       "15        538.113849    934.655776    2215.079016 2018-03-11   \n",
       "16        538.113849    834.796711    1855.797279 2018-04-11   \n",
       "17        538.113849    999.442880    2135.130741 2018-05-12   \n",
       "18        538.113849   1006.651873    2278.116638 2018-06-12   \n",
       "19        538.113849   1053.284574    2277.614906 2018-07-13   \n",
       "20        538.113849   1124.678558    1797.577610 2018-08-13   \n",
       "21        538.113849   1082.653241    2380.970903 2018-09-13   \n",
       "22        538.113849    851.352016    2384.972242 2018-10-14   \n",
       "23        538.113849    946.388351    2334.708744 2018-11-14   \n",
       "24        538.113849   1078.967846    2324.311034 2018-12-15   \n",
       "25        219.718444   1086.431562    1576.195080 2018-03-11   \n",
       "26        219.718444    977.412880    1569.622583 2018-04-11   \n",
       "27        219.718444    832.223156    1388.277215 2018-05-12   \n",
       "28        219.718444   1100.760524    1489.505004 2018-06-12   \n",
       "29        219.718444    956.273725    1557.915921 2018-07-13   \n",
       "...              ...           ...            ...        ...   \n",
       "119927    741.394048    865.889465    2787.969664 2018-02-08   \n",
       "119928    741.394048   1016.677574    2439.669647 2018-03-11   \n",
       "119929    741.394048   1008.213981    2620.098144 2018-04-11   \n",
       "119930    741.394048    942.462260    2596.108281 2018-05-12   \n",
       "119931    741.394048    936.814390    4387.542945 2018-06-12   \n",
       "119932    741.394048   1104.925121    2856.148411 2018-07-13   \n",
       "119933    741.394048    991.911761    2430.254018 2018-08-13   \n",
       "119934    741.394048    895.700387    2713.008033 2018-09-13   \n",
       "119935    741.394048    999.813229    2877.605278 2018-10-14   \n",
       "119936    741.394048   1007.066609    2742.294489 2018-11-14   \n",
       "119937    741.394048   1024.544743    2690.467294 2018-12-15   \n",
       "119938    238.323118    928.305709    2131.044250 2017-06-05   \n",
       "119939    238.323118    956.751764    2199.817043 2017-07-06   \n",
       "119940    238.323118    939.329302    1663.512745 2017-08-06   \n",
       "119941    238.323118   1192.457400    1720.711685 2017-09-06   \n",
       "119942    238.323118    863.324305    1427.658077 2017-10-07   \n",
       "119943    238.323118    992.516111    2145.163885 2017-11-07   \n",
       "119944    238.323118   1007.786207    1652.139410 2017-12-08   \n",
       "119945    238.323118    997.821963    1668.924825 2018-01-08   \n",
       "119946    238.323118    907.488679    2013.678091 2018-02-08   \n",
       "119947    238.323118   1017.164196    1857.592133 2018-03-11   \n",
       "119948    238.323118    973.744805    1198.114179 2018-04-11   \n",
       "119949    238.323118    998.105372    3618.688650 2018-05-12   \n",
       "119950    238.323118   1031.266520    1651.539584 2018-06-12   \n",
       "119951    238.323118   1023.319029    1583.706825 2018-07-13   \n",
       "119952    238.323118   1155.941675    1360.819971 2018-08-13   \n",
       "119953    238.323118   1004.350395    1685.613058 2018-09-13   \n",
       "119954    238.323118   1129.281883    1870.543429 2018-10-14   \n",
       "119955    238.323118   1130.956199    1569.323027 2018-11-14   \n",
       "119956    238.323118   1066.198167    1806.356185 2018-12-15   \n",
       "\n",
       "        avg_last_2_months_spend       target  \n",
       "0                           NaN  2889.845310  \n",
       "1                   2978.447870  3013.920100  \n",
       "2                   2889.845310  3290.401158  \n",
       "3                   3013.920100  2952.377721  \n",
       "4                   3290.401158  2469.308259  \n",
       "5                   2952.377721  2629.055393  \n",
       "6                   2469.308259  2691.856703  \n",
       "7                   2629.055393  2906.485533  \n",
       "8                   2691.856703  2977.553448  \n",
       "9                   2906.485533  2528.613270  \n",
       "10                  2977.553448  2598.651727  \n",
       "11                  2528.613270          NaN  \n",
       "12                  2598.651727          NaN  \n",
       "13                          NaN          NaN  \n",
       "14                  2477.737929          NaN  \n",
       "15                          NaN  1995.464010  \n",
       "16                  2035.438148  2206.623689  \n",
       "17                  1995.464010  2277.865772  \n",
       "18                  2206.623689  2037.596258  \n",
       "19                  2277.865772  2089.274257  \n",
       "20                  2037.596258  2382.971573  \n",
       "21                  2089.274257  2359.840493  \n",
       "22                  2382.971573  2329.509889  \n",
       "23                  2359.840493          NaN  \n",
       "24                  2329.509889          NaN  \n",
       "25                          NaN  1478.949899  \n",
       "26                  1572.908831  1438.891110  \n",
       "27                  1478.949899  1523.710463  \n",
       "28                  1438.891110  1409.380176  \n",
       "29                  1523.710463  1282.434410  \n",
       "...                         ...          ...  \n",
       "119927              2741.752199  2529.883896  \n",
       "119928              2613.819656  2608.103212  \n",
       "119929              2529.883896  3491.825613  \n",
       "119930              2608.103212  3621.845678  \n",
       "119931              3491.825613  2643.201214  \n",
       "119932              3621.845678  2571.631026  \n",
       "119933              2643.201214  2795.306656  \n",
       "119934              2571.631026  2809.949884  \n",
       "119935              2795.306656  2716.380892  \n",
       "119936              2809.949884          NaN  \n",
       "119937              2716.380892          NaN  \n",
       "119938                      NaN  1931.664894  \n",
       "119939              2165.430646  1692.112215  \n",
       "119940              1931.664894  1574.184881  \n",
       "119941              1692.112215  1786.410981  \n",
       "119942              1574.184881  1898.651647  \n",
       "119943              1786.410981  1660.532118  \n",
       "119944              1898.651647  1841.301458  \n",
       "119945              1660.532118  1935.635112  \n",
       "119946              1841.301458  1527.853156  \n",
       "119947              1935.635112  2408.401414  \n",
       "119948              1527.853156  2635.114117  \n",
       "119949              2408.401414  1617.623205  \n",
       "119950              2635.114117  1472.263398  \n",
       "119951              1617.623205  1523.216514  \n",
       "119952              1472.263398  1778.078244  \n",
       "119953              1523.216514  1719.933228  \n",
       "119954              1778.078244  1687.839606  \n",
       "119955              1719.933228          NaN  \n",
       "119956              1687.839606          NaN  \n",
       "\n",
       "[119957 rows x 12 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with_target_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-09-26T20:17:59.924306Z",
     "start_time": "2019-09-26T20:17:56.600177Z"
    }
   },
   "outputs": [],
   "source": [
    "with_target_df.to_csv(\"fklearn-tutorial-input-dataset.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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