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pump-sensor.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": 1,
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"id": "11813bfa",
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"metadata": {
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"_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
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"iopub.execute_input": "2024-05-22T21:47:18.276302Z",
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"iopub.status.idle": "2024-05-22T21:47:19.226594Z",
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"shell.execute_reply": "2024-05-22T21:47:19.224387Z"
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},
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"status": "completed"
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},
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"tags": []
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},
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"outputs": [
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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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"/kaggle/input/pump-sensor-data/sensor.csv\n"
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]
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}
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],
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"source": [
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"# This Python 3 environment comes with many helpful analytics libraries installed\n",
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"# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
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"# For example, here's several helpful packages to load\n",
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"\n",
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"import numpy as np # linear algebra\n",
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"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
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"\n",
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"# Input data files are available in the read-only \"../input/\" directory\n",
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"# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
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"\n",
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"import os\n",
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"for dirname, _, filenames in os.walk('/kaggle/input'):\n",
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" for filename in filenames:\n",
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" print(os.path.join(dirname, filename))\n",
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"\n",
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"# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
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"# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
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]
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},
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{
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"cell_type": "code",
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"id": "1526b0e5",
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" Unnamed: 0 timestamp sensor_00 sensor_01 sensor_02 \\\n",
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" sensor_50 sensor_51 machine_status \n",
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"0 243.0556 201.3889 NORMAL \n",
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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],
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"source": [
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"df = pd.read_csv('/kaggle/input/pump-sensor-data/sensor.csv')\n",
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"df.head()"
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]
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}
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],
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"metadata": {
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"accelerator": "none",
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"input_path": "__notebook__.ipynb",
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"output_path": "__notebook__.ipynb",
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"parameters": {},
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}

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