Apprendre Automating Repetitive Calculations | Automating Government Workflows with Python

Automating repetitive calculations is a key way to increase efficiency in government workflows. By using Python to handle common mathematical tasks, you can save time, reduce manual errors, and ensure consistency across your analyses. Automation allows you to focus on more complex analytical work, rather than spending hours on routine number crunching.


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def calculate_total_cost(expenses):
    """
    Calculate the total cost of a program given a list of expenses.

    Args:
        expenses (list of float): List containing individual expense amounts.

    Returns:
        float: The sum of all expenses.
    """
    return sum(expenses)

# Example usage
program_expenses = [1200.50, 3500.75, 800.00, 450.25]
total = calculate_total_cost(program_expenses)
print("Total program cost:", total)

When you write functions for calculations, you can generalize them for use with different datasets and scenarios. This means you do not need to rewrite code for every new project—just reuse your existing functions by passing in new data. Well-designed functions make your work more reliable and easier to maintain, especially when working with large or frequently updated datasets.


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def calculate_per_capita_cost(total_cost, population):
    """
    Automate calculation of per capita costs.

    Args:
        total_cost (float): The total cost of a program or service.
        population (int): The number of people served.

    Returns:
        float: The per capita cost.
    """
    if population == 0:
        return 0.0  # Avoid division by zero
    return total_cost / population

# Example usage
total_cost = 95000
population = 5000
per_capita = calculate_per_capita_cost(total_cost, population)
print("Per capita cost:", per_capita)

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Section 3. Chapitre 1

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Suggested prompts:

Can you explain how to adapt these functions for other types of calculations?

What are some best practices for writing reusable calculation functions?

Can you provide more examples of automating calculations in government workflows?

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              12345678910111213141516
            
def calculate_total_cost(expenses):
    """
    Calculate the total cost of a program given a list of expenses.

    Args:
        expenses (list of float): List containing individual expense amounts.

    Returns:
        float: The sum of all expenses.
    """
    return sum(expenses)

# Example usage
program_expenses = [1200.50, 3500.75, 800.00, 450.25]
total = calculate_total_cost(program_expenses)
print("Total program cost:", total)


              1234567891011121314151617181920
            
def calculate_per_capita_cost(total_cost, population):
    """
    Automate calculation of per capita costs.

    Args:
        total_cost (float): The total cost of a program or service.
        population (int): The number of people served.

    Returns:
        float: The per capita cost.
    """
    if population == 0:
        return 0.0  # Avoid division by zero
    return total_cost / population

# Example usage
total_cost = 95000
population = 5000
per_capita = calculate_per_capita_cost(total_cost, population)
print("Per capita cost:", per_capita)

Tout était clair ?

Merci pour vos commentaires !

Section 3. Chapitre 1

Automating Repetitive Calculations

1. What is the main advantage of automating calculations with functions?

2. How can automation improve accuracy in government reporting?

3. What should you consider when designing a reusable calculation function?

Automating Repetitive Calculations

1. What is the main advantage of automating calculations with functions?

2. How can automation improve accuracy in government reporting?

3. What should you consider when designing a reusable calculation function?