{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import logging\n",
    "import mlflow\n",
    "import pandas as pd\n",
    "import time\n",
    "# Those should be i nsome other module, but :shrug:\n",
    "from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.utils import shuffle\n",
    "from sklearn.decomposition import PCA\n",
    "logging.getLogger().setLevel(logging.INFO)\n",
    "%run ./scikit_knn.ipynb\n",
    "%run ./scikit_dbscan.ipynb\n",
    "%run ./scikit_medoids_7.ipynb\n",
    "%run ./utils.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "preparing dataset ...\n",
      "getting list of unique fans ....\n",
      "getting max tickets for fan ....\n",
      "getting max transaction value for fan ....\n",
      "standardizing gender ....\n",
      "dummy coding gender ....\n",
      "getting fan location distance to event venue ....\n",
      "fan_id                       object\n",
      "time_in_seconds_to_venue    float64\n",
      "dtype: object\n",
      "fan_id                              object\n",
      "gender                              object\n",
      "age                                float64\n",
      "male                                 int64\n",
      "female                               int64\n",
      "max_tickets_per_event              float64\n",
      "max_transcaction_value             float64\n",
      "rfm_segment                         object\n",
      "rfm_recency                          int64\n",
      "rfm_frequency                        int64\n",
      "rfm_monetary                         int64\n",
      "recency_value               datetime64[ns]\n",
      "frequency_value                    float64\n",
      "monetary_value                     float64\n",
      "date_diff                          float64\n",
      "time_in_seconds_to_venue           float64\n",
      "dtype: object\n",
      "(15474, 16)\n"
     ]
    }
   ],
   "source": [
    "schema = 'a441ffb172866cb4928c84a73de403ca15da4a54cc535e704413ab621' # unique customer schema id\n",
    "df1 = prepare_rfm_dataset(schema, 'fan_purchase')\n",
    "# print(df1.shape)\n",
    "df2 = prepare_fan_purchase(schema)\n",
    "# print(df2.shape)\n",
    "df3 = prepare_fan_demographics(schema)\n",
    "# print(df3.shape)\n",
    "df4 = prepare_fan_event_distance(schema)\n",
    "# print(df4.shape)\n",
    "df = pd.merge(df3, df2, how='inner', on=['fan_id'])\n",
    "df = pd.merge(df, df1, how='inner', on=['fan_id'])\n",
    "df = pd.merge(df, df4, how='left', on=['fan_id'])\n",
    "print(df.dtypes)\n",
    "print(df.shape)\n",
    "cols = df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                              fan_id  gender  age  male  \\\n",
      "0  01daeb57fd8dd128049c397ba2e527439b46130753f9d3...  female  NaN     0   \n",
      "1  000b06a1be22ef0a8ff82f504ef3f81ff3522224234821...    male  NaN     1   \n",
      "\n",
      "   female  max_tickets_per_event  max_transcaction_value      rfm_segment  \\\n",
      "0       1                    1.0                     0.0  Loyal Customers   \n",
      "1       0                    1.0                    97.0  Can't Lose Them   \n",
      "\n",
      "   rfm_recency  rfm_frequency  rfm_monetary recency_value  frequency_value  \\\n",
      "0            3              4             4    2019-11-16              1.0   \n",
      "1            1              5             3    2018-02-20              6.0   \n",
      "\n",
      "   monetary_value   date_diff  time_in_seconds_to_venue  \n",
      "0             NaN  211.697114                       NaN  \n",
      "1          333.54  845.697114                       NaN  \n"
     ]
    }
   ],
   "source": [
    "print(df.head(2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "254.68399999999977"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# find limit for extreme values\n",
    "ax =sns.boxplot(y=\"monetary_value\", data=df, showfliers = True)\n",
    "df[\"monetary_value\"].quantile(0.99)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(15474, 16)\n"
     ]
    }
   ],
   "source": [
    "# apply rules to remove extreme values\n",
    "df = df.fillna(-1000)\n",
    "# df=df[df[\"time_in_seconds_to_venue\"] < 14510]\n",
    "# df=df[df[\"date_diff\"] < 1701]\n",
    "# df=df[df[\"monetary_value\"] < 254]\n",
    "print(df.shape)\n",
    "df.to_csv('clusters_input.csv', sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\" Configure options for various model runs \"\"\"\n",
    "modelling_config = {\n",
    "        'plot_2d': True,\n",
    "        'plot_3d': True,\n",
    "        'importance': True,  # Calcualte feature importance (rf targeting cluster values)\n",
    "        'boxplot': False,  # Draw boxplot\n",
    "        'save_model': False,  # Whether to store model object.\n",
    "        'modelling_type': 'ML with hardcoded 7 clusters',  # Just a name description\n",
    "        'pca_components': 3, # 'se this if you want to use PCATODO! add PCA 4 and an extra dimension as \"size\" in plots\n",
    "        'clusters_to_rds': True\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Low-cardinality categorical/oject features are also useful for hues. Drop _id fields. Drop recency_value as this is date and should be calculated to datediff\n",
    "feature_vector = df[df.columns.drop(list(df.filter(regex='_id|recency_value')))]\n",
