Zad 04.Docker - Konteneryzacja
This commit is contained in:
Cezary Gałązkiewicz
parent
924738d4b3
commit
92a55cfc38
13
Dockerfile
13
Dockerfile
@ -1,19 +1,18 @@
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FROM ubuntu:latest
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RUN apt update && apt install -y python3-pip
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RUN apt install -y unzip
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RUN pip install --user kaggle pandas seaborn sklearn
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RUN apt install -y unzip python3
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RUN pip3 install kaggle pandas seaborn sklearn
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RUN mkdir ~/.kaggle/
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RUN echo '{"username":"ikami1","key":"c70ff184133bfabb351608b128e76cd2"}' > ~/.kaggle/kaggle.json
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WORKDIR /ium
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#COPY ./download_dataset.sh ./
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COPY ./Steel_industry_data.csv ./
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COPY ./process_dataset.py ./
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#COPY ./stats.sh ./
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COPY download_dataset.sh process_dataset.py stats.sh Steel_industry_data.csv ./
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RUN chmod a+x download_dataset.sh process_dataset.py
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#CMD ./download_dataset.sh
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CMD python3 process_dataset.py
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#CMD python3 process_dataset.py
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#CMD ./stats.sh
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539
IUM_dane02.ipynb
539
IUM_dane02.ipynb
@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 1,
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"id": "expected-payroll",
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"metadata": {},
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"outputs": [
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@ -10,36 +10,35 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Requirement already satisfied: kaggle in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (1.5.12)\n",
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"Requirement already satisfied: six>=1.10 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from kaggle) (1.15.0)\n",
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"Requirement already satisfied: certifi in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from kaggle) (2021.10.8)\n",
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"Requirement already satisfied: python-dateutil in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from kaggle) (2.8.1)\n",
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"Requirement already satisfied: requests in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from kaggle) (2.27.1)\n",
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"Requirement already satisfied: tqdm in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from kaggle) (4.59.0)\n",
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"Requirement already satisfied: python-slugify in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from kaggle) (6.1.1)\n",
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"Requirement already satisfied: urllib3 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from kaggle) (1.26.9)\n",
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"Requirement already satisfied: text-unidecode>=1.3 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from python-slugify->kaggle) (1.3)\n",
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"Requirement already satisfied: idna<4,>=2.5 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from requests->kaggle) (3.3)\n",
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"Requirement already satisfied: charset-normalizer~=2.0.0 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from requests->kaggle) (2.0.12)\n",
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"Requirement already satisfied: pandas in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (1.4.1)\n",
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"Requirement already satisfied: pytz>=2020.1 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from pandas) (2022.1)\n",
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"Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from pandas) (2.8.1)\n",
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"Requirement already satisfied: numpy>=1.18.5 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from pandas) (1.20.1)\n",
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"Requirement already satisfied: six>=1.5 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from python-dateutil>=2.8.1->pandas) (1.15.0)\n",
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"Requirement already satisfied: seaborn in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (0.11.2)\n",
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"Requirement already satisfied: pandas>=0.23 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from seaborn) (1.4.1)\n",
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"Requirement already satisfied: numpy>=1.15 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from seaborn) (1.20.1)\n",
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"Requirement already satisfied: scipy>=1.0 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from seaborn) (1.6.1)\n",
