Waiter Tips Data from US Restaurants

Comprising information on food servers' tips, intended to analyze factors influencing tip amounts. It was created by scikit-learn and last updated in June 2022. The dataset's specific row and column counts are unknown.

Use Cases

• Analyze the relationship between party size and tip amount to inform table assignment strategies.
• Model tip amounts based on factors like restaurant type and table location to predict server earnings.
• Investigate potential biases in tip distribution across different table locations to assess fairness for staff.

Strengths

• Dataset is provided by scikit-learn, a major machine learning library.
• Last update was recorded on June 23, 2022.
• Dataset is tagged for tabular modality and US region, providing context.

Limitations

• The exact number of rows and columns is unknown, limiting assessment of statistical power.
• Sample data and specific column names are unavailable, hindering immediate exploratory analysis.
• The dataset's size is categorized as 'n1 K', suggesting it may contain fewer than 1,000 records.

Provenance

Source

scikit-learn

Collection Method

Description retrieved from Kaggle; original collection method unknown.

Freshness

2022-06-23

Geography

Regionus tag suggests United States.