    "# Draw pairplot. This can take 20+sec\n",
    "#sns.pairplot(feature_vector,\n",
    "#             plot_kws={'alpha': 0.6, 's': 80, 'edgecolor': 'k'},\n",
    "#             #dropna = True,\n",
    "#             diag_kind='kde',\n",
    "#             hue='rfm_segment'\n",
    "#             )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:ML with hardcoded 7 clusters with PCA 3 components\n",
      "INFO:root:Using existing experiment a441ffb172866cb4928c84a73de403ca15da4a54cc535e704413ab621\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Executing model run with feature vector column names Index(['age', 'male', 'female', 'max_tickets_per_event',\n",
      "       'max_transcaction_value', 'rfm_recency', 'rfm_frequency',\n",
      "       'rfm_monetary', 'frequency_value', 'monetary_value', 'date_diff',\n",
      "       'time_in_seconds_to_venue'],\n",
      "      dtype='object')\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:Running algorithm KMedoids (PAM) PCA 3 ...\n",
      "/home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages/sklearn/metrics/pairwise.py:1458: FutureWarning: from version 0.25, pairwise_distances for metric='mahalanobis' will require VI to be specified if Y is passed.\n",
      "  \"specified if Y is passed.\", FutureWarning)\n",
      "INFO:root:Drawing 2d plot\n",
      "INFO:root:Drawing 3d plot\n",
      "INFO:root:Model run took 0.7 minutes\n",
      "INFO:root:Logging model run parameters and artifacts ... \n",
      "INFO:root:Running random forest to calculate feature importance ...\n",
      "INFO:root:Drawing feature importance...\n"
     ]
    },
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: 'empty_eblow_plot'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-21-320a7f318a6a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;31m# Initiate training\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m \u001b[0mtrain_clusters\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mschema\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeature_vector\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtolist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'rfm_modelling'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodelling_config\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-18-e0af58897a2e>\u001b[0m in \u001b[0;36mtrain_clusters\u001b[0;34m(client_id, df, cols, collection_id, modelling_config)\u001b[0m\n\u001b[1;32m    103\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    104\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mlocation\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mgraph_locations\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 105\u001b[0;31m                 \u001b[0mmlflow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog_artifact\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlocation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    106\u001b[0m                 \u001b[0;31m# delete file from local container, we don't need to retain it\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    107\u001b[0m                 \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlocation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/mlflow/tracking/fluent.py\u001b[0m in \u001b[0;36mlog_artifact\u001b[0;34m(local_path, artifact_path)\u001b[0m\n\u001b[1;32m    309\u001b[0m     \"\"\"\n\u001b[1;32m    310\u001b[0m     \u001b[0mrun_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_or_start_run\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_id\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 311\u001b[0;31m     \u001b[0mMlflowClient\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog_artifact\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlocal_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0martifact_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    313\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/mlflow/tracking/client.py\u001b[0m in \u001b[0;36mlog_artifact\u001b[0;34m(self, run_id, local_path, artifact_path)\u001b[0m\n\u001b[1;32m    256\u001b[0m         \u001b[0;34m:\u001b[0m\u001b[0mparam\u001b[0m \u001b[0martifact_path\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mIf\u001b[0m \u001b[0mprovided\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mdirectory\u001b[0m \u001b[0;32min\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0martifact_uri\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;31m`\u001b[0m \u001b[0mto\u001b[0m \u001b[0mwrite\u001b[0m \u001b[0mto\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    257\u001b[0m         \"\"\"\n\u001b[0;32m--> 258\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_tracking_client\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog_artifact\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlocal_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0martifact_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    259\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    260\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mlog_artifacts\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrun_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlocal_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0martifact_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/mlflow/tracking/_tracking_service/client.py\u001b[0m