Create app.py

app.py

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+
+import streamlit as st
+import pandas as pd
+from pandas_profiling import ProfileReport
+import base64
+
+st.set_page_config(page_title="Data Browser", page_icon=":bar_chart:")
+
+st.title("Data Browser")
+
+# File upload
+st.header("Upload your data file")
+uploaded_file = st.file_uploader("", type=["csv", "xlsx"])
+
+if uploaded_file is not None:
+    # Determine file type
+    file_ext = uploaded_file.name.split(".")[-1]
+    if file_ext == "csv":
+        df = pd.read_csv(uploaded_file)
+    elif file_ext in ["xls", "xlsx"]:
+        df = pd.read_excel(uploaded_file)
+
+    # Display basic info
+    st.write(f"Number of rows: {df.shape[0]}")
+    st.write(f"Number of columns: {df.shape[1]}")
+    st.write("Sample data:")
+    st.dataframe(df.head())
+
+    # Generate pandas profiling report
+    report = ProfileReport(df, explorative=True)
+    st.header("Data profiling")
+    st.write("Data distribution:")
+    st_profile_report(report)
+
+# Download link for example data
+example_csv = """name,age,income
+Alice,25,50000
+Bob,30,70000
+Charlie,35,90000"""
+csv_filename = "example.csv"
+b64 = base64.b64encode(example_csv.encode()).decode()
+href = f'<a href="data:file/csv;base64,{b64}" download="{csv_filename}">Download example data</a>'
+st.markdown(href, unsafe_allow_html=True)