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"Requirement already satisfied: matplotlib>=2.2 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from seaborn) (3.5.1)\n",
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"Requirement already satisfied: packaging>=20.0 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from matplotlib>=2.2->seaborn) (20.9)\n",
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"Requirement already satisfied: pyparsing>=2.2.1 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from matplotlib>=2.2->seaborn) (2.4.7)\n",
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"Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from matplotlib>=2.2->seaborn) (4.31.1)\n",
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"Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from matplotlib>=2.2->seaborn) (2.8.1)\n",
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"Requirement already satisfied: pillow>=6.2.0 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from matplotlib>=2.2->seaborn) (9.0.1)\n",
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"Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from matplotlib>=2.2->seaborn) (1.4.0)\n",
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"Requirement already satisfied: cycler>=0.10 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from matplotlib>=2.2->seaborn) (0.11.0)\n",
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"Requirement already satisfied: pytz>=2020.1 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from pandas>=0.23->seaborn) (2022.1)\n",
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"Requirement already satisfied: six>=1.5 in c:\\users\\cgala\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from python-dateutil>=2.7->matplotlib>=2.2->seaborn) (1.15.0)\n"
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"Requirement already satisfied: kaggle in c:\\users\\cgala\\anaconda3\\lib\\site-packages (1.5.12)\n",
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"Requirement already satisfied: tqdm in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from kaggle) (4.50.2)\n",
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"Requirement already satisfied: requests in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from kaggle) (2.24.0)\n",
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"Requirement already satisfied: certifi in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from kaggle) (2020.6.20)\n",
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"Requirement already satisfied: six>=1.10 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from kaggle) (1.15.0)\n",
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"Requirement already satisfied: python-slugify in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from kaggle) (6.1.1)\n",
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"Requirement already satisfied: urllib3 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from kaggle) (1.25.11)\n",
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"Requirement already satisfied: python-dateutil in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from kaggle) (2.8.1)\n",
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"Requirement already satisfied: idna<3,>=2.5 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from requests->kaggle) (2.10)\n",
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"Requirement already satisfied: chardet<4,>=3.0.2 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from requests->kaggle) (3.0.4)\n",
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"Requirement already satisfied: text-unidecode>=1.3 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from python-slugify->kaggle) (1.3)\n",
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"Requirement already satisfied: pandas in c:\\users\\cgala\\anaconda3\\lib\\site-packages (1.1.3)\n",
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"Requirement already satisfied: python-dateutil>=2.7.3 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from pandas) (2.8.1)\n",
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"Requirement already satisfied: numpy>=1.15.4 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from pandas) (1.19.2)\n",
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"Requirement already satisfied: pytz>=2017.2 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from pandas) (2020.1)\n",
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"Requirement already satisfied: six>=1.5 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from python-dateutil>=2.7.3->pandas) (1.15.0)\n",
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"Requirement already satisfied: seaborn in c:\\users\\cgala\\anaconda3\\lib\\site-packages (0.11.0)\n",
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"Requirement already satisfied: numpy>=1.15 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from seaborn) (1.19.2)\n",
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"Requirement already satisfied: scipy>=1.0 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from seaborn) (1.5.2)\n",
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"Requirement already satisfied: matplotlib>=2.2 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from seaborn) (3.3.2)\n",
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"Requirement already satisfied: pandas>=0.23 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from seaborn) (1.1.3)\n",
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"Requirement already satisfied: python-dateutil>=2.1 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from matplotlib>=2.2->seaborn) (2.8.1)\n",