in \u001b[0;36mlog_artifact\u001b[0;34m(self, run_id, local_path, artifact_path)\u001b[0m\n\u001b[1;32m    255\u001b[0m             \u001b[0martifact_repo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog_artifacts\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlocal_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpath_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    256\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 257\u001b[0;31m             \u001b[0martifact_repo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog_artifact\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlocal_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0martifact_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    258\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    259\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mlog_artifacts\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrun_id\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlocal_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0martifact_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/mlflow/store/artifact/s3_artifact_repo.py\u001b[0m in \u001b[0;36mlog_artifact\u001b[0;34m(self, local_file, artifact_path)\u001b[0m\n\u001b[1;32m     55\u001b[0m             \u001b[0mBucket\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbucket\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     56\u001b[0m             \u001b[0mKey\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdest_path\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 57\u001b[0;31m             ExtraArgs=self.get_s3_file_upload_extra_args())\n\u001b[0m\u001b[1;32m     58\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     59\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mlog_artifacts\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlocal_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0martifact_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/boto3/s3/inject.py\u001b[0m in \u001b[0;36mupload_file\u001b[0;34m(self, Filename, Bucket, Key, ExtraArgs, Callback, Config)\u001b[0m\n\u001b[1;32m    129\u001b[0m         return transfer.upload_file(\n\u001b[1;32m    130\u001b[0m             \u001b[0mfilename\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mFilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbucket\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mBucket\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mKey\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 131\u001b[0;31m             extra_args=ExtraArgs, callback=Callback)\n\u001b[0m\u001b[1;32m    132\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    133\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/boto3/s3/transfer.py\u001b[0m in \u001b[0;36mupload_file\u001b[0;34m(self, filename, bucket, key, callback, extra_args)\u001b[0m\n\u001b[1;32m    277\u001b[0m             filename, bucket, key, extra_args, subscribers)\n\u001b[1;32m    278\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 279\u001b[0;31m             \u001b[0mfuture\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    280\u001b[0m         \u001b[0;31m# If a client error was raised, add the backwards compatibility layer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    281\u001b[0m         \u001b[0;31m# that raises a S3UploadFailedError. These specific errors were only\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/s3transfer/futures.py\u001b[0m in \u001b[0;36mresult\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    104\u001b[0m             \u001b[0;31m# however if a KeyboardInterrupt is raised we want want to exit\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    105\u001b[0m             \u001b[0;31m# out of this and propogate the exception.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 106\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_coordinator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    107\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    108\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcancel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/s3transfer/futures.py\u001b[0m in \u001b[0;36mresult\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    263\u001b[0m         \u001b[0;31m# final result.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    264\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_exception\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 265\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_exception\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    266\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_result\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    267\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/s3transfer/tasks.py\u001b[0m in \u001b[0;36m_main\u001b[0;34m(self, transfer_future, **kwargs)\u001b[0m\n\u001b[1;32m    253\u001b[0m             \u001b[0;31m# Call the submit method to start submitting tasks to execute the\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    254\u001b[0m             \u001b[0;31m# transfer.