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Comedy Show Attendance Decision
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About
A small, focused dataset capturing the history of a person deciding whether to attend local comedy performances. For every event registered, the data includes details pertaining to the comedian performing, such as their experience level and ranking, and registers the binary outcome of attendance. This material is significant as it provides a clean, instructional example for Python Machine Learning exercises, specifically demonstrating the application and functionality of a Decision Tree flow chart used for making decisions based on past data.
Columns
- Age: The age of the comedian performing. The values range from 18 to 66, with a mean of 39.6.
- Experience: The years of professional experience held by the comedian, ranging from 3 to 21 years, with an average of 8.85 years.
- Rank: The relative ranking or rating given to the comedian, with values between 4 and 9.
- Nationality: The country of origin for the comedian. Key origins include the UK (38%) and the USA (31%).
- Go: The target variable, indicating the decision outcome ('should I go? yes/no'). This is a boolean column.
Distribution
The data is available in CSV format under the file name
shows.csv, weighing 229 B. The structure consists of 5 columns and 13 total records. All values across all columns are valid, with no missing or mismatched records. The target variable, 'Go', is reasonably balanced, with 7 records showing attendance (True, 54%) and 6 records showing non-attendance (False, 46%). The data is static and the expected update frequency is Never.Usage
- Teaching and learning fundamental machine learning concepts.
- Developing and demonstrating predictive models using Decision Trees.
- Exploring basic correlation between comedian attributes (like Rank and Experience) and audience behaviour.
- Use as a quick example for Python machine learning tutorials.
Coverage
The geographic scope is derived from the comedian’s country of origin, primarily covering talent from the UK and the USA, with a segment labelled 'Other'. Demographic coverage involves comedians whose ages span from young adults (18) to older professionals (66). The time range represented by the registered events is not explicitly defined.
License
CC0: Public Domain
Who Can Use It
- Students: For building initial machine learning models and understanding data processing.
- Instructors: To provide clear, illustrative examples in machine learning curriculum.
- Hobbyists: For a quick, low-barrier entry point into Python data science and predictive analysis.
Dataset Name Suggestions
- Comedy Show Attendance Decision
- Decision Tree Training Example Data
- Comedian Attributes and Attendance History
Attributes
Original Data Source: Comedy Show Attendance Decision
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