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"Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from matplotlib>=2.2->seaborn) (1.3.0)\n",
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"Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from matplotlib>=2.2->seaborn) (2.4.7)\n",
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"Requirement already satisfied: cycler>=0.10 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from matplotlib>=2.2->seaborn) (0.10.0)\n",
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"Requirement already satisfied: pillow>=6.2.0 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from matplotlib>=2.2->seaborn) (8.0.1)\n",
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"Requirement already satisfied: certifi>=2020.06.20 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from matplotlib>=2.2->seaborn) (2020.6.20)\n",
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"Requirement already satisfied: pytz>=2017.2 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from pandas>=0.23->seaborn) (2020.1)\n",
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"Requirement already satisfied: six>=1.5 in c:\\users\\cgala\\anaconda3\\lib\\site-packages (from python-dateutil>=2.1->matplotlib>=2.2->seaborn) (1.15.0)\n"
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]
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}
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],
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@ -51,7 +50,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 3,
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"id": "genetic-plaintiff",
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"metadata": {},
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"outputs": [
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@ -69,18 +68,18 @@
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"text": [
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"\n",
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" 0%| | 0.00/484k [00:00<?, ?B/s]\n",
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"100%|##########| 484k/484k [00:00<00:00, 3.32MB/s]\n",
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"100%|##########| 484k/484k [00:00<00:00, 3.29MB/s]\n"
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"100%|##########| 484k/484k [00:00<00:00, 2.36MB/s]\n",
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"100%|##########| 484k/484k [00:00<00:00, 2.36MB/s]\n"
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]
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}
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],
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"source": [
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"!kaggle datasets download -d csafrit2/steel-industry-energy-consumption"
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"!kaggle datasets download -d csafrit2/steel-industry-energy-consumption --force"
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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": 2,
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"execution_count": 3,
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"id": "compatible-following",
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"metadata": {},
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"outputs": [
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@ -628,7 +627,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 6,
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"id": "loved-delight",
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"metadata": {},
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"outputs": [
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"output_type": "stream",
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"text": [
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"Training set size:\n",
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"(31536, 11)\n",
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"(28032, 11)\n",
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"Testing set size:\n",
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"(1752, 11)\n",
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"(3504, 11)\n",
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"Dev set size:\n",
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"(1752, 11)\n"
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"(3504, 11)\n"
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]
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}
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],
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"source": [
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"from sklearn.model_selection import train_test_split\n",
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"\n",
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"train_data, test_data = train_test_split(energy_data, test_size=3504, random_state=1)\n",
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"test_data, dev_data = train_test_split(test_data, test_size=1752, random_state=1)\n",
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"train_data, test_data = train_test_split(energy_data, test_size=7008, random_state=1)\n",
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"test_data, dev_data = train_test_split(test_data, test_size=3504, random_state=1)\n",
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"print('Training set size:')\n",
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"print(train_data.shape)\n",