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 255\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_submit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtransfer_future\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtransfer_future\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    256\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mBaseException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    257\u001b[0m             \u001b[0;31m# If there was an exception raised during the submission of task\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/s3transfer/upload.py\u001b[0m in \u001b[0;36m_submit\u001b[0;34m(self, client, config, osutil, request_executor, transfer_future, bandwidth_limiter)\u001b[0m\n\u001b[1;32m    547\u001b[0m         \u001b[0;31m# Determine the size if it was not provided\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    548\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mtransfer_future\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeta\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 549\u001b[0;31m             \u001b[0mupload_input_manager\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprovide_transfer_size\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtransfer_future\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    550\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    551\u001b[0m         \u001b[0;31m# Do a multipart upload if needed, otherwise do a regular put object.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/s3transfer/upload.py\u001b[0m in \u001b[0;36mprovide_transfer_size\u001b[0;34m(self, transfer_future)\u001b[0m\n\u001b[1;32m    235\u001b[0m         transfer_future.meta.provide_transfer_size(\n\u001b[1;32m    236\u001b[0m             self._osutil.get_file_size(\n\u001b[0;32m--> 237\u001b[0;31m                 transfer_future.meta.call_args.fileobj))\n\u001b[0m\u001b[1;32m    238\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    239\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mrequires_multipart_upload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtransfer_future\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/site-packages/s3transfer/utils.py\u001b[0m in \u001b[0;36mget_file_size\u001b[0;34m(self, filename)\u001b[0m\n\u001b[1;32m    243\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    244\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget_file_size\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 245\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetsize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    246\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    247\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mopen_file_chunk_reader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstart_byte\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msize\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallbacks\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/envs/python3/lib/python3.6/genericpath.py\u001b[0m in \u001b[0;36mgetsize\u001b[0;34m(filename)\u001b[0m\n\u001b[1;32m     48\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mgetsize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     49\u001b[0m     \u001b[0;34m\"\"\"Return the size of a file, reported by os.stat().\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 50\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mst_size\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     51\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     52\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'empty_eblow_plot'"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\" Execute this to train model \"\"\"\n",
    "# drop _ids and rfm_ for training\n",
    "feature_vector = df[df.columns.drop(list(df.filter(regex='_id|rfm_segment|gender|recency_value')))]\n",
    "\n",
    "print(f\"Executing model run with feature vector column names {feature_vector.columns}\")\n",
    "\n",
    "# We should use preprocessing and use other interpolation methods too\n",
    "df = df.fillna(-1000)\n",
    "\n",
    "#print(df.head(100))\n",
    "\n",
    "# Initiate training\n",
    "train_clusters(schema, df, feature_vector.columns.tolist(), 'rfm_modelling', modelling_config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(15474, 2)\n",
      "                                              fan_id  cluster\n",
      "0  000b06a1be22ef0a8ff82f504ef3f81ff3522224234821...        1\n",
      "1  000dc180b87292bd3a2889f7bc761b75e12d1caef26b3f...        1\n",
      "2  000e6fe8e4d38c283f51d137106d5d635652436241ae29...        0\n",
      "3  000ea8e44e3e065fa0345440ac63eaa4b842882a20b93d...        1\n",
      "4  0012719ea08d19ddb3790c2ad7aacbf075895b504c0c35...        0\n",
      "preparing dataset ...\n",
      "getting list of unique fans ....\n",
      "getting max tickets for fan ....\n",
      "getting max transaction value for fan ....\n",
      "standardizing gender ....\n",
      "dummy coding gender ....\n",
      "getting fan location distance to event venue ....\n",
      "fan_id                       object\n",
      "time_in_seconds_to_venue    float64\n",
      "dtype: object\n",
      "(15474, 15)\n",
      "fan_id                            object\n",
      "gender                            object\n",
      "age                              float64\n",
      "male                               int64\n",
      "female                             int64\n",
      "max_tickets_per_event            float64\n",
      "max_transcaction_value           float64\n",
