Code Review - Terrence Gorman

Apr 10, 2025 by ADMIN 30 views

Overview of the Code Review

In this article, we will be reviewing the code submitted by Terrence Gorman. The code appears to be well-structured and organized, with a clear focus on data analysis and visualization. However, there are a few areas where the code could be improved to make it more efficient and scalable.

Demand Code Review

The demand code in the file Ethiopia 15-16 and 11-12 looks great. The code is well-organized and easy to follow. However, there is one thing that I would consider implementing to make the code even better. It would be beneficial to break down the Google Sheets data into viable data frames and put them into functions that take in year as a parameter. This would make it easy to toggle between data and results across years.

Benefits of Breaking Down Code into Functions

Breaking down the code into functions that take in year as a parameter would have several benefits. Firstly, it would make the code more modular and easier to maintain. If there are any changes to the data or the analysis, it would be easy to update the code without having to rewrite the entire script. Secondly, it would make the code more reusable. If there are any other years that need to be analyzed, it would be easy to simply call the function with the new year as a parameter.

Implementing a Function for Demand

Another function that could be implemented is one that creates a demand function. This function would take in different foods as parameters and make it easy to put in new visualizations without having to keep changing or rewriting the code. This would make the code more flexible and easier to use.

Example of How the Function Could be Implemented

Here is an example of how the function could be implemented:

def demand_function(year, food):
    # Load the data for the given year and food
    data = load_data(year, food)
    
    # Perform the analysis and create the visualization
    visualization = create_visualization(data)
    
    return visualization

Nutrition and Counterfactual Code Review

The nutrition and counterfactual code looks very solid. The code is well-organized and easy to follow. I particularly liked how the external data set was brought in. This shows a good understanding of how to work with external data sources and how to integrate them into the code.

Benefits of Using External Data Sources

Using external data sources can have several benefits. Firstly, it can provide additional insights and information that may not be available from the internal data sources. Secondly, it can make the code more robust and easier to maintain. If there are any changes to the external data source, it would be easy to update the code without having to rewrite the entire script.

Conclusion

In conclusion, the code submitted by Terrence Gorman looks great. However, there are a few areas where the code could be improved to make it more efficient and scalable. Breaking down the code into functions that take in year as a parameter and implementing a function for demand would make the code more modular, reusable, and flexible. The nutrition and counterfactual code looks very solid, and the use of external data sources a good practice.

Recommendations for Future Development

Based on the code review, here are some recommendations for future development:

Break down the code into functions that take in year as a parameter
Implement a function for demand that takes in different foods as parameters
Continue to use external data sources to provide additional insights and information
Make sure to test the code thoroughly to ensure that it is working correctly

Future Directions

The future directions for this code are to continue to improve and expand the functionality. Some potential future directions include:

Adding more visualizations and analysis to the code
Integrating the code with other data sources and systems
Making the code more user-friendly and easier to use
Continuing to use external data sources to provide additional insights and information

Conclusion

Q: What are some potential benefits of breaking down the code into functions that take in year as a parameter?

A: Breaking down the code into functions that take in year as a parameter would have several benefits. Firstly, it would make the code more modular and easier to maintain. If there are any changes to the data or the analysis, it would be easy to update the code without having to rewrite the entire script. Secondly, it would make the code more reusable. If there are any other years that need to be analyzed, it would be easy to simply call the function with the new year as a parameter.

Q: How would implementing a function for demand make the code more flexible and easier to use?

A: Implementing a function for demand would make the code more flexible and easier to use by allowing users to easily switch between different foods and visualizations without having to rewrite the code. This would make the code more user-friendly and easier to use.

Q: What are some potential benefits of using external data sources in the code?

A: Using external data sources can have several benefits. Firstly, it can provide additional insights and information that may not be available from the internal data sources. Secondly, it can make the code more robust and easier to maintain. If there are any changes to the external data source, it would be easy to update the code without having to rewrite the entire script.

Q: How can the code be made more modular and easier to maintain?

A: The code can be made more modular and easier to maintain by breaking it down into smaller functions that each perform a specific task. This would make it easier to update the code without having to rewrite the entire script.

Q: What are some potential future directions for the code?

A: Some potential future directions for the code include:

Adding more visualizations and analysis to the code
Integrating the code with other data sources and systems
Making the code more user-friendly and easier to use
Continuing to use external data sources to provide additional insights and information

Q: How can the code be made more user-friendly and easier to use?

A: The code can be made more user-friendly and easier to use by implementing a function for demand that takes in different foods as parameters. This would make it easy for users to switch between different foods and visualizations without having to rewrite the code.

Q: What are some potential challenges that may arise when implementing the code?

A: Some potential challenges that may arise when implementing the code include:

Ensuring that the code is working correctly and producing accurate results
Integrating the code with other data sources and systems
Making the code more user-friendly and easier to use
Continuing to use external data sources to provide additional insights and information

Q: How can the code be tested to ensure that it is working correctly?

A: The code can be tested to ensure that it is working correctly by using a variety of testing methods, including unit testing and integration testing. This would help to identify any errors or bugs in the code and that it is producing accurate results.

Q: What are some potential benefits of using a testing framework to test the code?

A: Using a testing framework to test the code can have several benefits, including:

Ensuring that the code is working correctly and producing accurate results
Identifying any errors or bugs in the code
Making it easier to maintain and update the code
Providing a way to test the code in a variety of scenarios and environments

Q: How can the code be maintained and updated over time?

A: The code can be maintained and updated over time by using a variety of methods, including:

Breaking the code down into smaller functions that each perform a specific task
Using a testing framework to test the code
Integrating the code with other data sources and systems
Continuing to use external data sources to provide additional insights and information