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import streamlit as st
import sqlite3
import pandas as pd
import streamlit as st
import pygwalker as pyg
import streamlit.components.v1 as components
st.set_page_config(
page_title="Financial Data",
page_icon="📈",
layout="wide",
initial_sidebar_state="expanded",
)
st.title('Financial Data')
st.subheader('This is a BI tool to analyze news sentiment data')
conn = sqlite3.connect('fin_data.db')
c = conn.cursor()
c.execute("""
select * from company_news
""")
rows = c.fetchall()
# Extract column names from the cursor
column_names = [description[0] for description in c.description]
conn.commit()
conn.close()
# Create a DataFrame
df = pd.DataFrame(rows, columns=column_names)
# setup pygwalker configuration: https://github.com/Kanaries/pygwalker, https://docs.kanaries.net/pygwalker/use-pygwalker-with-streamlit.en
pyg_html = pyg.walk(df, dark = 'dark', return_html=True)
components.html(pyg_html, height=1000, scrolling=True)
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