      "rfm_segment                       object\n",
      "rfm_recency                        int64\n",
      "rfm_frequency                      int64\n",
      "rfm_monetary                       int64\n",
      "recency_value             datetime64[ns]\n",
      "frequency_value                  float64\n",
      "monetary_value                   float64\n",
      "date_diff                        float64\n",
      "cluster                            int64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "\"\"\" Get cluster output and plot pairplot \"\"\"\n",
    "schema = 'a441ffb172866cb4928c84a73de403ca15da4a54cc535e704413ab621' # unique customer schema id\n",
    "algo = 'kmedoids'\n",
    "\n",
    "clusters = prepare_clustering_output(schema, algo)\n",
    "print(clusters.shape)\n",
    "print(clusters.head(5))\n",
    "clusters.to_csv('clusters.csv', sep=',')\n",
    "# TODO! this is training data.. modularize it to somwhere\n",
    "df1 = prepare_rfm_dataset(schema, 'fan_purchase')\n",
    "df2 = prepare_fan_purchase(schema)\n",
    "df3 = prepare_fan_demographics(schema)\n",
    "df4 = prepare_fan_event_distance(schema)\n",
    "df = pd.merge(df3, df2, how='inner', on=['fan_id'])\n",
    "df = pd.merge(df, df1, how='inner', on=['fan_id'])\n",
    "# df = pd.merge(df, df4, how='inner', on=['fan_id'])\n",
    "print(df.shape)\n",
    "# join with clusters\n",
    "df = pd.merge(df, clusters, how='inner', on=['fan_id'])\n",
    "\n",
    "# Try to convert some strings to numbers\n",
    "print(df.dtypes)\n",
    "cols = df.columns.tolist()\n",
    "df = df.apply(pd.to_numeric, errors='ignore')\n",
    "\n",
    "\n",
    "df.to_csv('cluster_output.csv', sep=',')\n",
    "\n",
    "# Drop _id fields\n",
    "df = df[df.columns.drop(list(df.filter(regex='_id')))]\n",
    "\n",
    "# Only pick fields we want (from feature importance)\n",
    "df = df[['max_transcaction_value','date_diff','monetary_value','cluster']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f825a2767f0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 589.8x540 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Draw pairplot. This can take 20+sec. It should automatically remove _id fields.\n",
    "sns.pairplot(df,\n",
    "             plot_kws={'alpha': 0.6, 's': 80, 'edgecolor': 'k'},\n",
    "             #dropna = True,\n",
    "             #diag_kind='kde',\n",
    "             hue='cluster'\n",
    "             )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_clusters(client_id, df, cols, collection_id, modelling_config):\n",
    "    \n",
    "    feature_vector = df\n",
    "    \n",
    "    original_feature_vector = feature_vector.copy() # This is from legacy, could probably save memory from here\n",
    "    original_cols = cols\n",
    "\n",
    "    \"\"\" Do PCA dimensionality reduction \"\"\"\n",
    "    pca_components =  modelling_config.get('pca_components', False)\n",
    "\n",
    "    modelling_type = modelling_config.get('modelling_type')\n",
    "    logging.info(f\"{modelling_type} with PCA {pca_components} components\")\n",
    "\n",
    "    # TODO! add PCA 4 and extra dimension as \"size\" in plots\n",
    "\n",
    "    if modelling_config.get('pca_components'):\n",
    "        # TODO! Add PCA evaluation metrics\n",
    "        reduced_data = PCA(n_components=pca_components).fit_transform(feature_vector[cols])\n",
    "        reduced_data = pd.DataFrame(reduced_data)\n",
    "        # Our columns are changing\n",
    "        column_names = {x: f\"PCA_{x}\" for x in reduced_data.columns}\n",
    "        reduced_data = reduced_data.rename(columns=column_names)\n",
    "        #reduced_data = reduced_data.rename(columns={0: 'PCA0', 1: 'PCA1', 2: 'PCA2'})\n",
    "        cols = reduced_data.columns.tolist()\n",
    "\n",
    "        # Attach fan_id to the feature vector so we could map output back later \"\"\"\n",
    "        feature_vector = reduced_data.join(feature_vector['fan_id'])\n",
    "\n",
    "    mlflow.tracking.set_tracking_uri('https://mlflow.fansifter.cloud')\n",
    "    try:\n",
    "        \"\"\" Even though 'set_experiment' creates new when not exists,\n",
    "            we explicitly create it to have control over artifact_location\n",
    "            (set_experiment) doesn't expose this option \"\"\"\n",
    "        mlflow.create_experiment(client_id)\n",
    "        mlflow.set_experiment(client_id)\n",
    "        logging.info(\"Created new experiment {}\".format(client_id))\n",
    "    except Exception as e:\n",
    "        logging.info(\"Using existing experiment {}\".format(client_id))\n",
    "        mlflow.set_experiment(client_id)  # Creates a new one if doesn't exist with same name\n",
    "\n",
    "    \"\"\" Add more algorithms here \"\"\"\n",
    "    algorithms = [\n",
    "        # TODO! add affinity propagation algorithm\n",
    "        # TODO! add t-SNE\n",
    "        {'name': 'KMedoids (PAM)', 'func': run_kmedoids_algo, 'db_friendly_name': 'kmedoids'},\n",
    "        #{'name': 'KMeans', 'func': run_knn_algo, 'db_friendly_name': 'kmeans'},\n",
    "        #{'name': 'DBSCAN', 'func': run_dbscan_algo, 'db_friendly_name': 'dbscan'},\n",
    "        ]\n",
    "    mlflow.set_experiment(client_id)\n",
    "    # TODO! Add parallelism, dask, multiprocessing\n",
    "\n",
    "    for algorithm in algorithms:\n",