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"print('Testing set size:')\n",
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 7,
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"id": "formed-virginia",
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"metadata": {},
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"outputs": [
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" <tbody>\n",
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" <tr>\n",
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" <th>count</th>\n",
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" <td>31536</td>\n",
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" <td>31536.000000</td>\n",
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" <td>31536.000000</td>\n",
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" <td>31536.000000</td>\n",
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" <td>31536.000000</td>\n",
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" <td>31536.000000</td>\n",
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" <td>31536.000000</td>\n",
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" <td>31536.000000</td>\n",
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" <td>31536</td>\n",
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" <td>31536</td>\n",
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" <td>31536</td>\n",
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" <td>28032</td>\n",
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" <td>28032.000000</td>\n",
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" <td>28032.000000</td>\n",
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" <td>28032.000000</td>\n",
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" <td>28032.000000</td>\n",
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" <td>28032.000000</td>\n",
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" <td>28032.000000</td>\n",
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" <td>28032.000000</td>\n",
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" <td>28032</td>\n",
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" <td>28032</td>\n",
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" <td>28032</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>unique</th>\n",
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" <td>31536</td>\n",
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" <td>28032</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>top</th>\n",
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" <td>30/01/2018 00:15</td>\n",
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" <td>07/08/2018 14:15</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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@ -751,20 +750,20 @@
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>22514</td>\n",
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" <td>4560</td>\n",
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" <td>16280</td>\n",
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" <td>19998</td>\n",
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" <td>4087</td>\n",
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" <td>14467</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>mean</th>\n",
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" <td>NaN</td>\n",
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" <td>27.369449</td>\n",
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" <td>13.037946</td>\n",
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" <td>3.866059</td>\n",
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" <td>0.011513</td>\n",
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" <td>80.525058</td>\n",
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" <td>84.410086</td>\n",
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" <td>42707.363014</td>\n",
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" <td>27.340174</td>\n",
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" <td>13.026801</td>\n",
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" <td>3.875001</td>\n",
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" <td>0.011498</td>\n",
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" <td>80.520145</td>\n",
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" <td>84.369511</td>\n",
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" <td>42761.429795</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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@ -772,13 +771,13 @@
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" <tr>\n",
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" <th>std</th>\n",
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" <td>NaN</td>\n",
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" <td>33.473304</td>\n",
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" <td>16.302910</td>\n",
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" <td>7.434250</td>\n",
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" <td>0.016159</td>\n",
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" <td>18.929571</td>\n",
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" <td>30.436675</td>\n",
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" <td>24968.193911</td>\n",
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" <td>33.469130</td>\n",
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" <td>16.289348</td>\n",
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" <td>7.445898</td>\n",
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" <td>0.016153</td>\n",
