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import streamlit as st
import plotly.graph_objects as go
from src.utils import fetch_financials, clean_financials
def plot_income(income_df, ticker_symbol):
fig = go.Figure()
# List of metrics we want to plot — change as per availability
metrics = [
"Total Revenue",
"Net Income Available to Common Shares"
]
for m in metrics:
if m in income_df.columns:
fig.add_trace(go.Bar(
x=income_df.index,
y=income_df[m] / 1e9, # convert to billions
name=m
))
fig.update_layout(
title=f"{ticker_symbol} Income Statement",
xaxis_title="Date",
yaxis_title="Value (in billions)",
barmode='group'
)
return fig
def plot_cashflow(cash_df, ticker_symbol):
fig = go.Figure()
metrics = [
"Total Cash From Operating Activities",
"Capital Expenditures",
]
for m in metrics:
if m in cash_df.columns:
vals = cash_df[m]
# If CapEx, often negative -> make positive for bar
if "Capital Expenditures" in m:
vals = -vals
fig.add_trace(go.Bar(
x=cash_df.index,
y=vals / 1e9,
name=m
))
fig.update_layout(
title=f"{ticker_symbol} Cash Flow Statement",
xaxis_title="Date",
yaxis_title="Value (in billions)",
barmode='group'
)
return fig
def main():
st.title("Financial Dashboard")
ticker_symbol = st.text_input("Ticker Symbol", "AAPL")
if st.button("Refresh Data"):
with st.spinner("Fetching data..."):
income, cash = fetch_financials(ticker_symbol, freq="annual")
if income.empty and cash.empty:
st.error("No financial data returned. Check ticker or try again.")
return
income_clean = clean_financials(income)
cash_clean = clean_financials(cash)
st.subheader("Income Statement")
fig_income = plot_income(income_clean, ticker_symbol)
st.plotly_chart(fig_income, use_container_width=True)
st.subheader("Cash Flow")
fig_cash = plot_cashflow(cash_clean, ticker_symbol)
st.plotly_chart(fig_cash, use_container_width=True)
st.write("### Raw Data — Income Statement")
st.dataframe(income_clean)
st.write("### Raw Data — Cash Flow")
st.dataframe(cash_clean)
if __name__ == "__main__":
main()
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