Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import matplotlib.pyplot as plt
+
+st.set_page_config(page_title="Data Visualization App", page_icon="📊", layout="wide")
+
+st.title("📊 Interactive Data Visualization App")
+
+uploaded_file = st.file_uploader("Upload a CSV file", type=["csv"])
+
+if uploaded_file is not None:
+    df = pd.read_csv(uploaded_file)
+    st.subheader("🔍 Data Preview")
+    st.dataframe(df.head())
+
+    st.subheader("📈 Data Summary")
+    st.write(df.describe())
+
+    st.subheader("🎨 Visualization Options")
+    columns = df.columns.tolist()
+
+    chart_type = st.selectbox("Select chart type", ["Line", "Bar", "Scatter", "Histogram", "Pie"])
+    x_axis = st.selectbox("Select X-axis", columns)
+    y_axis = st.selectbox("Select Y-axis", columns)
+
+    fig, ax = plt.subplots(figsize=(8, 5))
+
+    if chart_type == "Line":
+        ax.plot(df[x_axis], df[y_axis])
+    elif chart_type == "Bar":
+        ax.bar(df[x_axis], df[y_axis])
+    elif chart_type == "Scatter":
+        ax.scatter(df[x_axis], df[y_axis])
+    elif chart_type == "Histogram":
+        ax.hist(df[y_axis], bins=20)
+    elif chart_type == "Pie":
+        df.groupby(x_axis)[y_axis].sum().plot(kind="pie", autopct="%1.1f%%", ax=ax)
+
+    ax.set_xlabel(x_axis)
+    ax.set_ylabel(y_axis)
+    ax.set_title(f"{chart_type} Chart of {y_axis} vs {x_axis}")
+    st.pyplot(fig)
+else:
+    st.info("👆 Upload a CSV file to begin exploring your data.")