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Enhance API with data loading functionality and update README.

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- Added `/load-data` endpoint to load transaction data from either a database or a CSV file.
- Updated `SalaryAnalyticsPipeline` and `DataLoader` to support loading from CSV.
- Implemented data validation and error handling for loading processes.
- Revised README to include new data loading instructions and workflow steps.
- Added checks to ensure data is loaded before running analysis endpoints.
This commit is contained in:
Joshua Salako
2025-05-01 22:57:55 +01:00
parent 7e7094f0fd
commit 8acfb436f3
12 changed files with 205 additions and 29 deletions
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salary_analytics/salary_earner_analyzer.py
+3 -4
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@@ -83,11 +83,10 @@ class SalaryEarnerAnalyzer:
def analyze_salary_earners(self, final_df):
"""Analyze salary earners and identify high earners."""
high_earners = final_df[final_df['estimated_next_amount'] >= MODEL_CONFIG['high_earner_threshold']]
high_earners['least_inflow_6m'] = high_earners['least_inflow_6m']
count_high = len(high_earners)
high_earners = final_df[final_df['estimated_next_amount'] >= MODEL_CONFIG['high_earner_threshold']].copy()
high_earner_details = high_earners[['accountid', 'least_inflow_6m']].reset_index(drop=True)
count_high = len(high_earners)
return high_earner_details, count_high
def generate_reports(self):