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50 lines
1.4 KiB
50 lines
1.4 KiB
{
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"cells": [
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{
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"source": [
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"# Data Setup\n",
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"\n",
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"In this notebook, we demonstrate how to:\n",
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"\n",
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"setup time series data for this module\n",
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"visualize the data\n",
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"The data in this example is taken from the GEFCom2014 forecasting competition1. It consists of 3 years of hourly electricity load and temperature values between 2012 and 2014.\n",
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"\n",
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"1Tao Hong, Pierre Pinson, Shu Fan, Hamidreza Zareipour, Alberto Troccoli and Rob J. Hyndman, \"Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond\", International Journal of Forecasting, vol.32, no.3, pp 896-913, July-September, 2016."
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],
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"cell_type": "markdown",
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"metadata": {}
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}
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],
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"metadata": {
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"kernel_info": {
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"name": "python3"
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},
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"kernelspec": {
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"name": "python37364bit8d3b438fb5fc4430a93ac2cb74d693a7",
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"display_name": "Python 3.7.0 64-bit ('3.7')"
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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": "3.7.0"
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},
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"nteract": {
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"version": "nteract-front-end@1.0.0"
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},
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"metadata": {
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"interpreter": {
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"hash": "70b38d7a306a849643e446cd70466270a13445e5987dfa1344ef2b127438fa4d"
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}
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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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} |