1. 1. Syntax: Python uses a more intuitive and readable syntax compared to SAS. Python uses indentation as the method for grouping statements, making the code more organized and easier to understand. SAS, on the other hand, uses semicolons and keywords to define statements, which can be more complex and harder to read for beginners.

2. 2. Flexibility: Python is a general-purpose programming language that allows for a wide range of applications beyond data analysis. It can be used for web development, artificial intelligence, machine learning, and more. On the other hand, SAS is primarily focused on statistical analysis and data management, making it less versatile than Python.

3. 3. Data Manipulation: Python offers extensive libraries such as Pandas and NumPy that provide powerful tools for data manipulation and analysis. These libraries allow users to easily clean, transform, and analyze data, making Python a popular choice for data scientists. SAS also offers data manipulation capabilities, but it is more limited compared to Python in terms of functionality and ease of use.

4. 4. Visualization: Python provides a wide range of libraries such as Matplotlib and Seaborn that allow for high-quality data visualization. These libraries offer various types of plots and charts to present data in a visually appealing manner. SAS also has visualization capabilities, but it is more focused on basic graphs and lacks the flexibility and customization options provided by Python libraries.

5. 5. Open-Source vs Proprietary: Python is an open-source language, which means it is free to use and has a large community of developers constantly contributing to its development. On the other hand, SAS is a proprietary software, which means it requires a license and access to SAS servers to use. This can make Python a more accessible and cost-effective option for individuals and small businesses.

6. 6. Learning Curve: Python has a more gentle learning curve compared to SAS. Python's syntax and structure are more beginner-friendly and easier to grasp, making it a popular choice for those new to programming. SAS, on the other hand, has a steeper learning curve due to its complex syntax and specialized nature, requiring users to invest more time and effort in learning the language.

In Summary, Python and SAS have distinct differences such as syntax, flexibility, data manipulation capabilities, visualization options, cost, and learning curve. Python offers a more intuitive syntax and has a wider range of applications, while SAS is more focused on statistical analysis and data management. Python has powerful libraries for data manipulation and visualization, while SAS has more limited capabilities in these areas. Python is open-source and has a gentler learning curve compared to SAS.