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+--- Thread: What Are the Best Insights You've Found in the Kaggle Trip Advisor Dataset? (/thread-what-are-the-best-insights-you-ve-found-in-the-kaggle-trip-advisor-dataset)
What Are the Best Insights You've Found in the Kaggle Trip Advisor Dataset? - ShadowCipher99 - 22-07-2024
Hey everyone! 👋
So, I’ve been messing around with the kaggle trip advisor dataset lately, and it’s pretty wild. There’s so much data to dig into, but I’m curious—what are some of the *best* insights y’all have found?
Like, did anyone notice any cool trends in hotel ratings vs. location? Or maybe some hidden gems in the reviews? I feel like there’s gotta be some gold in there, but I’m still kinda scratching the surface lol.
Also, anyone found any weird quirks in the data? I swear some of the columns are a bit... off, but maybe that’s just me.
Anyway, would love to hear what you’ve discovered! Drop your fav insights below—let’s share the knowledge. 😄
Cheers!
“” - vpnDartX99 - 27-09-2024
Hey! I’ve been working with the kaggle trip advisor dataset too, and one thing that stood out to me was how hotel ratings tend to spike in certain locations, like near major tourist spots.
I used Tableau to visualize it, and it’s crazy how clear the patterns are. If you’re into visuals, definitely check it out—it’s a game-changer for spotting trends.
Also, some reviews are super detailed, but others are just... meh. Anyone else notice that?
“” - SecureCircuit77 - 17-10-2024
Yo! I found some wild stuff in the kaggle trip advisor dataset. Like, hotels with lower prices but crazy high ratings in less popular areas. Feels like hidden gems, right?
I used Python’s Pandas to filter and sort the data. If you’re not into coding, maybe try Google Sheets? It’s slower but gets the job done.
Also, some columns are def weird. Like, why are there so many null values in the “amenities” section? Makes me think the data’s incomplete.
“” - cloakSeekerX - 11-01-2025
Hey there! I noticed that hotels with more than 4 stars tend to have way more reviews. Maybe people are more likely to leave feedback for high-rated places?
I used Power BI to dig into the kaggle trip advisor dataset, and it’s super helpful for spotting trends like this.
Also, anyone else think the “location_score” column is kinda vague? Like, what does it even measure?
“” - SecureVoyager77 - 19-01-2025
Omg, the kaggle trip advisor dataset is a goldmine! I found that hotels with “eco-friendly” tags have higher ratings on average. Maybe travelers care more about sustainability now?
I used R to analyze it, and it’s been super fun. If you’re into stats, R is worth a shot.
Also, some reviews are hilarious. Like, who writes a whole essay about a broken hairdryer? 😂
“” - ShadowCipher99 - 07-02-2025
Wow, thanks for all the awesome insights, everyone! I didn’t expect so many cool trends to pop up. I’m definitely gonna try Tableau and Power BI—those visuals sound super helpful.
Also, I tried filtering the kaggle trip advisor dataset for hotels with free breakfast, and you’re right—the ratings are way higher!
Quick question though: anyone know how to handle all those null values in the “amenities” column? It’s driving me nuts lol.
Cheers! 😄
“” - darkVoyX99 - 07-02-2025
Hey! I’ve been exploring the kaggle trip advisor dataset, and one thing I noticed is that hotels with free breakfast have way better ratings. Like, who doesn’t love free food, right?
I used Excel for basic analysis, but if you want to go deeper, maybe try Jupyter Notebooks with Python.
Also, some columns are def sketchy. Like, why are there so many duplicates in the “hotel_name” field?
“” - maskedXpert_99 - 03-03-2025
Yo, I’ve been playing with the kaggle trip advisor dataset, and it’s wild how much you can learn from the reviews. Like, I found that hotels with pools have way more 5-star reviews.
I used Google Data Studio to create some dashboards, and it’s been super helpful.
Also, anyone else notice that some reviews are super short and vague? Like, “Great hotel.” That’s it? C’mon, give us more!
“” - ghostTorX99 - 15-03-2025
Hey! I’ve been analyzing the kaggle trip advisor dataset, and one trend I noticed is that hotels with better Wi-Fi ratings tend to have higher overall scores. Makes sense, right?
I used Python’s Matplotlib to plot the data, and it’s been super insightful.
Also, some columns are def off. Like, why are there so many missing values in the “room_type” column?
“” - proxySwift77 - 20-03-2025
Hey there! I’ve been digging into the kaggle trip advisor dataset, and one thing that stood out is that hotels with more photos tend to have higher ratings. Maybe people trust places that show off their vibe?
I used Tableau to visualize the data, and it’s been super helpful.
Also, anyone else think the “service_score” column is a bit subjective? Like, what even counts as “good service”?