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" <td>18.932825</td>\n",
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" <td>30.462193</td>\n",
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" <td>24944.585138</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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@ -801,11 +800,11 @@
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" <th>25%</th>\n",
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" <td>NaN</td>\n",
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" <td>3.200000</td>\n",
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" <td>2.330000</td>\n",
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" <td>2.300000</td>\n",
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" <td>0.000000</td>\n",
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" <td>0.000000</td>\n",
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" <td>63.200000</td>\n",
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" <td>99.720000</td>\n",
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" <td>63.227500</td>\n",
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" <td>99.710000</td>\n",
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" <td>20700.000000</td>\n",
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" <td>NaN</td>\n",
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" <td>NaN</td>\n",
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@ -818,9 +817,9 @@
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" <td>5.000000</td>\n",
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" <td>0.000000</td>\n",
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" <td>0.000000</td>\n",
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" <td>87.900000</td>\n",
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" <td>87.870000</td>\n",
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||||
" <td>100.000000</td>\n",
|
||||
" <td>42300.000000</td>\n",
|
||||
" <td>43200.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -828,13 +827,13 @@
|
||||
" <tr>\n",
|
||||
" <th>75%</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>51.230000</td>\n",
|
||||
" <td>22.650000</td>\n",
|
||||
" <td>1.980000</td>\n",
|
||||
" <td>51.190000</td>\n",
|
||||
" <td>22.750000</td>\n",
|
||||
" <td>2.020000</td>\n",
|
||||
" <td>0.020000</td>\n",
|
||||
" <td>98.970000</td>\n",
|
||||
" <td>99.000000</td>\n",
|
||||
" <td>100.000000</td>\n",
|
||||
" <td>63900.000000</td>\n",
|
||||
" <td>64800.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -859,59 +858,59 @@
|
||||
],
|
||||
"text/plain": [
|
||||
" date Usage_kWh Lagging_Current_Reactive.Power_kVarh \\\n",
|
||||
"count 31536 31536.000000 31536.000000 \n",
|
||||
"unique 31536 NaN NaN \n",
|
||||
"top 30/01/2018 00:15 NaN NaN \n",
|
||||
"count 28032 28032.000000 28032.000000 \n",
|
||||
"unique 28032 NaN NaN \n",
|
||||
"top 07/08/2018 14:15 NaN NaN \n",
|
||||
"freq 1 NaN NaN \n",
|
||||
"mean NaN 27.369449 13.037946 \n",
|
||||
"std NaN 33.473304 16.302910 \n",
|
||||
"mean NaN 27.340174 13.026801 \n",
|
||||
"std NaN 33.469130 16.289348 \n",
|
||||
"min NaN 0.000000 0.000000 \n",
|
||||
"25% NaN 3.200000 2.330000 \n",
|
||||
"25% NaN 3.200000 2.300000 \n",
|
||||
"50% NaN 4.570000 5.000000 \n",
|
||||
"75% NaN 51.230000 22.650000 \n",
|
||||
"75% NaN 51.190000 22.750000 \n",
|
||||
"max NaN 157.180000 96.910000 \n",
|
||||
"\n",
|
||||
" Leading_Current_Reactive_Power_kVarh CO2(tCO2) \\\n",
|
||||
"count 31536.000000 31536.000000 \n",
|
||||
"count 28032.000000 28032.000000 \n",
|
||||
"unique NaN NaN \n",
|
||||
"top NaN NaN \n",
|
||||
"freq NaN NaN \n",
|
||||
"mean 3.866059 0.011513 \n",
|
||||
"std 7.434250 0.016159 \n",
|
||||
"mean 3.875001 0.011498 \n",
|
||||
"std 7.445898 0.016153 \n",
|
||||
"min 0.000000 0.000000 \n",
|
||||
"25% 0.000000 0.000000 \n",
|
||||
"50% 0.000000 0.000000 \n",
|
||||
"75% 1.980000 0.020000 \n",
|
||||
"75% 2.020000 0.020000 \n",
|
||||
"max 27.760000 0.070000 \n",
|
||||
"\n",
|
||||
" Lagging_Current_Power_Factor Leading_Current_Power_Factor \\\n",
|
||||
"count 31536.000000 31536.000000 \n",
|
||||
"count 28032.000000 28032.000000 \n",
|
||||
"unique NaN NaN \n",
|
||||
"top NaN NaN \n",
|
||||
"freq NaN NaN \n",
|
||||
"mean 80.525058 84.410086 \n",
|
||||
"std 18.929571 30.436675 \n",
|
||||
"mean 80.520145 84.369511 \n",
|
||||
"std 18.932825 30.462193 \n",
|
||||
"min 0.000000 0.000000 \n",
|
||||
"25% 63.200000 99.720000 \n",
|
||||
"50% 87.900000 100.000000 \n",
|
||||
"75% 98.970000 100.000000 \n",
|
||||
"25% 63.227500 99.710000 \n",
|
||||
"50% 87.870000 100.000000 \n",
|
||||
"75% 99.000000 100.000000 \n",
|
||||
"max 100.000000 100.000000 \n",
|
||||
"\n",
|
||||
" NSM WeekStatus Day_of_week Load_Type \n",
|
||||
"count 31536.000000 31536 31536 31536 \n",
|
||||
"count 28032.000000 28032 28032 28032 \n",
|
||||
"unique NaN 2 7 3 \n",
|
||||
"top NaN Weekday Monday Light_Load \n",
|
||||
"freq NaN 22514 4560 16280 \n",
|
||||
"mean 42707.363014 NaN NaN NaN \n",
|
||||
"std 24968.193911 NaN NaN NaN \n",
|
||||
"freq NaN 19998 4087 14467 \n",
|
||||
"mean 42761.429795 NaN NaN NaN \n",
|
||||
"std 24944.585138 NaN NaN NaN \n",
|
||||
"min 0.000000 NaN NaN NaN \n",
|
||||
"25% 20700.000000 NaN NaN NaN \n",
|
||||
"50% 42300.000000 NaN NaN NaN \n",
|
||||
"75% 63900.000000 NaN NaN NaN \n",
|
||||
"50% 43200.000000 NaN NaN NaN \n",
|
||||
"75% 64800.000000 NaN NaN NaN \n",
|
||||
"max 85500.000000 NaN NaN NaN "
|
||||
]
|
||||
},
|
||||
"execution_count": 12,
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@ -922,7 +921,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"execution_count": 8,
|
||||
