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Code used to construct the graphs in "The Energy Equity Gap: Unveiling Hidden Energy Poverty"
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Pa223/The-Energy-Equity-Gap
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Data processing 1. webscraping temperature data.py: webscrapes hourly temperature from the study region, 2015-2019. 2. defining calendar.py: define calendar, 2015-2019, whether each day is a weekday/weekend, and/or holiday. 3. hourly to daily meter.py: aggregates hourly electricity consumption into daily, adds on calendar and daily mean temperature data. Repeat for all years.
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Code used to construct the graphs in "The Energy Equity Gap: Unveiling Hidden Energy Poverty"
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