    "        \"\"\" We make a copy of the dataframe, otherwise we keep operating on the same df.\n",
    "            If we don't do this, then every iteration in loop will add another \"cluster\"\n",
    "            column to dataframe\n",
    "        \"\"\"\n",
    "        df = feature_vector.copy()\n",
    "        algo_name = algorithm['name']\n",
    "\n",
    "        if pca_components:\n",
    "            algo_name = algorithm['name'] + f' PCA {pca_components}'\n",
    "\n",
    "        algo_func = algorithm['func']\n",
    "        logging.info(f\"Running algorithm {algo_name} ...\")\n",
    "\n",
    "        with mlflow.start_run(run_name=f\"{collection_id} - {algo_name} - {modelling_type}\"):\n",
    "            mlflow.set_tag('model_name', algo_name)\n",
    "            mlflow.set_tag('modelling_type', modelling_type)\n",
    "            start_time = time.time()\n",
    "\n",
    "            model, eval_metrics, hyperparams, cluster_output, graph_locations = algo_func(client_id, df, cols, modelling_config)\n",
    "            elapsed_minutes = str(round(((time.time() - start_time) / 60), 2))\n",
    "            logging.info(f\"Model run took {elapsed_minutes} minutes\")\n",
    "\n",
    "            logging.info(\"Logging model run parameters and artifacts ... \")\n",
    "\n",
    "            if modelling_config.get('importance'):\n",
    "                \"\"\" Add feature importance. We calculate feature importance by running random forest, \n",
    "                    and targeting the cluster label we get from clustering model \"\"\"\n",
    "                # Our output index should match with input index\n",
    "                df['cluster'] = cluster_output['cluster']\n",
    "                original_feature_vector['cluster'] = cluster_output['cluster']\n",
    "                target = 'cluster'\n",
    "                feature_importance_plot_location, feature_importance = run_random_forest(client_id, original_feature_vector, original_cols, target, algo_name)\n",
    "                mlflow.log_artifact(feature_importance_plot_location)\n",
    "                mlflow.log_param('feature_importance', feature_importance.tolist())\n",
    "\n",
    "            # ALTER TABLE params ALTER COLUMN value SET DATA TYPE varchar;\n",
    "            mlflow.log_param('collection_id', collection_id)\n",
    "\n",
    "            mlflow.log_param('data_params', {\n",
    "                \"data_shape\": df[cols].shape,\n",
    "                \"original_data_shape\": original_feature_vector[original_cols].shape,\n",
    "                \"features\": cols  # make sure this is always a list\n",
    "            })\n",
    "            mlflow.log_param('original_features', original_cols)\n",
    "            mlflow.log_param('model_params', {\n",
    "                'algorithm': algo_name,\n",
    "                'hyperparams': hyperparams\n",
    "            })\n",
    "\n",
    "            mlflow.log_metrics(eval_metrics)\n",
    "\n",
    "            for location in graph_locations:\n",
    "                mlflow.log_artifact(location)\n",
    "                # delete file from local container, we don't need to retain it\n",
    "                os.remove(location)\n",
    "\n",
    "            if modelling_config.get('save_model'):\n",
    "                logging.info(\"Saving model object ... \")\n",
    "                mlflow.sklearn.log_model(model, client_id)\n",
    "\n",
    "            \"\"\" Get cluster output to csv \"\"\"\n",
    "            #current_path = os.path.abspath('')\n",
    "            logging.info(\"Storing cluster output to csv ... \")\n",
    "            file_location = f'collection_{collection_id}_clusters_output_{algo_name}.csv'\n",
    "            cluster_output.to_csv(file_location, sep=',', encoding='utf-8')\n",
    "            mlflow.log_artifact(file_location)\n",
    "            # delete file from local container, we don't need to retain it\n",
    "            os.remove(file_location)\n",
    "\n",
    "            #if not 'RFM' in modelling_type:\n",
    "            if modelling_config.get('clusters_to_rds'):\n",
    "                logging.info(\"Load clustering output to rds ... \")\n",
    "                db_friendly_name = algorithm['db_friendly_name']\n",
    "                engine = get_rds_engine()\n",
    "                \"\"\" Load cluster output csv to RDS\"\"\"\n",
    "                # TODO! load to collection table with parent = collection_id\n",
    "                cluster_output.to_sql(f'collection_{collection_id}_{db_friendly_name}',\n",
    "                                      engine,\n",
    "                                      schema=client_id,\n",
    "                                      if_exists='replace',\n",
    "                                      index_label='row_id',\n",
    "                                      # index=False\n",
    "                                      )\n",
    "\n",
    "            logging.info(f\"Successfully completed training process for {algo_name}\")\n",
    "\n",
    "    logging.info(\"Done modelling!\")\n",
    "    return cluster_output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda_python3",
   "language": "python",
   "name": "conda_python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
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