Evony Cataleya May 31, 2021 Spreadsheet
Given this data set imagine trying to find out which Fridays you were busy at an appointment at noon while your partner was also busy at an appointment at noon and the descriptions of both of your appointments contained the phrase down town. If you are not familiar with relational databases and SQL it might surprise you to know that the question can be answered by a single simple SQL query. The database and SQL don‘t have it all their own way however. Spreadsheets come in to their own for tasks that benefit from a visual representation. Traditionally databases do not provide a visual way to browse the data in tables without explicitly requesting data.
He was an ex-divorce attorney who had seen firsthand what a messy thing divorce was when lawyers were involved. He developed a program where a couple would meet together, with him present, and work through the divorce piece by piece. Property, finances, kids, pensions. It was a great system. And he was cheap! Relatively speaking. It took about 10 months including some stops and starts (”what do you mean you want some of my inheritance? if you want my inheritance then you STAY married to me”) but in the end we were able to come to terms with each other in a reasonable and fair way.
Here‘s a very simple budget set up. Keep a simple income spreadsheet. List all the sources by name in column A. List how much each brings in in column B. And then, any notes you have for the income (like if it is temporary) in column C. You don‘t need to get very detailed with the income, because it only needs to be accounted for so that we can budget for it‘s use. And, the incomes use is in our expenses spreadsheet. This spreadsheet will be much more complex than the income one. You‘ll need a field for income that you carry over from the income sheet. You‘ll also need a field for a total expenses budgeted for. A third field will give us the budget surplus. We get that by subtracting the budgeted amounts from the income amount. A final field will subtract the actual amount spent from the income, and will serve to tell us where we stand in our budget. If you like, you can add another field that subtracts the actual amount spent from the amount budgeted.
Lester loved his numeric universe, but this was not how he had envisioned his life unfolding; flying hither and thither from his hometown of Hershey to wherever his firm wished to send him. Just because he was 38, single, and still living with his folks didn‘t mean his employer should take advantage of him which, in fact, his company did on a regular basis. After all, Lester had other important interests, too. The ”Four Bs” he called them: Botany, bowling, bugs and Buddy Holly. Myriad plants crowded his tiny room in his parent‘s house, forcibly sucking carbon dioxide out of anyone who entered. Bowling trophies – ranging in size from tiny silver cups to massive bronze edifices shaped like the Empire State Building – claimed space not dominated by flower pots, planter boxes, and hanging baskets.
Microsoft Excel is a phenomenally powerful calculator. You can create spreadsheets with 10,000 lines of data and calculate subtotals instantly. Indeed, if you change your data, any totals will get automatically updated. Arguably that‘s not too impressive. If we have quarterly revenues of $1m, and we secure another $20k, we can update our subtotal without summing revenues from scratch. So it‘s more impressive that Excel can do the same thing with statistical functions. If you‘ve ever plotted a chart on Excel, you may be aware that you can add a best fit line. These best fit lines are calculated using a method known as regression. Basically, you have to calculate the distance of every single point from the line, and minimise the sum. The maths is a little more sophisticated but the key point is that, every time you change the data, you need to perform the analysis all over again.
He grossed $2,000 a week for his bosses, and earned slightly less than $500 for himself. Still, the wages kept him in seeds, bowling shoes, stick pins, and a Platinum Buddy Holly Fan Club Membership. Lester‘s favorite word was ”crapola,” and he applied it to the ball bearing factory‘s antiquated data processing system in coats as thick as the olive drab membrane clinging to the smudgy glass before him. ”You piteous piece of crapola!” he‘d hiss at the computer when error messages flashed across its screen or its ancient system locked under the demand of crunching numbers to the tenth decimal point. ”Some day I‘ll throw your sorry ass into one of those melting pots out there!”