A meticulously compiled dataset providing deep insights into the global fitness industry in 2025. This dataset covers high-demand topics such as the exponential growth of fitness clubs, emerging trends in boutique fitness studios, skyrocketing online fitness training statistics, the flourishing fitness equipment market, and changing consumer behavior and expenditure patterns in the fitness sector.

🔍 The Case of the Disguised Villains: Predicting Team Rocket with Data

In the bustling world of Kanto, where Pokémon battles shape destinies, crime lurks in the shadows. Detective Kotso, the sharpest mind in Pokémon crime investigations, has been tasked with an urgent mission. The mayor suspects that Team Rocket has infiltrated the city, disguising themselves as ordinary citizens.

But Kotso doesn’t work alone—he relies on you, a brilliant data scientist, to uncover the truth. Your job? Analyze the data of 5,000 residents to predict which of the 1,000 unclassified individuals are secretly part of Team Rocket.

Can you spot the hidden patterns? Can Machine Learning crack the case where traditional detective work fails? The fate of Kanto depends on your skills.

📊 Dataset Structure & Features

This dataset holds the key to exposing Team Rocket’s operatives. Below is a breakdown of the features at your disposal:

🕵️ Can You Crack the Case?

This dataset is not just about numbers—it’s a criminal investigation. Hidden patterns lurk beneath the surface, waiting to be uncovered.

• Are certain Pokémon types more common among Team Rocket members?
• Do suspicious financial transactions hint at illegal activities?
• Does their battle strategy betray their allegiance?

This isn’t just another classification task—it’s a race against time to stop Team Rocket before they take control of Kanto!

Detective Kotso is counting on you. Will you rise to the challenge? 🕵️‍♂️🔎

🔎 10 Key Questions & Suggested Analysis Techniques

1️⃣ Do certain Pokémon types indicate suspicious behavior?
- 📈 Graph: Stacked bar chart comparing Pokémon type distribution between Rocket & non-Rocket members.
- 🎯 Test: Chi-square test for correlation.

2️⃣ Is economic status a reliable predictor of criminal affiliation?
- 📊 Graph: Box plot of debt and economic status per Team Rocket status.
- 🏦 Test: ANOVA test for group differences.

3️⃣ Do Team Rocket members have a preference for specific PokéBalls?
- 🎨 Graph: Heatmap of PokéBall usage vs. Team Rocket status.
- ⚡ Test: Chi-square test for independence.

4️⃣ Does a high battle win ratio correlate with Team Rocket membership?
- 📉 Graph: KDE plot of win ratio distribution for both classes.
- 🏆 Test: T-test for mean differences.

5️⃣ Are migration patterns different for Team Rocket members?
- 📈 Graph: Violin plot of migration counts per group.
- 🌍 Test: Mann-Whitney U test.

6️⃣ Do Rocket members tend to avoid charity participation?
- 📊 Graph: Grouped bar chart of charity participation rates.
- 🕵️‍♂️ Test: Fisher’s Exact Test for small sample sizes.

7️⃣ Do Rocket members disguise themselves in certain professions?
- 📊 Graph: Horizontal bar chart of profession frequency per group.
- 🕵️‍♂️ Test: Chi-square test for profession-Team Rocket relationship.

8️⃣ Is there an unusual cluster of Rocket members in specific cities?
- 🗺 Graph: Geographic heatmap of city distributions.
- 📌 Test: Spatial autocorrelation test.

9️⃣ How does badge count affect the likelihood of being a Rocket member?
- 📉 Graph: Histogram of gym badge distributions.
- 🏅 Test: Kruskal-Wallis test.

🔟 **Are there any multi-feature interactions that reve...

The number of members of fitness centers and health clubs within the United States has experienced a near continual increase between 2000 and 2024. In 2024, there were found to be around ** million members of fitness centers and health clubs within the U.S., the greatest number during the period of observation.

Context

This dataset was collected by me, along with my friends during my college days. The dataset mostly contains data from my friends and family members. This dataset has the survey data for the type of fitness practices that people follow.

Acknowledgements

This dataset wouldn't be here without the help of my friends. So, thanks to them!

What is in the dataset

1. Name of the person attending the survey
2. Gender of the person attending the survey
3. Age of the person attending the survey
4. How important is an exercise to you on the scale of 1 to 5
5. How do you describe your current level of fitness? - Perfect, Very good, Good, Average, Unfit
6. How often do you exercise? - Every day, 1 to 2 times a week, 2 to 3 times a week, 3 to 4 times a week, 5 to 6 times a week, never
7. What barriers, if any, prevent you from exercising more regularly? (Select all that applies) - I don't have enough time, I can't stay motivated, ill become too tired, I have an injury, I don't really enjoy exercising, I exercise regularly with no barriers
8. What forms of exercise do you currently participate in? (Select all that applies) - Walking or jogging, gym, swimming, yoga, Zumba dance, lifting weights, team sport, I don't really exercise
9. Do you exercise _? - Alone, With a friend, With a group, Within a class environment, I don't really exercise
10. What time of the day do you prefer to exercise? - Early morning, afternoon, evening
11. How long do you spend exercising per day? - 30 min, 1 hour, 2 hours, 3 hours and above, I don't really exercise
12. Would you say, you eat a healthy balanced diet? - Yes, No, Not always
13. What prevents you from eating a healthy balanced diet, if any? (Select all that applies) - Lack of time, Cost, Ease of access to fast food, Temptation, and cravings, I have a balanced diet
14. How healthy do you consider yourself on a scale of 1 to 5?
15. Have you recommended your friends to follow a fitness routine? - Yes, No
16. Have you ever purchased fitness equipment? - Yes, No
17. What motivates you to exercise? (Select all that applies) - I want to be fit, I want to increase muscle mass and strength, I want to lose weight, I want to be flexible, I want to relieve stress, I want to achieve a sporting goal, I'm not really interested in exercising.