"id": "radical-score",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -963,21 +962,21 @@
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>count</th>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>unique</th>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -991,7 +990,7 @@
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>top</th>\n",
|
||||
" <td>07/05/2018 06:00</td>\n",
|
||||
" <td>20/06/2018 13:00</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1000,7 +999,7 @@
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>Weekday</td>\n",
|
||||
" <td>Tuesday</td>\n",
|
||||
" <td>Wednesday</td>\n",
|
||||
" <td>Light_Load</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
@ -1013,20 +1012,20 @@
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>1268</td>\n",
|
||||
" <td>291</td>\n",
|
||||
" <td>898</td>\n",
|
||||
" <td>2522</td>\n",
|
||||
" <td>527</td>\n",
|
||||
" <td>1837</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>mean</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>27.330982</td>\n",
|
||||
" <td>12.649024</td>\n",
|
||||
" <td>3.949281</td>\n",
|
||||
" <td>0.011530</td>\n",
|
||||
" <td>81.364526</td>\n",
|
||||
" <td>83.630702</td>\n",
|
||||
" <td>43080.821918</td>\n",
|
||||
" <td>26.355685</td>\n",
|
||||
" <td>12.374717</td>\n",
|
||||
" <td>3.891093</td>\n",
|
||||
" <td>0.011050</td>\n",
|
||||
" <td>80.687751</td>\n",
|
||||
" <td>84.082794</td>\n",
|
||||
" <td>42594.092466</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1034,13 +1033,13 @@
|
||||
" <tr>\n",
|
||||
" <th>std</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>33.484216</td>\n",
|
||||
" <td>16.185283</td>\n",
|
||||
" <td>7.298637</td>\n",
|
||||
" <td>0.016224</td>\n",
|
||||
" <td>18.758338</td>\n",
|
||||
" <td>30.801180</td>\n",
|
||||
" <td>24944.325392</td>\n",
|
||||
" <td>32.519749</td>\n",
|
||||
" <td>15.830961</td>\n",
|
||||
" <td>7.353028</td>\n",
|
||||
" <td>0.015762</td>\n",
|
||||
" <td>19.053018</td>\n",
|
||||
" <td>30.614144</td>\n",
|
||||
" <td>25222.804637</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1052,7 +1051,7 @@
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>41.120000</td>\n",
|
||||
" <td>40.290000</td>\n",
|
||||
" <td>12.540000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1062,13 +1061,13 @@
|
||||
" <tr>\n",
|
||||
" <th>25%</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>3.200000</td>\n",
|
||||
" <td>1.392500</td>\n",
|
||||
" <td>3.192500</td>\n",
|
||||
" <td>2.090000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>64.630000</td>\n",
|
||||
" <td>99.180000</td>\n",
|
||||
" <td>21600.000000</td>\n",
|
||||
" <td>63.130000</td>\n",
|
||||
" <td>99.562500</td>\n",
|
||||
" <td>20700.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1076,13 +1075,13 @@
|
||||
" <tr>\n",
|
||||
" <th>50%</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>4.570000</td>\n",
|
||||
" <td>4.930000</td>\n",
|
||||
" <td>4.500000</td>\n",
|
||||
" <td>4.900000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>88.955000</td>\n",
|
||||
" <td>88.210000</td>\n",
|
||||
" <td>100.000000</td>\n",
|
||||
" <td>43200.000000</td>\n",
|
||||
" <td>42300.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1090,11 +1089,11 @@
|
||||
" <tr>\n",
|
||||
" <th>75%</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>49.870000</td>\n",
|
||||
" <td>21.240000</td>\n",
|
||||
" <td>3.837500</td>\n",
|
||||
" <td>49.570000</td>\n",
|
||||
" <td>20.700000</td>\n",
|
||||
" <td>2.967500</td>\n",
|
||||
" <td>0.020000</td>\n",
|
||||
" <td>99.852500</td>\n",
|
||||
" <td>99.390000</td>\n",
|
||||
" <td>100.000000</td>\n",
|
||||
" <td>64800.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1104,9 +1103,9 @@
|
||||
" <tr>\n",
|
||||
" <th>max</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>143.930000</td>\n",
|
||||
" <td>87.700000</td>\n",
|
||||
" <td>27.540000</td>\n",
|
||||
" <td>153.140000</td>\n",
|
||||
" <td>82.940000</td>\n",
|
||||
" <td>27.650000</td>\n",
|
||||
" <td>0.070000</td>\n",
|
||||
" <td>100.000000</td>\n",
|
||||
" <td>100.000000</td>\n",
|
||||
@ -1121,59 +1120,59 @@
|
||||
],
|
||||
"text/plain": [
|
||||
" date Usage_kWh Lagging_Current_Reactive.Power_kVarh \\\n",
|
||||
"count 1752 1752.000000 1752.000000 \n",
|
||||
"unique 1752 NaN NaN \n",
|
||||
"top 07/05/2018 06:00 NaN NaN \n",
|
||||
"count 3504 3504.000000 3504.000000 \n",
|
||||
"unique 3504 NaN NaN \n",
|
||||
"top 20/06/2018 13:00 NaN NaN \n",
|
||||
"freq 1 NaN NaN \n",
|
||||
"mean NaN 27.330982 12.649024 \n",
|
||||
"std NaN 33.484216 16.185283 \n",
|
||||
"mean NaN 26.355685 12.374717 \n",
|
||||
"std NaN 32.519749 15.830961 \n",
|
||||
"min NaN 2.480000 0.000000 \n",
|
||||
"25% NaN 3.200000 1.392500 \n",
|
||||
"50% NaN 4.570000 4.930000 \n",
|
||||
"75% NaN 49.870000 21.240000 \n",
|
||||
"max NaN 143.930000 87.700000 \n",
|
||||
"25% NaN 3.192500 2.090000 \n",
|
||||
"50% NaN 4.500000 4.900000 \n",
|
||||
"75% NaN 49.570000 20.700000 \n",
|
||||
"max NaN 153.140000 82.940000 \n",
|
||||
"\n",
|
||||
" Leading_Current_Reactive_Power_kVarh CO2(tCO2) \\\n",
|
||||
"count 1752.000000 1752.000000 \n",
|
||||
"count 3504.000000 3504.000000 \n",
|
||||
"unique NaN NaN \n",
|
||||
"top NaN NaN \n",
|
||||
"freq NaN NaN \n",
|
||||
"mean 3.949281 0.011530 \n",
|
||||
"std 7.298637 0.016224 \n",
|
||||
"mean 3.891093 0.011050 \n",
|
||||
"std 7.353028 0.015762 \n",
|
||||
"min 0.000000 0.000000 \n",
|
||||
"25% 0.000000 0.000000 \n",
|
||||
"50% 0.000000 0.000000 \n",
|
||||
"75% 3.837500 0.020000 \n",
|
||||
"max 27.540000 0.070000 \n",
|
||||
"75% 2.967500 0.020000 \n",
|
||||
"max 27.650000 0.070000 \n",
|
||||
"\n",
|
||||
" Lagging_Current_Power_Factor Leading_Current_Power_Factor \\\n",
|
||||
