To perform this task, create a notebook in colab which allows you to perform data analysis using python in the cloud for free. Once you are done with the task, please share the notebook with tmramalho@recursiveai.co.jp

The task consists of analysing the dataset for individual household electric power consumption available here. The questions are relatively open ended to allow you to decide on your own what would be the most effective technique to solve the challenge. Suppose the end customer is a power utility company which wishes to use these insights to offer better plans to their customers as well as better manage their grid based on customer usage patterns.

1. Download and process the data into a pandas Dataframe.
2. Visualize the data. It’s a very large dataset, how can we plot it in a way that a human understands its main features?
3. Using a clustering method, identify different power usage patterns of the household.
4. Using a time series regression method, predict the next month’s consumption patterns.
5. Using publicly available data, estimate the GHG Scope 2 emissions of the household on a monthly basis.
6. Assuming a hypothetical grid where generated power is mostly renewables during the day, and fossil fuels at night, identify potential changes to the household’s patterns to minimize its GHG emissions.