Tips Dataset
The Tips dataset contains information about tips received by waitstaff in a restaurant. It’s commonly used for regression and exploratory data analysis (EDA). The dataset includes features such as total bill amount, tip amount, gender of the person paying the bill, whether the person is a smoker, day of the week, time of day, and size of the party.
Advantages: Simple and intuitive, good for demonstrating basic statistical analysis and visualization.
Disadvantages: Small size limits complexity of analyses, limited to restaurant tipping context.
Features and Characteristics
- total_bill: Total bill amount (numerical)
- tip: Tip amount (numerical)
- sex: Gender of the person paying the bill (categorical)
- smoker: Whether the person is a smoker (categorical)
- day: Day of the week (categorical)
- time: Time of day (Lunch/Dinner) (categorical)
- size: Size of the party (numerical)
How to load Tips Dataset?
import seaborn as sns
tips = sns.load_dataset("tips")
print(tips.head())
total_bill | tip | sex | smoker | day | time | size |
---|---|---|---|---|---|---|
16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
21.01 | 3.50 | Male | No | Sun | Dinner | 3 |
23.68 | 3.31 | Male | No | Sun | Dinner | 2 |
24.59 | 3.61 | Female | No | Sun | Dinner | 4 |
Seaborn Datasets For Data Science
Seaborn, a Python data visualization library, offers a range of built-in datasets that are perfect for practicing and demonstrating various data science concepts. These datasets are designed to be simple, intuitive, and easy to work with, making them ideal for beginners and experienced data scientists alike.
In this article, we’ll explore the different datasets available in Seaborn, their characteristics, advantages, and disadvantages, and how they can be used for various data analysis and visualization tasks.
Seaborn Datasets For Data Science
- 1. Tips Dataset
- 2. Iris Dataset
- 3. Penguins Dataset
- 4. Flights Dataset
- 5. Diamonds Dataset
- 6. Titanic Dataset
- 7. Exercise Dataset
- 8. MPG Dataset
- 9. Planets Dataset