I'm going with option B. Load the data first, then worry about preparing it. You can't do anything without the data, so that's gotta be the first step.
Definitely C. Preparing the data is the first and most important step. Otherwise, you're just going to end up with a model that's based on messy, unreliable data. No good can come from that.
I'm leaning towards option C. Preparing the data is crucial in any data analysis project. You can't just jump straight into deploying a model without making sure your data is clean and ready to go.
I think option C is the way to go. You need to prepare the data before you can do anything else with it. Loading the data without preparing it first seems like a recipe for disaster.
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