Data-Visualization-using-Python

This Notebook explores the "tips" dataset from the Seaborn library.

Performed the following analyses:

- Visualized the relationship between total bill and tip amount, considering gender differences.

- Explored the relationship between tip amount, total bill, and table size.

- Used Seaborn's lmplot to visualize the trend and potential linear relationship between tip and total bill.

- Created histograms to show the distribution of total bill amounts.

- Utilized Seaborn's histplot with kernel density estimation to visualize the distribution of tip amounts.

- Analyzed tip amounts by time and day of the week, using bar plots and stacked bar charts.

- Employed Seaborn's lmplot to visualize the relationship between total bill and tip amount, considering gender and time of day.

- Created histograms to show the distribution of tip amounts and total bill amounts.

This notebook provides insights into tipping patterns based on factors like gender, time of day, and total bill amount.

The visualizations help understand the distribution of these variables and potential relationships between them.