"count 1752.000000 1752.000000 \n",
|
||||
"count 3504.000000 3504.000000 \n",
|
||||
"unique NaN NaN \n",
|
||||
"top NaN NaN \n",
|
||||
"freq NaN NaN \n",
|
||||
"mean 81.364526 83.630702 \n",
|
||||
"std 18.758338 30.801180 \n",
|
||||
"min 41.120000 12.540000 \n",
|
||||
"25% 64.630000 99.180000 \n",
|
||||
"50% 88.955000 100.000000 \n",
|
||||
"75% 99.852500 100.000000 \n",
|
||||
"mean 80.687751 84.082794 \n",
|
||||
"std 19.053018 30.614144 \n",
|
||||
"min 40.290000 12.540000 \n",
|
||||
"25% 63.130000 99.562500 \n",
|
||||
"50% 88.210000 100.000000 \n",
|
||||
"75% 99.390000 100.000000 \n",
|
||||
"max 100.000000 100.000000 \n",
|
||||
"\n",
|
||||
" NSM WeekStatus Day_of_week Load_Type \n",
|
||||
"count 1752.000000 1752 1752 1752 \n",
|
||||
"count 3504.000000 3504 3504 3504 \n",
|
||||
"unique NaN 2 7 3 \n",
|
||||
"top NaN Weekday Tuesday Light_Load \n",
|
||||
"freq NaN 1268 291 898 \n",
|
||||
"mean 43080.821918 NaN NaN NaN \n",
|
||||
"std 24944.325392 NaN NaN NaN \n",
|
||||
"top NaN Weekday Wednesday Light_Load \n",
|
||||
"freq NaN 2522 527 1837 \n",
|
||||
"mean 42594.092466 NaN NaN NaN \n",
|
||||
"std 25222.804637 NaN NaN NaN \n",
|
||||
"min 0.000000 NaN NaN NaN \n",
|
||||
"25% 21600.000000 NaN NaN NaN \n",
|
||||
"50% 43200.000000 NaN NaN NaN \n",
|
||||
"25% 20700.000000 NaN NaN NaN \n",
|
||||
"50% 42300.000000 NaN NaN NaN \n",
|
||||
"75% 64800.000000 NaN NaN NaN \n",
|
||||
"max 85500.000000 NaN NaN NaN "
|
||||
]
|
||||
},
|
||||
"execution_count": 13,
|
||||
"execution_count": 8,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@ -1184,7 +1183,7 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"execution_count": 9,
|
||||
"id": "attempted-lafayette",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
@ -1225,21 +1224,21 @@
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>count</th>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752.000000</td>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504.000000</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>unique</th>\n",
|
||||
" <td>1752</td>\n",
|
||||
" <td>3504</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1253,7 +1252,7 @@
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>top</th>\n",
|
||||
" <td>02/06/2018 02:00</td>\n",
|
||||
" <td>16/11/2018 16:45</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1262,7 +1261,7 @@
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>Weekday</td>\n",
|
||||
" <td>Monday</td>\n",
|
||||
" <td>Tuesday</td>\n",
|
||||
" <td>Light_Load</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
@ -1275,20 +1274,20 @@
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>1274</td>\n",
|
||||
" <td>275</td>\n",
|
||||
" <td>894</td>\n",
|
||||
" <td>2536</td>\n",
|
||||
" <td>543</td>\n",
|
||||
" <td>1768</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>mean</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>27.756787</td>\n",
|
||||
" <td>13.375628</td>\n",
|
||||
" <td>3.880634</td>\n",
|
||||
" <td>0.011729</td>\n",
|
||||
" <td>80.745548</td>\n",
|
||||
" <td>84.345154</td>\n",
|
||||
" <td>43186.643836</td>\n",
|
||||
" <td>28.791849</td>\n",
|
||||
" <td>13.764709</td>\n",
|
||||
" <td>3.818382</td>\n",
|
||||
" <td>0.012212</td>\n",
|
||||
" <td>80.931650</td>\n",
|
||||
" <td>84.639817</td>\n",
|
||||
" <td>42814.469178</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1296,13 +1295,13 @@
|
||||
" <tr>\n",
|
||||
" <th>std</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>32.895802</td>\n",
|
||||
" <td>16.482148</td>\n",
|
||||
" <td>7.376468</td>\n",
|
||||
" <td>0.015943</td>\n",
|
||||
" <td>18.927378</td>\n",
|
||||
" <td>30.475427</td>\n",
|
||||
" <td>24440.888112</td>\n",
|
||||
" <td>34.115238</td>\n",
|
||||
" <td>16.872400</td>\n",
|
||||
" <td>7.325016</td>\n",
|
||||
" <td>0.016499</td>\n",
|
||||
" <td>18.696834</td>\n",
|
||||
" <td>30.258743</td>\n",
|
||||
" <td>24628.829557</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1310,12 +1309,12 @@
|
||||
" <tr>\n",
|
||||
" <th>min</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>2.520000</td>\n",
|
||||
" <td>2.480000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>38.330000</td>\n",
|
||||
" <td>14.070000</td>\n",
|
||||
" <td>13.050000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1324,13 +1323,13 @@
|
||||
" <tr>\n",
|
||||
" <th>25%</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>3.200000</td>\n",
|
||||
" <td>2.270000</td>\n",
|
||||
" <td>3.240000</td>\n",
|
||||
" <td>2.380000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>63.942500</td>\n",
|
||||
" <td>99.690000</td>\n",
|
||||
" <td>22500.000000</td>\n",
|
||||
" <td>64.112500</td>\n",
|
||||
" <td>99.730000</td>\n",
|
||||
" <td>21600.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1338,11 +1337,11 @@
|
||||
" <tr>\n",
|
||||
" <th>50%</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>4.680000</td>\n",
|
||||
" <td>4.720000</td>\n",
|
||||
" <td>5.110000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>0.000000</td>\n",
|
||||
" <td>87.940000</td>\n",
|
||||
" <td>88.325000</td>\n",
|
||||
" <td>100.000000</td>\n",
|
||||
" <td>43200.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1352,11 +1351,11 @@
|
||||
" <tr>\n",
|
||||
" <th>75%</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>52.187500</td>\n",
|
||||
" <td>24.050000</td>\n",
|
||||
" <td>2.177500</td>\n",
|
||||
" <td>53.227500</td>\n",
|
||||
" <td>24.810000</td>\n",
|
||||
" <td>1.917500</td>\n",
|
||||
" <td>0.020000</td>\n",
|
||||
" <td>99.030000</td>\n",
|
||||
" <td>98.792500</td>\n",
|
||||
" <td>100.000000</td>\n",
|
||||
" <td>63900.000000</td>\n",
|
||||
" <td>NaN</td>\n",
|
||||
@ -1366,10 +1365,10 @@
