diff --git a/frontend/main.py b/frontend/main.py
index b51c053..79b9a64 100644
--- a/frontend/main.py
+++ b/frontend/main.py
@@ -1,10 +1,64 @@
 import pandas as pd
 import streamlit as st
+import matplotlib.pyplot as plt
+import seaborn as sns
+from pandas.api.types import is_numeric_dtype
 
-st.title("Hello world!")
+st.set_page_config(
+    page_title="Project Miner",
+    layout="wide"
+)
 
-uploaded_file = st.file_uploader("Choose a file")
-if uploaded_file is not None:
-    df = pd.read_csv(uploaded_file)
-    st.write(df.head(10))
-    st.write(df.tail(10))
+### Exploration
+uploaded_file = st.file_uploader("Upload your CSV file", type=["csv"])
+
+if uploaded_file:
+    data = pd.read_csv(uploaded_file)
+    st.success("File loaded successfully!")
+
+    st.header("Data Preview")
+    
+    st.subheader("First 5 Rows")
+    st.write(data.head())
+    
+    st.subheader("Last 5 Rows")
+    st.write(data.tail())
+    
+    st.header("Data Summary")
+    
+    st.subheader("Basic Information")
+    col1, col2 = st.columns(2)
+    col1.metric("Number of Rows", data.shape[0])
+    col2.metric("Number of Columns", data.shape[1])
+    
+    st.write(f"Column Names: {list(data.columns)}")
+    
+    st.subheader("Missing Values by Column")
+    missing_values = data.isnull().sum()
+    st.write(missing_values)
+    
+    st.subheader("Statistical Summary")
+    st.write(data.describe())
+    
+    ### Visualization
+
+    st.header("Data Visualization")
+
+    st.subheader("Histogram")
+    column_to_plot = st.selectbox("Select Column for Histogram", data.columns)
+    if column_to_plot:
+        fig, ax = plt.subplots()
+        ax.hist(data[column_to_plot].dropna(), bins=20, edgecolor='k')
+        ax.set_title(f'Histogram of {column_to_plot}')
+        ax.set_xlabel(column_to_plot)
+        ax.set_ylabel('Frequency')
+        st.pyplot(fig)
+    
+    st.subheader("Boxplot")
+    dataNumeric = data.select_dtypes(include='number')
+    column_to_plot = st.selectbox("Select Column for Boxplot", dataNumeric.columns)
+    if column_to_plot:
+        fig, ax = plt.subplots()
+        sns.boxplot(data=data, x=column_to_plot, ax=ax)
+        ax.set_title(f'Boxplot of {column_to_plot}')
+        st.pyplot(fig)
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