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Merge pull request #1544 from PrAyAg9/prayag_patch1
Solves #1543 :- EV Battery Life Prediction
2 parents 40fd8d2 + db9c16c commit 0f4e71d

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‎Prediction Models/EV Battery LIfe Prediction/Model/final_notebooks_5.3-ssn-stacker.ipynb

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‎Prediction Models/EV Battery LIfe Prediction/Model/final_notebooks_Final-XGBoost.ipynb

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‎Prediction Models/EV Battery LIfe Prediction/Model/notebooks_Final-Data-Prep-NB.ipynb

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‎Prediction Models/EV Battery LIfe Prediction/Model/notebooks_XGBoost-part-GridSearchCV.ipynb

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‎Prediction Models/EV Battery LIfe Prediction/Model/notebooks_dask_xgb_1.1.ipynb

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‎Prediction Models/EV Battery LIfe Prediction/Model/notebooks_flow_file.ipynb

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‎Prediction Models/EV Battery LIfe Prediction/Model/notebooks_msil_xgb_script.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/javascript": [
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"IPython.notebook.set_autosave_interval(60000)"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Autosaving every 60 seconds\n"
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]
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}
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],
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"source": [
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"%autosave 60"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"BUCKET_NAME = \"msil_raw\"\n",
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"FOLDER_NAME = \"training_data\"\n",
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"TRAINFILE = \"trainset.csv\"\n",
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"VALIDFILE = \"validset.csv\"\n",
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"TESTFILE = \"testset.csv\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"import google.datalab.storage as storage\n",
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"import pandas as pd\n",
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"from io import BytesIO\n",
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"\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"import xgboost as xgb\n",
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"from sklearn.model_selection import GridSearchCV\n",
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"import time\n",
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"from datetime import datetime\n",
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"from scipy import integrate"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"# setting up the parameters\n",
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"plt.rcParams[\"figure.figsize\"] = (10, 10)\n",
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"pd.set_option(\"display.max_rows\", 200)\n",
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"pd.set_option(\"display.max_columns\", 200)\n",
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"pd.set_option(\"precision\", 15)\n",
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"sns.set_style(\"darkgrid\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>IMEI</th>\n",
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" <th>Year</th>\n",
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" <th>Month</th>\n",
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" <th>Day</th>\n",
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" <th>Hour</th>\n",
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" <th>Minute</th>\n",
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" <th>Seconds</th>\n",
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" <th>tp</th>\n",
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" <th>sp</th>\n",
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" <th>EVVSP</th>\n",
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" <th>EVVSP_delta</th>\n",
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" <th>EVVSP_change</th>\n",
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" <th>EVGPO</th>\n",
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" <th>EVOAS</th>\n",
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" <th>EVIGM_Latest</th>\n",
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" <th>EVCOM_Latest</th>\n",
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" <th>EVACO_Z</th>\n",
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" <th>EVIRT_Min</th>\n",
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" <th>EVDI2</th>\n",
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" <th>EVBMI_Latest</th>\n",
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" <th>EVBMA_Latest</th>\n",
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" <th>EVVAC</th>\n",
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" <th>EVVAC_delta</th>\n",
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" <th>EVVAC_change</th>\n",
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" <th>EVODO</th>\n",
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" <th>EVODOH</th>\n",
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" <th>EVSMA_EWMA</th>\n",
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" <th>EVSMA_delta</th>\n",
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" <th>EVSMA_in</th>\n",
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" <th>combine</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>7</td>\n",
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" <td>2018</td>\n",
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" <td>11</td>\n",
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" <td>15</td>\n",
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" <td>10</td>\n",
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" <td>58</td>\n",
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" <td>49</td>\n",
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" <td>1</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0</td>\n",
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" <td>26.0</td>\n",
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" <td>-51</td>\n",
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" <td>-51</td>\n",
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" <td>-1008.0</td>\n",
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" <td>-41</td>\n",
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" <td>20</td>\n",
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" <td>21.5</td>\n",
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" <td>21.5</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>690</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>1606</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>7</td>\n",
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" <td>2018</td>\n",
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" <td>11</td>\n",
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" <td>15</td>\n",
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" <td>10</td>\n",
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" <td>58</td>\n",
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" <td>50</td>\n",
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" <td>1</td>\n",
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" <td>1000.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0</td>\n",
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" <td>26.0</td>\n",
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" <td>-51</td>\n",
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" <td>-51</td>\n",
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" <td>-1004.0</td>\n",
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" <td>-41</td>\n",
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" <td>20</td>\n",
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" <td>21.5</td>\n",
