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Fictional Power Ratings Collection
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About
A powerful fictional data collection featuring character statistics for 200 superheroes and villains originating from the Marvel and DC universes. Each record provides crucial attributes such as strength, speed, intelligence, combat expertise, and an overall calculated power score. The data is suitable for beginners and includes intentionally introduced missing values in certain fields to mimic challenges found in real-world data analysis tasks. It is updated quarterly.
Columns
- Name: The unique identifier for the fictional superhero or villain character (200 unique values).
- Universe: Specifies the origin of the character, either Marvel or DC (2 unique values, 50% Marvel, 50% DC).
- Alignment: Defines the moral leaning of the character: Hero, Villain, or Anti-Hero (Hero is the most frequent category at 37%).
- Strength: Measures the physical power level, rated on a scale of 1 to 10 (10 values are missing, mean is 5.67).
- Speed: Measures movement and combat velocity, rated 1 to 10 (10 values are missing, mean is 5.35).
- Intelligence: Measures strategic thinking and intellect, rated 1 to 10 (10 values are missing, mean is 5.57).
- Combat Skill: Measures fighting proficiency and martial skill, rated 1 to 10 (No missing values, mean is 5.38).
- Weapon: Describes the primary weapon or power type (e.g., Tech, Magic, Sword). The most common is Claws (14%). 10 values are missing.
- Power Score: The overall calculated rating of the character's abilities, ranging from 40 to 100 (No missing values, mean is 71.4).
- Popularity Score: A fictional public rating of the character's popularity, ranging from 1 to 100 (No missing values, mean is 51).
Distribution
The data is a single tabular file, typically provided in CSV format. It contains information on 200 distinct records (fictional characters) and features 10 core attributes (columns). The size of the file is approximately 10.29 kB. The expected refresh rate for this dataset is quarterly.
Usage
This data product is ideal for several data science and machine learning applications:
- Classification: Building models to predict a character's moral alignment (Hero, Villain, Anti-Hero).
- Regression: Developing models to estimate or predict the overall Power Score.
- Clustering: Grouping characters based on shared attributes such as Strength, Speed, and Intelligence.
- Exploratory Data Analysis (EDA): Practising data visualization and deriving insights into fictional character distribution across the two universes.
Coverage
The scope of this data is focused entirely on fictional characters drawn from two specific comic book franchises: Marvel and DC. It covers 200 individual characters, providing detailed stats relevant to their physical and intellectual capabilities. There is no geographic, temporal, or real-world demographic scope. Note that several attribute scores (Strength, Speed, Intelligence, Weapon) contain 5% missing values.
License
CC0: Public Domain
Who Can Use It
- Data Science Students: Utilising a clean, low-volume dataset for practice in machine learning ethics, classification, and regression assignments.
- Educators and Trainers: Creating practical exercises for teaching basic EDA and visualization techniques.
- Hobbyists: Exploring and visualizing the statistical differences between Marvel and DC characters.
- Algorithm Developers: Testing clustering algorithms by grouping heroes based on ability metrics.
Dataset Name Suggestions
- Superhero Abilities Universe Stats
- Marvel and DC Character Metrics
- Fictional Power Ratings Collection
- Comic Book Ability Scores
Attributes
Original Data Source:Fictional Power Ratings Collection
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