salakojoshua1234_gmail.com
8acfb436f3
- 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.
64 lines
2.2 KiB
Python
64 lines
2.2 KiB
Python
"""
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Consistent amount transaction analysis module.
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"""
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import pandas as pd
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from .config import MODEL_CONFIG
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class ConsistentAmountAnalyzer:
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def __init__(self, df):
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self.df = df
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self.const_df = None
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def calculate_coefficient_of_variation(self, group):
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"""Calculate coefficient of variation for a group of transactions."""
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amounts = group[group['initiated_by'] == 'C']['amount']
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mean = amounts.mean()
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std = amounts.std(ddof=0)
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if mean == 0:
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return float('nan')
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return std / mean
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def flag_consistent_amounts(self, group, cv_threshold=None):
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"""Flag accounts with low variance in transaction amounts."""
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if cv_threshold is None:
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cv_threshold = MODEL_CONFIG['cv_threshold']
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filtered_group = group[group['initiated_by'] == 'C']
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cv = self.calculate_coefficient_of_variation(filtered_group)
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is_consistent = cv <= cv_threshold if not pd.isna(cv) else False
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return pd.Series(
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[is_consistent] * len(group),
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index=group.index,
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name='is_consistent_amount'
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)
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def identify_consistent_amount_accounts(self, cv_threshold=None):
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"""Identify accounts with consistent transaction amounts."""
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if cv_threshold is None:
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cv_threshold = MODEL_CONFIG['cv_threshold']
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# Create a copy of the original DataFrame
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self.const_df = self.df.copy()
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# Calculate consistent amount flags
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consistent_flags = self.const_df.groupby('accountid').apply(
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lambda group: self.flag_consistent_amounts(group, cv_threshold)
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).reset_index(level=0, drop=True)
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# Add the flags to the original DataFrame
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self.const_df['is_consistent_amount'] = consistent_flags
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return self.const_df
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def get_consistent_amount_data(self):
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"""Get transactions identified as having consistent amounts."""
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if self.const_df is None:
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self.identify_consistent_amount_accounts()
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return self.const_df[
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(self.const_df['is_consistent_amount']) &
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(self.const_df['initiated_by'] == 'C')
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] |