initial commit

.gitignore

@@ -0,0 +1,2 @@
+# Virtual environments
+.venv

README.md

@@ -0,0 +1,68 @@
+---
+title: 🚀 Streamlit Multi-Page Lab
+emoji: 🚀
+colorFrom: purple
+colorTo: blue
+sdk: streamlit
+app_file: app.py
+pinned: false
+---
+
+# 🚀 Streamlit Multi-Page Lab
+
+A comprehensive collection of Streamlit experiments, data dashboards, and AI-powered tools merged into a single multi-page application. This project is designed for rapid prototyping and testing various Streamlit features and open-source templates.
+
+## 🧪 Integrated Demos
+
+1.  **Home**: Interactive Altair charts and selection-enabled dataframes.
+2.  **🌍 Top Stocks**: A visual ranking. Derived from `companiesmarketcap.com` data and logos (provided in CSV). File: `1_us-stock-top-mktcap.py`
+3.  **📈 US Top Stock Peers**: Comparative analysis. Fetches real-time market data using the `yfinance` package. File: `2_us-stock-top-compare.py`
+4.  **🗺️ GDP Dashboard**: Historical GDP analysis. Visualizes pre-saved World Bank data (in CSV). File: `3_global-gdp-compare.py`
+5.  **🤖 Gemini File Q&A**: RAG tool using Gemini 3.1 Flash Lite. File: `4_llm-gemini-rag.py`
+
+## 🏗️ Project Structure
+
+```text
+lab-streamlit-start/
+├── assets/
+│   └── assets-logo/           # Brand logos for the Top Companies demo
+├── data/
+│   ├── data-gdp.csv           # World Bank GDP dataset
+│   └── data-stock-us.csv      # Top companies market cap dataset
+├── pages/                     # Multi-page implementation
+│   ├── 1_us-stock-top-mktcap.py
+│   ├── 2_us-stock-top-compare.py
+│   ├── 3_global-gdp-compare.py
+│   └── 4_llm-gemini-rag.py
+├── requirements.txt           # Project dependencies
+└── app.py        # Main entry point & Landing page
+```
+
+## 🛠️ Setup & Execution
+
+### Prerequisites
+- Python 3.11+
+- [Google AI Studio API Key](https://aistudio.google.com/app/apikey) (for Gemini File Q&A)
+
+### Running Locally
+1. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+2. Run the application:
+   ```bash
+   streamlit run app.py
+   ```
+
+## ⚙️ Configuration
+The project is configured for seamless execution in **GitHub Codespaces**. Check `.devcontainer/devcontainer.json` for pre-configured environment settings.
+
+## 📚 References & Credits
+This lab integrates and adapts features from the following open-source projects:
+- **Top Companies Market Cap**: [bi-cnc/top_companies_market_cap](https://github.com/bi-cnc/top_companies_market_cap)
+- **Stock Peer Analysis**: [streamlit/demo-stockpeers](https://github.com/streamlit/demo-stockpeers)
+- **GDP Dashboard**: [streamlit/GDP-Dashboard](https://github.com/streamlit/GDP-Dashboard)
+- **Gemini File Q&A Source**: Adapted from [streamlit/llm-examples](https://github.com/streamlit/llm-examples) (Original Anthropic version)
+
+---
+*Built with ❤️ using Streamlit, Altair, and Google Gemini.*

