Find Top-Funded Villages and Their Top Projects

Question

The question asks the candidate to identify the top-funded villages and their corresponding top projects using SQL or Python for data manipulation.

Codemia · Accepted Answer

To find the top-funded villages and their top projects, I would start by determining the data structure and the relevant tables involved. I would focus on a table containing village funding information and another that lists projects associated with those villages. The goal is to aggregate the funding data and rank the projects accordingly.

Assuming we have two tables: `villages` (with columns `village_id`, `village_name`, `funding_amount`) and `projects` (with columns `project_id`, `village_id`, `project_name`, `project_budget`), I would write the following SQL query:

```sql
SELECT v.village_name, p.project_name, v.funding_amount
FROM villages v
JOIN projects p ON v.village_id = p.village_id
WHERE v.funding_amount IS NOT NULL
ORDER BY v.funding_amount DESC, p.project_budget DESC
LIMIT 10;
```
This query retrieves the top 10 funded villages along with their projects, ordered by funding amount and project budget.

The time complexity of this query is O(n log n) due to the sorting operation, where n is the number of records in the villages and projects tables. The join operation is O(n) in the average case, making this approach efficient for reasonably sized datasets.

If using Python, I would utilize the pandas library to manipulate the data. Here’s a code snippet:

```python
import pandas as pd

# Load data
villages = pd.read_csv('villages.csv')
projects = pd.read_csv('projects.csv')

# Merge dataframes
merged = pd.merge(villages, projects, on='village_id')

# Filter and sort
result = merged[merged['funding_amount'].notnull()]
result = result.sort_values(by=['funding_amount', 'project_budget'], ascending=False)

# Get top 10
top_funded = result.head(10)[['village_name', 'project_name', 'funding_amount']]
print(top_funded)
```
This code achieves the same result using Python, showcasing versatility in handling data.

When performing this analysis, it's crucial to consider potential issues such as missing data or outliers in funding amounts. Additionally, understanding the context of the data, such as the time frame for funding, can provide deeper insights into the projects and their relevance to the villages.

Find Top-Funded Villages and Their Top Projects

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