Compare departmental workload, cost, closure performance, and service quality.
Caso práctico progresivo para transformar datos municipales sucios en información confiable, analizable y útil para decisiones.
Compare departmental workload, cost, closure performance, and service quality.
Este caso continúa el flujo real de trabajo con solicitudes de servicios municipales y documenta cada transformación de forma trazable.
Results can vary because the source dataset was generated synthetically and randomly. Run the code to obtain the exact values from your local file.
Los resultados pueden variar porque el dataset de origen fue generado de forma sintética y aleatoria. Ejecuta el código para obtener los valores exactos de tu archivo local.
import pandas as pd
from pathlib import Path
base = Path.home() / "Documents" / "Pandas_Use_Cases"
input_file = base / "city_service_requests_clean_master.csv"
output_file = base / "analysis_by_department.csv"
df = pd.read_csv(input_file)Departmental analysis uses standardized department names.
df["Is_Closed"] = df["Status"].isin(["Closed", "Resolved"])Every request is classified as completed or not completed.
department_summary = (
df.groupby("Department", dropna=False)
.agg(
Request_Count=("Request_ID", "count"),
Closed_Requests=("Is_Closed", "sum"),
Average_Resolution_Days=("Resolution_Days", "mean"),
Total_Estimated_Cost=("Estimated_Cost", "sum"),
Average_Satisfaction=("Satisfaction_Score", "mean")
)
.round(2)
)
department_summary["Closure_Rate_Percent"] = (
department_summary["Closed_Requests"]
/ department_summary["Request_Count"]
* 100
).round(2)Core departmental workload and performance indicators are calculated.
department_summary["Workload_Rank"] = (
department_summary["Request_Count"]
.rank(method="dense", ascending=False)
.astype(int)
)
department_summary = department_summary.sort_values(
"Request_Count",
ascending=False
)
print(department_summary.to_string())Departments can be compared by workload and closure performance.
department_summary.to_csv(output_file, encoding="utf-8-sig")
print(f"Saved: {output_file}")A department KPI table is produced for management review.
The output of this module becomes the controlled input for the next stage of the 20-case Pandas workflow.
La salida de este módulo se convierte en la entrada controlada para la siguiente etapa del flujo de 20 casos de Pandas.
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Recursos comunitarios enfocados en oficios, habilidades, oportunidades locales y desarrollo profesional práctico.
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