Tips Dataset 2024 Istanbul

This dataset simulates real-world tipping and spending behavior in Istanbul's restaurants for the year 2024. It includes detailed information on customer group size, total spending, cuisine preferences, sitting time, payment methods, and tips. The data was designed to reflect realistic scenarios, with key considerations for Turkish dining habits, economic conditions, and cultural norms.

Key Features:
person: Number of people in the dining group (1-8).

total: Total bill amount in Turkish Lira, reflecting an average per-person spending range of 180₺ to 600₺.

cuisine: Cuisine type served at the restaurant, including popular categories like kebab, doner, Turkish, pizza, and international cuisines.

restaurant: Restaurant identifier to indicate the establishment where the transaction occurred.

sitting_time: Time spent at the restaurant (in minutes), ranging from quick meals to extended dining experiences.

payment_type: Method of payment (cash, credit card, or meal card).

tips: Amount of tip left by the customer, adhering to typical tipping practices in Turkey (rounded to the nearest valid banknote denomination: 5, 10, 20, 50, 100, 200₺).

Dataset Context:

The dataset represents diverse dining scenarios, including both common and outlier cases:

Small groups spending more on premium experiences.

Larger groups with shared bills and moderate tipping.

Outliers where tips may be disproportionately low or high compared to the total spending.

The data aims to provide valuable insights for machine learning models, such as predicting tipping behavior, understanding spending patterns, or segmenting customers by group size and preferences. This dataset also captures the cultural and economic nuances of dining out in Istanbul's vibrant restaurant scene in 2024.

Note:

This dataset is fictional and was created for analytical purposes. While the data is not derived from actual records, significant effort was made to ensure its consistency and realism to reflect typical scenarios in Istanbul's restaurant industry.