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Streamlit_code / utils /preprocessing.py

Create utils/preprocessing.py

60daf05 almost 3 years ago

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# utils/preprocessing.py
import pandas as pd
from sklearn.preprocessing import StandardScaler

def preprocess_data_for_streamlit(data_path):
    df = pd.read_csv(data_path)
    df = feature_engineering(df)  # Assuming feature_engineering is defined
    X = df.drop('label', axis=1)
    scaler = StandardScaler()
    X_scaled = scaler.fit_transform(X)
    return df, X_scaled

	# utils/preprocessing.py
	import pandas as pd
	from sklearn.preprocessing import StandardScaler

	def preprocess_data_for_streamlit(data_path):
	df = pd.read_csv(data_path)
	df = feature_engineering(df) # Assuming feature_engineering is defined
	X = df.drop('label', axis=1)
	scaler = StandardScaler()
	X_scaled = scaler.fit_transform(X)
	return df, X_scaled