From the course: Python for Time Series Forecasting

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Decomposing California solar energy using data from EIA

Decomposing California solar energy using data from EIA - Python Tutorial

From the course: Python for Time Series Forecasting

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Decomposing California solar energy using data from EIA

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- [Instructor] Time series components. In this notebook, I'll walk you through data coming from the US Energy Administration, EIA. In this case, the hourly generation by fuel type in California. If we be see their dashboard online, here we can see the vast amount of information that they have to explore in Python. In our case, we are working with the generation mix where the data is located in the region of California, and these are the real-time energy fuel types that we get in California. At the end of this notebook, you will learn how to visually interpret the decomposition of the original time series. And not only that, but also the pre-processing steps because here we have the hourly information, but we work with the monthly aggregated information coming only from one source of energy, which in this case will be the solar. So, with solar monthly energy information, we can reach conclusions such as in the month of July, where we see the seasonal components for each one of the…

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