From the course: Python for Time Series Forecasting
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How to specify the aggregation rule and periods - Python Tutorial
From the course: Python for Time Series Forecasting
How to specify the aggregation rule and periods
- [Instructor] Now, before you get started, there is one thing that I'd like to clarify in this other practical case where we work with the hydroelectric energy generation. We observe the filtering based on these Python codes that you have on California Hydro. And the most important part is the aggregation on pre-processed data. For example, if the data is hourly and we'd like to analyze the annual seasonality, we aggregate the data on a monthly basis. In the rule, we put month at the end. If we want weekly patterns, we aggregate the data daily. In this case, with a d. In this case, with this series, hydropower, we are analyzing it on a weekly basis. And this is how the aggregated hydroelectric generation looks like. There seems to be a yearly seasonality that you observe from year-to-year and some variations inside, like this up and down, this other up and down from January, the water accumulated. And also in 2024. After the summer months, because there is no rain, you observe a huge…
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