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import streamlit as st
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import pandas as pd
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import seaborn as sns
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import matplotlib.pyplot as plt
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import streamlit as st
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import pandas as pd
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import numpy as np
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df = pd.read_csv(r"C:\Users\91879\Downloads\data.csv")
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st.title("📊 Exploratory Data Analysis")
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df.fillna(df.mean(), inplace=True)
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st.subheader("📄 View Dataset Preview")
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if st.button("🔍 Show Dataset Head"):
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st.dataframe(df.head())
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features = [
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'Brake_Pressure', 'Pad_Wear_Level', 'ABS_Status',
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'Wheel_Speed_FL', 'Wheel_Speed_FR',
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'Wheel_Speed_RL', 'Wheel_Speed_RR',
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'Fluid_Temperature', 'Pedal_Position'
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]
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st.subheader("⚠️ Fault Distribution")
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fault_counts = df['Fault'].value_counts()
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st.bar_chart(fault_counts)
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st.write(df['Fault'].value_counts(normalize=True) * 100)
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st.subheader("📊 Correlation Heatmap")
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corr = df.corr()
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fig, ax = plt.subplots(figsize=(10, 8))
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sns.heatmap(corr, annot=True, fmt=".2f", cmap="coolwarm", ax=ax)
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st.pyplot(fig)
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