app.py

@@ -0,0 +1,209 @@
+# -*- coding: utf-8 -*-
+"""streamlit_altair.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1KiJCGzPr79u2mN7nXBz-smug7tEclhJE
+"""
+#!pip install -q streamlit
+# streamlit and other required libraries should be written in requirements.txt in Github repo
+
+import streamlit as st
+import altair as alt
+import numpy as np
+import pandas as pd
+from vega_datasets import data
+from faker import Faker
+
+# 1. Main Page Config
+st.set_page_config(
+    page_title="Streamlit Multi-Page Demo",
+    page_icon="🚀",
+    layout="wide",
+    initial_sidebar_state="expanded",
+)
+
+# Sidebar Navigation Hint
+st.sidebar.success("느좋 데이러 싸이언스")
+
+# Landing Page Content (Kept as per user request for markdown additions)
+st.title("🚀 Streamlit Multi-Page Lab")
+st.markdown("""
+Welcome to your integrated Streamlit workspace! This project combines multiple quickstart templates and interactive demos into a single multi-page application.
+
+### 🧪 Available Demos:
+1.  **Home (This page)**: Current Altair and Interactive Dataframe demo.
+2.  **🌍 [Top Stocks](./us-stock-top-mktcap)**: Ranking of the world's largest companies by market cap with logos.
+3.  **📈 [US Top Stock Peers](./us-stock-top-compare)**: Comparative analysis of stock market peers using Yahoo Finance.
+4.  **🗺️ [GDP Dashboard](./global-gdp-compare)**: Global GDP analysis from World Bank data.
+5.  **🤖 [Gemini File Q&A](./llm-gemini-rag)**: Document answering using Google Gemini (PDF/TXT/MD support).
+
+---
+""")
+
+@st.cache_data # Streamlit will only download the data once since the data will be saved in a cache
+def get_data():
+    source = data.stocks()
+    source = source[source.date.gt("2006-01-01")]
+    return source
+
+
+def get_profile_dataset(number_of_items: int = 20, seed: int = 0) -> pd.DataFrame:
+    new_data = []
+
+    fake = Faker()
+    np.random.seed(seed)
+    Faker.seed(seed)
+
+    for i in range(number_of_items):
+        profile = fake.profile()
+        new_data.append(
+            {
+                "name": profile["name"],
+                "daily_activity": np.random.rand(25),
+                "activity": np.random.randint(2, 90, size=12),
+            }
+        )
+
+    profile_df = pd.DataFrame(new_data)
+    return profile_df
+
+
+#######################################
+st.title("Altair") 
+stock_data = get_data()
+
+# Events in altair
+# Note: selection_single is deprecated in Altair 5+, but we use selection_point for compatibility
+# while maintaining the original logic functionality.
+hover = alt.selection_point(
+    fields=["date"],
+    nearest=True,
+    on="mouseover",
+    empty=False,
+)
+
+lines = (
+    alt.Chart(stock_data, title="Evolution of stock prices")
+    .mark_line()
+    .encode(
+        x="date",
+        y="price",
+        color="symbol",
+    )
+)
+
+points = lines.transform_filter(hover).mark_circle(size=65)
+
+tooltips = (
+    alt.Chart(stock_data)
+    .mark_rule()
+    .encode(
+        x="yearmonthdate(date)",
+        y="price",
+        opacity=alt.condition(hover, alt.value(0.3), alt.value(0)),
+        tooltip=[
+            alt.Tooltip("date", title="Date"),
+            alt.Tooltip("price", title="Price (USD)"),
+        ],
+    )
+    .add_params(hover)
+)
+
+# Combine the lines, points, and tooltips into a single chart.
+data_layer = lines + points + tooltips
+
+# Build the annotation layer
+ANNOTATIONS = [
+    ("Sep 01, 2007", 450, "🙂", "Something's going well for GOOG & AAPL."),
+    ("Nov 01, 2008", 220, "🙂", "The market is recovering."),
+    ("Dec 01, 2007", 750, "😱", "Something's going wrong for GOOG & AAPL."),
+    ("Dec 01, 2009", 680, "😱", "A hiccup for GOOG."),
+]
+annotations_df = pd.DataFrame(
+    ANNOTATIONS, columns=["date", "price", "marker", "description"]
+)
+annotations_df.date = pd.to_datetime(annotations_df.date)
+
+annotation_layer = (
+    alt.Chart(annotations_df)
+    .mark_text(size=20, dx=-10, dy=0, align="left")
+    .encode(x="date:T", y=alt.Y("price:Q"), text="marker", tooltip="description")
+)
+
+# Define the combined chart.
+combined_chart = data_layer + annotation_layer
+# enable panning and zooming
+# combined_chart = (data_layer + annotation_layer).interactive()
+
+# Display the chart in Streamlit.
+st.altair_chart(combined_chart, use_container_width=True)
+
+
+#######################################
+st.title("Get dataframe row-selections")
+
+column_configuration = {
+    "name": st.column_config.TextColumn(
+        "Name", help="The name of the user", max_chars=100, width="medium"
+    ),
+    "activity": st.column_config.LineChartColumn(
+        "Activity (1 year)",
+        help="The user's activity over the last 1 year",
+        width="large",
+        y_min=0,
+        y_max=100,
+    ),
+    "daily_activity": st.column_config.BarChartColumn(
+        "Activity (daily)",
+        help="The user's activity in the last 25 days",
+        width="medium",
+        y_min=0,
+        y_max=1,
+    ),
+}
+
+select, compare = st.tabs(["Select members", "Compare selected"])
+
+with select:
+    st.header("All members")
+
+    df = get_profile_dataset()
+
+    event = st.dataframe(
+        df,
+        column_config=column_configuration,
+        use_container_width=True,
+        hide_index=True,
+        on_select="rerun",
+        selection_mode="multi-row",
+    )
+
+    st.header("Selected members")
+    people = event.selection.rows
+    filtered_df = df.iloc[people]
+    st.dataframe(
+        filtered_df,
+        column_config=column_configuration,
+        use_container_width=True,
+    )
+
+with compare:
+    activity_df = {}
+    for person in people:
+        activity_df[df.iloc[person]["name"]] = df.iloc[person]["activity"]
+    activity_df = pd.DataFrame(activity_df)
+
+    daily_activity_df = {}
+    for person in people:
+        daily_activity_df[df.iloc[person]["name"]] = df.iloc[person]["daily_activity"]
+    daily_activity_df = pd.DataFrame(daily_activity_df)
+
+    if len(people) > 0:
+        st.header("Daily activity comparison")
+        st.bar_chart(daily_activity_df)
+        st.header("Yearly activity comparison")
+        st.line_chart(activity_df)
+    else:
+        st.markdown("No members selected.")