Aprende Generating Automated Reports | Automating Government Workflows with Python

Automated report generation is transforming how government analysts approach data-driven decision-making. By using Python to create summary reports, you can streamline the process of compiling, analyzing, and presenting key findings, reducing manual effort and minimizing the risk of human error. Automated reports ensure that decision-makers receive timely, accurate, and consistent information, allowing them to focus on interpreting results and making informed choices. This approach not only saves valuable time but also improves the overall quality and professionalism of government workflows.


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import pandas as pd

def print_summary_report(df, column):
    total = df[column].sum()
    average = df[column].mean()
    minimum = df[column].min()
    maximum = df[column].max()
    print("Summary Report")
    print("-------------------")
    print(f"Total {column}: {total}")
    print(f"Average {column}: {average:.2f}")
    print(f"Minimum {column}: {minimum}")
    print(f"Maximum {column}: {maximum}")

# Example usage:
data = {'Department': ['A', 'B', 'C', 'D'],
        'Expenditure': [12000, 15000, 8000, 20000]}
df = pd.DataFrame(data)
print_summary_report(df, 'Expenditure')

When creating automated reports, the way you format the output is crucial for clarity and professionalism. Well-organized and readable reports help decision-makers quickly understand the key points, spot trends, and identify areas that need attention. Consistent use of headers, spacing, and number formatting makes your reports easier to interpret and increases their impact. By presenting data in a clear and concise manner, you ensure that important information stands out and supports effective decision-making.


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def print_summary_report_with_flags(df, column, threshold):
    total = df[column].sum()
    average = df[column].mean()
    minimum = df[column].min()
    maximum = df[column].max()
    print("Summary Report with Flags")
    print("-------------------------")
    print(f"Total {column}: {total}")
    print(f"Average {column}: {average:.2f}")
    print(f"Minimum {column}: {minimum}")
    print(f"Maximum {column}: {maximum}")
    print("\nDepartments exceeding threshold:")
    for idx, row in df.iterrows():
        value = row[column]
        if value > threshold:
            print(f"  {row['Department']}: {value} <-- Above {threshold}")

# Example usage:
print_summary_report_with_flags(df, 'Expenditure', 14000)

¿Todo estuvo claro?

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Sección 3. Capítulo 2

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              12345678910111213141516171819
            
import pandas as pd

def print_summary_report(df, column):
    total = df[column].sum()
    average = df[column].mean()
    minimum = df[column].min()
    maximum = df[column].max()
    print("Summary Report")
    print("-------------------")
    print(f"Total {column}: {total}")
    print(f"Average {column}: {average:.2f}")
    print(f"Minimum {column}: {minimum}")
    print(f"Maximum {column}: {maximum}")

# Example usage:
data = {'Department': ['A', 'B', 'C', 'D'],
        'Expenditure': [12000, 15000, 8000, 20000]}
df = pd.DataFrame(data)
print_summary_report(df, 'Expenditure')


              12345678910111213141516171819
            
def print_summary_report_with_flags(df, column, threshold):
    total = df[column].sum()
    average = df[column].mean()
    minimum = df[column].min()
    maximum = df[column].max()
    print("Summary Report with Flags")
    print("-------------------------")
    print(f"Total {column}: {total}")
    print(f"Average {column}: {average:.2f}")
    print(f"Minimum {column}: {minimum}")
    print(f"Maximum {column}: {maximum}")
    print("\nDepartments exceeding threshold:")
    for idx, row in df.iterrows():
        value = row[column]
        if value > threshold:
            print(f"  {row['Department']}: {value} <-- Above {threshold}")

# Example usage:
print_summary_report_with_flags(df, 'Expenditure', 14000)

¿Todo estuvo claro?

¡Gracias por tus comentarios!

Sección 3. Capítulo 2

Generating Automated Reports

1. Why is formatting important in automated reports?

2. How can conditional formatting help highlight important findings?

3. What are the risks of relying solely on automated reports?

Generating Automated Reports

1. Why is formatting important in automated reports?

2. How can conditional formatting help highlight important findings?

3. What are the risks of relying solely on automated reports?