Graphics Programs Reference
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microwave premade frozen goods. During my first year of college, I survived
on dorm food and an unlimited supply of tater tots and soft-serve ice cream,
so my mom was worried that I would have nothing to eat after I moved into
an apartment the next year. My daily schedule also revolves around feeding
time, so needless to say, I was eager to learn how to cook.
Each night that summer I stood in the kitchen with my mom, and she would
demonstrate a technique, and then I would mimic her. I learned how to use
a wok, manage heat, prepare my ingredients ahead of time, and magically
ended up with a meal that didn't taste horrible at the end of each session.
During the first weeks of learning, I carefully watched my mom's spatula
movements, took note of ingredient proportions, and where to put dishware
for plating. I tried to do everything exactly the same, and this worked well for
the specific dishes that my mom had planned. Everything was laid out for me
so that she could clearly explain each step.
Then it was time for me to cook on my own. I looked up recipes, sometimes ones
that used only the ingredients I had in the refrigerator or ones that required
that I just grab a few from the grocery store. With measuring cup, spoon, and
timer in hand, I followed each recipe to the teaspoon and the second.
As I followed more recipes, I learned what ingredients tasted good (and gross)
together, when a “teaspoon” meant “around one or three teaspoons, depending
on what's in the pot,” and most important, I learned why so many recipes end with
“season to taste.” Why can't someone just tell me the exact amount of seasoning
to put? Because it varies by dish, even when you cook the same thing twice.
That little change, based on taste, can make the food taste amazing, subpar, or
even inedible. These little changes happen throughout the cooking process,
and the sum of these changes is why you like that dish so much at that one
restaurant across town.
Learning how to visualize data works in the same way. There are general rules
and suggestions that you learn at first. You might follow them to a cue in
the beginning, but as you work with more data and make more things, you
shift and adjust based on what you have and what you see. Those shifts and
adjustments are what make great visualization stand out from the rest.
The goal is to get to the point where you can take any ingredients—your data—
and understand what they represent. The better you understand your data,
the better you can help others understand. That's how you get visualization
that means something.
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