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" <td>21.5</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>690</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>1606</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>7</td>\n",
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" <td>2018</td>\n",
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" <td>11</td>\n",
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" <td>15</td>\n",
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" <td>10</td>\n",
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" <td>58</td>\n",
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" <td>51</td>\n",
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" <td>1</td>\n",
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" <td>2000.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0</td>\n",
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" <td>26.0</td>\n",
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" <td>-51</td>\n",
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" <td>-51</td>\n",
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" <td>-1016.0</td>\n",
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" <td>-41</td>\n",
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" <td>20</td>\n",
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" <td>21.5</td>\n",
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" <td>21.5</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>690</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>1606</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>7</td>\n",
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" <td>2018</td>\n",
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" <td>11</td>\n",
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" <td>15</td>\n",
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" <td>10</td>\n",
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" <td>58</td>\n",
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" <td>52</td>\n",
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" <td>1</td>\n",
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" <td>3000.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0</td>\n",
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" <td>26.0</td>\n",
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" <td>-51</td>\n",
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" <td>-51</td>\n",
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" <td>-1002.0</td>\n",
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" <td>-41</td>\n",
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" <td>20</td>\n",
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" <td>21.5</td>\n",
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" <td>21.5</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>690</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>1606</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>7</td>\n",
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" <td>2018</td>\n",
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" <td>11</td>\n",
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" <td>15</td>\n",
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" <td>10</td>\n",
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" <td>58</td>\n",
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" <td>53</td>\n",
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" <td>1</td>\n",
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" <td>4000.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0</td>\n",
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" <td>26.0</td>\n",
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" <td>-51</td>\n",
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" <td>-51</td>\n",
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" <td>-1012.0</td>\n",
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" <td>-41</td>\n",
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" <td>20</td>\n",
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" <td>21.5</td>\n",
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" <td>21.5</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>690</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>0.0</td>\n",
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" <td>93.200000000000003</td>\n",
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" <td>1606</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" IMEI Year Month Day Hour Minute Seconds tp sp EVVSP \\\n",
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"0 7 2018 11 15 10 58 49 1 0.0 0.0 \n",
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"1 7 2018 11 15 10 58 50 1 1000.0 0.0 \n",
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"2 7 2018 11 15 10 58 51 1 2000.0 0.0 \n",
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"3 7 2018 11 15 10 58 52 1 3000.0 0.0 \n",
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"4 7 2018 11 15 10 58 53 1 4000.0 0.0 \n",
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"\n",
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" EVVSP_delta EVVSP_change EVGPO EVOAS EVIGM_Latest EVCOM_Latest \\\n",
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"0 0.0 0.0 0 26.0 -51 -51 \n",
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"1 0.0 0.0 0 26.0 -51 -51 \n",
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"2 0.0 0.0 0 26.0 -51 -51 \n",
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"3 0.0 0.0 0 26.0 -51 -51 \n",
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"4 0.0 0.0 0 26.0 -51 -51 \n",
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"\n",
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" EVACO_Z EVIRT_Min EVDI2 EVBMI_Latest EVBMA_Latest EVVAC EVVAC_delta \\\n",
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"0 -1008.0 -41 20 21.5 21.5 0.0 0.0 \n",
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"1 -1004.0 -41 20 21.5 21.5 0.0 0.0 \n",
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"2 -1016.0 -41 20 21.5 21.5 0.0 0.0 \n",
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"3 -1002.0 -41 20 21.5 21.5 0.0 0.0 \n",
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"4 -1012.0 -41 20 21.5 21.5 0.0 0.0 \n",
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"\n",
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" EVVAC_change EVODO EVODOH EVSMA_EWMA EVSMA_delta \\\n",
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"0 0.0 690 0.0 93.200000000000003 0.0 \n",
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"1 0.0 690 0.0 93.200000000000003 0.0 \n",
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"2 0.0 690 0.0 93.200000000000003 0.0 \n",
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"3 0.0 690 0.0 93.200000000000003 0.0 \n",
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"4 0.0 690 0.0 93.200000000000003 0.0 \n",
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"\n",
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" EVSMA_in combine \n",
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"0 93.200000000000003 1606 \n",
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"1 93.200000000000003 1606 \n",
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"2 93.200000000000003 1606 \n",
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"3 93.200000000000003 1606 \n",
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"4 93.200000000000003 1606 "
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"mybucket = storage.Bucket(BUCKET_NAME)\n",
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"data_csv = mybucket.object(FOLDER_NAME + \"/\" + TESTFILE)\n",
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"\n",
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"uri = data_csv.uri\n",
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"%gcs read --object $uri --variable data\n",
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"\n",
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"testset = pd.read_csv(BytesIO(data))\n",
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"testset.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import data_proces"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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