Preppin' Data

Solution by Jonathan Allenby and you can download the  full workflow here .  This week in Preppin' Data we were highlighting the slightly confusing and inconsistent world of vegan shopping. A world where Sweet Chilli crisps, Tesco jam doughnuts, and Kellogg's Crunch Nut Clusters aren't vegan but somehow Bacon Rasher crisps, Co-op jam doughnuts, and Cookie Crisp cereal are somehow. Perhaps most enlightening of all however is that Jammie Dodgers use raspberry flavoured apple jam instead of just using raspberry jam. What a world. Step 1 - Prepare the keywords In order to check whether each product contains any of our non-vegan keywords within their ingredients we're going to take every keyword and E number and place them into a single field, one keyword per row, and append them to the list of products. Prepare the E Numbers There's a few different ways and points where you could attach an 'E' to the start of every number. One great way that we used was to use t...

Challenge by: Jonathan Allenby Now that Veganuary has come and gone we thought it would be interesting to take a look at some common supermarket products and use Prep to figure out whether or not they are vegan. Some results may surprise you! For the sake of this analysis we're taking bee by-products as non-vegan (beeswax, honey, etc). Inputs A shopping list of products and their ingredients (or allergens when ingredients were not available). I have a child-like palate so its mostly full of sweet treats, some of which you'd expect to be vegan and some of which you'd expect not to be, however everything is commonly found in UK supermarkets so no specialist shops required. Two lists of common non-vegan ingredients and E numbers ( source ) Requirements Input the data Prepare the keyword data Add an 'E' in front of every E number. Stack Animal Ingredients and E Numbers on top of each other. Get every ingredient and E number onto separate rows. Append the keywords onto t...