|
||||
" <tr>\n",
|
||||
" <th>max</th>\n",
|
||||
" <td>NaN</td>\n",
|
||||
" <td>139.030000</td>\n",
|
||||
" <td>80.750000</td>\n",
|
||||
" <td>27.580000</td>\n",
|
||||
" <td>0.060000</td>\n",
|
||||
" <td>146.880000</td>\n",
|
||||
" <td>87.700000</td>\n",
|
||||
" <td>27.540000</td>\n",
|
||||
" <td>0.070000</td>\n",
|
||||
" <td>100.000000</td>\n",
|
||||
" <td>100.000000</td>\n",
|
||||
" <td>85500.000000</td>\n",
|
||||
@ -1383,59 +1382,59 @@
|
||||
],
|
||||
"text/plain": [
|
||||
" date Usage_kWh Lagging_Current_Reactive.Power_kVarh \\\n",
|
||||
"count 1752 1752.000000 1752.000000 \n",
|
||||
"unique 1752 NaN NaN \n",
|
||||
"top 02/06/2018 02:00 NaN NaN \n",
|
||||
"count 3504 3504.000000 3504.000000 \n",
|
||||
"unique 3504 NaN NaN \n",
|
||||
"top 16/11/2018 16:45 NaN NaN \n",
|
||||
"freq 1 NaN NaN \n",
|
||||
"mean NaN 27.756787 13.375628 \n",
|
||||
"std NaN 32.895802 16.482148 \n",
|
||||
"min NaN 2.520000 0.000000 \n",
|
||||
"25% NaN 3.200000 2.270000 \n",
|
||||
"50% NaN 4.680000 5.110000 \n",
|
||||
"75% NaN 52.187500 24.050000 \n",
|
||||
"max NaN 139.030000 80.750000 \n",
|
||||
"mean NaN 28.791849 13.764709 \n",
|
||||
"std NaN 34.115238 16.872400 \n",
|
||||
"min NaN 2.480000 0.000000 \n",
|
||||
"25% NaN 3.240000 2.380000 \n",
|
||||
"50% NaN 4.720000 5.110000 \n",
|
||||
"75% NaN 53.227500 24.810000 \n",
|
||||
"max NaN 146.880000 87.700000 \n",
|
||||
"\n",
|
||||
" Leading_Current_Reactive_Power_kVarh CO2(tCO2) \\\n",
|
||||
"count 1752.000000 1752.000000 \n",
|
||||
"count 3504.000000 3504.000000 \n",
|
||||
"unique NaN NaN \n",
|
||||
"top NaN NaN \n",
|
||||
"freq NaN NaN \n",
|
||||
"mean 3.880634 0.011729 \n",
|
||||
"std 7.376468 0.015943 \n",
|
||||
"mean 3.818382 0.012212 \n",
|
||||
"std 7.325016 0.016499 \n",
|
||||
"min 0.000000 0.000000 \n",
|
||||
"25% 0.000000 0.000000 \n",
|
||||
"50% 0.000000 0.000000 \n",
|
||||
"75% 2.177500 0.020000 \n",
|
||||
"max 27.580000 0.060000 \n",
|
||||
"75% 1.917500 0.020000 \n",
|
||||
"max 27.540000 0.070000 \n",
|
||||
"\n",
|
||||
" Lagging_Current_Power_Factor Leading_Current_Power_Factor \\\n",
|
||||
"count 1752.000000 1752.000000 \n",
|
||||
"count 3504.000000 3504.000000 \n",
|
||||
"unique NaN NaN \n",
|
||||
"top NaN NaN \n",
|
||||
"freq NaN NaN \n",
|
||||
"mean 80.745548 84.345154 \n",
|
||||
"std 18.927378 30.475427 \n",
|
||||
"min 38.330000 14.070000 \n",
|
||||
"25% 63.942500 99.690000 \n",
|
||||
"50% 87.940000 100.000000 \n",
|
||||
"75% 99.030000 100.000000 \n",
|
||||
"mean 80.931650 84.639817 \n",
|
||||
"std 18.696834 30.258743 \n",
|
||||
"min 38.330000 13.050000 \n",
|
||||
"25% 64.112500 99.730000 \n",
|
||||
"50% 88.325000 100.000000 \n",
|
||||
"75% 98.792500 100.000000 \n",
|
||||
"max 100.000000 100.000000 \n",
|
||||
"\n",
|
||||
" NSM WeekStatus Day_of_week Load_Type \n",
|
||||
"count 1752.000000 1752 1752 1752 \n",
|
||||
"count 3504.000000 3504 3504 3504 \n",
|
||||
"unique NaN 2 7 3 \n",
|
||||
"top NaN Weekday Monday Light_Load \n",
|
||||
"freq NaN 1274 275 894 \n",
|
||||
"mean 43186.643836 NaN NaN NaN \n",
|
||||
"std 24440.888112 NaN NaN NaN \n",
|
||||
"top NaN Weekday Tuesday Light_Load \n",
|
||||
"freq NaN 2536 543 1768 \n",
|
||||
"mean 42814.469178 NaN NaN NaN \n",
|
||||
"std 24628.829557 NaN NaN NaN \n",
|
||||
"min 0.000000 NaN NaN NaN \n",
|
||||
"25% 22500.000000 NaN NaN NaN \n",
|
||||
"25% 21600.000000 NaN NaN NaN \n",
|
||||
"50% 43200.000000 NaN NaN NaN \n",
|
||||
"75% 63900.000000 NaN NaN NaN \n",
|
||||
"max 85500.000000 NaN NaN NaN "
|
||||
]
|
||||
},
|
||||
"execution_count": 14,
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@ -1443,6 +1442,18 @@
|
||||
"source": [
|
||||
"dev_data.describe(include='all')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"id": "banned-scottish",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"test_data.to_csv(\"steel_industry_data_test.csv\", encoding=\"utf-8\", index=False)\n",
|
||||
"dev_data.to_csv(\"steel_industry_data_dev.csv\", encoding=\"utf-8\", index=False)\n",
|
||||
"train_data.to_csv(\"steel_industry_data_train.csv\", encoding=\"utf-8\", index=False)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
@ -1466,4 +1477,4 @@
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
}
|
||||
@ -1,5 +1,7 @@
|
||||
pipeline {
|
||||
agent any
|
||||
agent {
|
||||
docker { image 'ikami1/ium:v1' }
|
||||
}
|
||||
parameters {
|
||||
buildSelector(
|
||||
defaultSelector: lastSuccessful(),
|
||||
|
||||
@ -1,2 +1,2 @@
|
||||
kaggle datasets download -d csafrit2/steel-industry-energy-consumption --force
|
||||
unzip -o -j steel-industry-energy-consumption.zip
|
||||
kaggle datasets download -d csafrit2/steel-industry-energy-consumption
|
||||
unzip -o steel-industry-energy-consumption.zip
|
||||
@ -1,5 +1,7 @@
|
||||
pipeline {
|
||||
agent any
|
||||
agent {
|
||||
dockerfile true
|
||||
}
|
||||
parameters {
|
||||
string(
|
||||
defaultValue: 'ikami1',
|
||||
@ -8,7 +10,7 @@ pipeline {
|
||||
trim: false
|
||||
)
|
||||
password(
|
||||
defaultValue: 'c70ff184133bfabb351608b128e76cd2',
|
||||
defaultValue: '',
|
||||
description: 'Kaggle token taken from kaggle.json file, as described in https://github.com/Kaggle/kaggle-api#api-credentials',
|
||||
name: 'KAGGLE_KEY'
|
||||
)
|
||||
@ -38,7 +40,8 @@ pipeline {
|
||||
withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}",
|
||||
"KAGGLE_KEY=${params.KAGGLE_KEY}",
|
||||
"CUTOFF=${params.CUTOFF}"]) {
|
||||
sh "./download.sh"
|
||||
sh "./download_dataset.sh"
|
||||
sh "python3 process_dataset.py"
|
||||
archiveArtifacts artifacts: "steel_industry_data_test.csv, steel_industry_data_dev.csv, steel_industry_data_train.csv"
|
||||
}
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user