Alright folks, gather ’round. Remember that trip planning headache I was having? My cousin from down south wants to visit Fenway for the first time, bless his heart, but has no clue what kinda jacket to bring when. Kept asking, “Is May cold? Is August brutal?” Honestly, I had a rough idea from going myself, but I wanted actual numbers, not just my feelings. Wanted something solid to tell him.
So, first thing? Went hunting online. Typed in “Boston weather history” and landed on one of those big public weather sites. Sounds easy, right? Wrong. The site was packed with data, like way too much. Monthly stats for decades! Felt like trying to find a specific peanut in a dump truck full of ’em.
Next step? Downloads. Clicked on monthly data files. Must have downloaded like… ten years’ worth? My computer desktop looked scary messy, all .csv files piled up. Opened one in Excel and almost cried. Columns! Rows! Numbers everywhere! Humidity, wind, rain – way more than I needed. Just wanted the average daily high temperature for each month near the ballpark. Just the simple stuff.
Here’s where the real fight started. Trying to get Excel to understand what I wanted:
- Tried using those filter things. Picked ‘TAVG’ (hoping that meant average temp), picked Fenway years.
- Got hundreds of days listed per month. How do I just get one number for each month?
- Stumbled around formulas. Heard of pivot tables? Tried. Felt like I needed a college degree.
- After wasting maybe an hour, got something that sort of looked like monthly averages… for one year. But I had ten years’ worth! Felt impossible.
Finally threw my hands up. Remembered a pal mentioned Python could do this “easy.” Installed some Python thing, copied some code snippet for averaging stuff… sweat bullets trying to point it at the right folder.
Punched in a command, held my breath… and BOOM! Out popped a little list. January: 32.1, February: 34.7… right down to December. Ten years of data, crunched into twelve numbers. Finally! Took some file wrangling to save it nicely, but man, seeing those monthly averages felt like winning the lottery.
Biggest surprise? How much it actually fluctuates even in supposedly “mild” months. April? That average hides some seriously cold nights. September? Way more comfy than I realized compared to August’s stickiness. My cousin definitely needs layers almost anytime except maybe high summer.
So yeah, that’s the journey. Wanted simple answers, found a mountain of messy files, wrestled with Excel until I gave up, then accidentally learned a tiny bit of Python magic to tame the beast. Got the numbers. Next time? Tell your cousin to pack a sweater unless it’s peak July. You’re welcome!
