submarine_forecast / check_load_data.py
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NEW: Major change and analyze the data to forecast and summary
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import pandas as pd
from utils.excel_loader import load_submarine_forecast_data
data = load_submarine_forecast_data('dataset/submarine_forecast.xlsx')
df = data['load']
print("Load data sample:")
print(df.head(10))
print("\n\nLoad data stats:")
print(f"Min: {df['mw'].min()}")
print(f"Max: {df['mw'].max()}")
print(f"Mean: {df['mw'].mean()}")
# Check for anomalies
print(f"\n\nRows with mw > 1000: {len(df[df['mw'] > 1000])}")
print(f"Rows with mw < 0: {len(df[df['mw'] < 0])}")
if len(df[df['mw'] > 1000]) > 0:
print("\nFirst anomalies (mw > 1000):")
print(df[df['mw'] > 1000].head())
if len(df[df['mw'] < 0]) > 0:
print("\nFirst anomalies (mw < 0):")
print(df[df['mw'] < 0].head())