import os import pandas as pd import streamlit as st import base64 import json # navigate to url def nav_to(url): nav_script = """ """ % (url) st.write(nav_script, unsafe_allow_html=True) @st.cache_data def df_to_html(df): df = df.fillna("") # Define table styling styles = [ {'selector': 'tr', 'props': [('border', 'none')]}, # Hide row borders {'selector': 'td, th', 'props': [('border', 'none'), ("text-align", "center"), ('font-size', 'smaller')]}, # Remove cell borders, reduce font size {'selector': 'tr:hover', 'props': [('background-color', '#f5f5f5')]}, {'selector': 'a:hover', 'props': [('color', 'darkblue')]}, {'selector': 'table', 'props': [('border-collapse', 'collapse'), ('border', 'none'), ('border-bottom', '1px solid black'), ('width', '50%')]}, # Set table width to 50% {'selector': 'thead', 'props': [('border', 'none')]}, # Hide header border {'selector': 'tbody td', 'props': [('border-left', 'none'), ('border-right', 'none')]}, {'selector': 'tr:not(:first-child) td', 'props': [('border-left', 'none'), ('border-right', 'none'), ('border-top', 'none')]}, {'selector': 'table', 'props': [('table-layout', 'fixed')]}, # Prevent overflow ] # Apply table styles and convert DataFrame to HTML styled_html = df.style.hide(axis="index").set_table_styles(styles).to_html(escape=False, index=False, bold_rows=True, justify='center').replace('', '') return styled_html @st.cache_data def render_svg(svg): """Renders the given svg string.""" b64 = base64.b64encode(svg.encode("utf-8")).decode("utf-8") html = rf'

' c = st.container() c.write(html, unsafe_allow_html=True) @st.cache_resource def combine_json_files(folder_path): combined_data = {} # Iterate through each file in the folder for filename in os.listdir(folder_path): file_path = os.path.join(folder_path, filename) # Check if the file is a JSON file if filename.endswith('.json'): with open(file_path, 'r') as file: # Load JSON data from the file data = {filename.replace('.json', ''): json.load(file)} # Merge the loaded data into the combined_data dictionary combined_data.update(data) return combined_data