![]() Next, start out by creating a presentation (you could also create an infographic, or even a printed product ). To get here, jump over to Piktochart to make an account - it’s free, and you can log in from Google or Facebook (they won’t post anything without your permission). The full presentation has some other nifty charts as well. Let’s use Piktochart to make an interactive presentation that shows the change in my annual spend over time - something like this: For example, my spend plummeted while I was living abroad in 2009, and it spiked in 20, when I moved and renovated my apartment. (By the way, this TEXT function is pretty flexible about what you put within the quotes.) For instance, writing:Īnyways, now we have a column that shows the year that every order was placed in, and we can surface some insights that reveal milestones and patterns in my own life. Now, just double-click the bottom-right corner of the cell B2 (or whatever cell you just ran the formula in) to apply the formula to all cells beneath it. For example, if the order date in cell A2 was “” and I’d like to put the first three characters of the year into cell B2, I’d put this into B2: Use the TEXT formula in a new “year” column. ![]() Clean the data.Įxtracting the year of each item can be done with a formula ( School of Datahas a great primer on formulas). But the raw data doesn’t have a column for “year”, so I needed to extract that information from the “order date” column. The diversity and clarity of the dataset is remarkable.Īlso, a quick skim in Excel shows that most cells have content - there aren’t any gaps - and the column titles do a good job of explaining what they represent (this isn’t always the case, and that’s when good metadata comes in handy).īased on what I saw, I figured it would be useful to learn how my purchase patterns evolve from year to year. Next, inspect the data.Įach of the 300+ rows corresponds to a different item that I ordered, and there are 40 columns with fields describing everything from the order date and payment method to shipping address and item category (such as “paperback” and “sports”). The data downloads as a single CSV file, which is a common format to store simple information in a table ( here’s a good explanation of the difference between CSV and Excel files). It’s easy to access previous data requests through
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