app.py

# Usage:
# streamlit run app.py

import streamlit as st

from utils import (
    get_final_df,
    show_correlation_tab,
    show_description_tab,
    show_predictive_tab,
    show_relationship_tab,
)

# Make page content wider
st.set_page_config(
    page_title="ESG x Market Performance",
    page_icon=":earth_americas:",
    layout="wide",
)

# Allow long selection columns to scroll
st.markdown(
    """
      <style>
          [data-testid="column"] > div:nth-child(1) > div:nth-child(1) > div:nth-child(2) > div {
          overflow: auto;
          max-height: 90vh;
        }
      </style>
    """,
    unsafe_allow_html=True,
)

# Hide the streamlit backend features in serve
st.markdown(
    """
      <style>
        #MainMenu {visibility: hidden;}
        header {visibility: hidden;}
        footer {visibility: hidden;}
      </style>
    """,
    unsafe_allow_html=True,
)

# Set the title
st.title("ESG x Market Performance :earth_americas:")
st.markdown("""Nathan Alakija, Nicole ElChaar, Mason Otley, Xiaozhe Zhang""")

# Use three main tabs: Description, Relationship Model, and Predictive Model
tab_list = [
    "Description",
    "ESG Metric Details",
    "Relationship Model",
    "Predictive Model",
]
description_tab, correlation_tab, relationship_tab, predictive_tab = st.tabs(tab_list)

# Store the final df for manipulation across all tabs
final_df = get_final_df()

# Description page
with description_tab:
    show_description_tab()

# Show ESG score details
with correlation_tab:
    show_correlation_tab(final_df)

# Relationship Model page
with relationship_tab:
    show_relationship_tab(final_df)

# Predictive Model page
with predictive_tab:
    show_predictive_tab(final_df)