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"""Financial statements — Income Statement, Balance Sheet, Cash Flow."""
import numpy as np
import pandas as pd
import streamlit as st
from services.data_service import get_income_statement, get_balance_sheet, get_cash_flow
from utils.formatters import fmt_large
# Rows where a decline is actually good (e.g. costs, expenses)
_INVERSE_ROWS = {
"cost of revenue", "cost of goods sold", "operating expenses",
"selling general administrative", "research development",
"interest expense", "income tax expense", "total expenses",
"reconciled cost of revenue",
}
def _is_inverse(label: str) -> bool:
return label.strip().lower() in _INVERSE_ROWS
def _fmt_cell(value) -> str:
try:
v = float(value)
except (TypeError, ValueError):
return "—"
return fmt_large(v)
def _yoy_raw(current, previous):
"""Return raw float YoY % change, or None."""
try:
c, p = float(current), float(previous)
if p == 0:
return None
return (c - p) / abs(p) * 100
except (TypeError, ValueError):
return None
def _yoy_str(pct) -> str:
if pct is None:
return "—"
arrow = "▲" if pct >= 0 else "▼"
return f"{arrow} {abs(pct):.1f}%"
def _build_statement(df: pd.DataFrame):
"""
Returns (display_df, color_df).
display_df: formatted string DataFrame for rendering.
color_df: same shape, cells are 'green', 'red', or '' for styling.
"""
df = df.copy()
df.columns = [str(c)[:10] for c in df.columns]
cols = list(df.columns)
display = pd.DataFrame(index=df.index)
colors = pd.DataFrame(index=df.index)
for i, col in enumerate(cols):
display[col] = df[col].apply(_fmt_cell)
colors[col] = ""
if i + 1 < len(cols):
prev_col = cols[i + 1]
yoy_label = f"YoY {col[:4]}"
raw_yoy = df.apply(lambda row: _yoy_raw(row[col], row[prev_col]), axis=1)
display[yoy_label] = raw_yoy.apply(_yoy_str)
def cell_color(row_label, pct):
if pct is None:
return ""
inverse = _is_inverse(row_label)
positive_change = pct >= 0
good = positive_change if not inverse else not positive_change
return "green" if good else "red"
colors[yoy_label] = pd.Series(
[cell_color(idx, pct) for idx, pct in zip(df.index, raw_yoy)],
index=df.index,
)
return display, colors
def _style(display: pd.DataFrame, colors: pd.DataFrame):
GREEN_BG = "background-color: rgba(46, 204, 113, 0.18); color: #7ce3a1;"
RED_BG = "background-color: rgba(231, 76, 60, 0.18); color: #ff8a8a;"
def apply_colors(row):
return [
GREEN_BG if colors.loc[row.name, col] == "green"
else RED_BG if colors.loc[row.name, col] == "red"
else ""
for col in display.columns
]
return display.style.apply(apply_colors, axis=1)
def render_financials(ticker: str):
col1, col2 = st.columns([1, 3])
with col1:
freq = st.radio("Frequency", ["Annual", "Quarterly"], horizontal=False)
quarterly = freq == "Quarterly"
tab_income, tab_balance, tab_cashflow = st.tabs(
["Income Statement", "Balance Sheet", "Cash Flow"]
)
with tab_income:
df = get_income_statement(ticker, quarterly=quarterly)
if df.empty:
st.info("Income statement data unavailable.")
else:
display, colors = _build_statement(df)
st.dataframe(_style(display, colors), use_container_width=True)
st.download_button(
"Download CSV",
df.to_csv().encode(),
file_name=f"{ticker.upper()}_income_{'quarterly' if quarterly else 'annual'}.csv",
mime="text/csv",
key=f"dl_income_{ticker}_{quarterly}",
)
with tab_balance:
df = get_balance_sheet(ticker, quarterly=quarterly)
if df.empty:
st.info("Balance sheet data unavailable.")
else:
display, colors = _build_statement(df)
st.dataframe(_style(display, colors), use_container_width=True)
st.download_button(
"Download CSV",
df.to_csv().encode(),
file_name=f"{ticker.upper()}_balance_{'quarterly' if quarterly else 'annual'}.csv",
mime="text/csv",
key=f"dl_balance_{ticker}_{quarterly}",
)
with tab_cashflow:
df = get_cash_flow(ticker, quarterly=quarterly)
if df.empty:
st.info("Cash flow data unavailable.")
else:
display, colors = _build_statement(df)
st.dataframe(_style(display, colors), use_container_width=True)
st.download_button(
"Download CSV",
df.to_csv().encode(),
file_name=f"{ticker.upper()}_cashflow_{'quarterly' if quarterly else 'annual'}.csv",
mime="text/csv",
key=f"dl_cashflow_{ticker}_{quarterly}",
)
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