GnuCash demo: daily totals + first analysis

Once you have a normalized BYOD project (see Track D BYOD with GnuCash (core_gl profile)), you can turn accounting tables into a simple “business time series” for basic statistics and forecasting.

What we’ll build

A small daily table:

  • date

  • revenue_proxy (net credits to Revenue accounts)

  • expenses_proxy (net debits to Expense accounts)

  • net_proxy (revenue_proxy − expenses_proxy)

Download (prebuilt)

If you want to jump straight to analysis without running the normalization step first:

Option A — Build daily totals from your normalized tables

Assume your BYOD project is at <BYOD_DIR> and you have:

  • <BYOD_DIR>/normalized/gl_journal.csv

  • <BYOD_DIR>/normalized/chart_of_accounts.csv

Run the built-in helper:

pystatsv1 trackd byod daily-totals --project <BYOD_DIR>

# (optional) choose an explicit output path
pystatsv1 trackd byod daily-totals --project <BYOD_DIR> --out <BYOD_DIR>/normalized/daily_totals.csv

Need a reminder of options? Run: pystatsv1 trackd byod daily-totals --help

This writes:

  • <BYOD_DIR>/normalized/daily_totals.csv

Option B — Quick first analysis (no repo clone required)

Once you have normalized/daily_totals.csv, you can do a quick first pass with pandas. This snippet prints a few summary stats and writes a simple plot:

python - <<'PY'
import pandas as pd
import matplotlib.pyplot as plt
from pathlib import Path

project = Path("byod/gnucash_demo")  # <-- set to your BYOD project folder (e.g., "<BYOD_DIR>")

csv_path = project / "normalized" / "daily_totals.csv"
outdir = Path("outputs/gnucash_demo")
outdir.mkdir(parents=True, exist_ok=True)

df = pd.read_csv(csv_path, parse_dates=["date"])
df = df.sort_values("date")

print(df.describe(include="all"))

ax = df.plot(x="date", y=["revenue_proxy", "expenses_proxy", "net_proxy"])
ax.figure.tight_layout()
ax.figure.savefig(outdir / "daily_totals.png")
print(f"Wrote: {outdir / 'daily_totals.png'}")
PY

(If you are working from the repo source, you can also adapt scripts/my_data_01_explore.py to your needs.)