Enhance Bitcoin vs M2 chart with improved plotting and indexing

Refactor `bitcoin_m2_chart.py` to plot Bitcoin price on a log scale against a rebased M2 money supply index (base 100). Update visual elements for clarity, including color adjustments and axis labels. Extend x-axis for future projections and improve x-tick formatting for better readability. Add new output images for the updated chart.

scripts/bitcoin_m2_chart.py

@@ -1,15 +1,11 @@
 #!/usr/bin/env python3
 """bitcoin_m2_chart.py
 ----------------------
-Plot Bitcoin price versus global M2 money supply stored in `data/fred.db`.
-
-The script reads two FRED series from the local SQLite database and
-plots them on dual axes. The M2 series can be shifted relative to the
-Bitcoin series by a configurable number of days.
+Plot Bitcoin price (log scale) versus global M2 money supply (as a 100-point index)
+stored in `data/fred.db`. Bitcoin is orange; M2 is green; white background; monthly x-ticks.
 """
 
 from __future__ import annotations
-
 import argparse
 from datetime import datetime
 from pathlib import Path
@@ -23,7 +19,7 @@ import matplotlib.pyplot as plt
 import pandas as pd
 from dateutil.relativedelta import relativedelta
 
-# IMPORTANT: use the package‐qualified import
+# IMPORTANT: use the package-qualified import
 from scripts.common import (
     fetch_series_db,
     save_figure,
@@ -65,37 +61,76 @@ def plot_bitcoin_m2(
     height: float = 6,
     dpi: int | None = None,
 ) -> plt.Figure:
-    """Plot Bitcoin price and shifted M2 on dual axes."""
-    # Determine overlapping range
+    """
+    Plot Bitcoin price (log scale) and a rebased (100-point) M2 index on dual axes:
+      • Bitcoin is orange, on a log-scaled left y-axis
+      • Global M2 is green, on a linear right y-axis
+      • White background, monthly x-ticks, with an “empty buffer” past the last date.
+    """
+    # 1) Determine overlapping date range
     common_start = max(btc.index.min(), m2.index.min())
     common_end = min(btc.index.max(), m2.index.max())
 
-    btc_common = btc.loc[common_start:common_end]
-    m2_common = m2.loc[common_start:common_end]
+    btc_common = btc.loc[common_start:common_end].dropna(subset=["value"])
+    m2_common = m2.loc[common_start:common_end].dropna(subset=["value"])
 
+    # 2) Shift M2 by `offset_days`
     m2_shifted = m2_common.shift(offset_days)
 
+    # 3) Rebase M2 to a 100-point index
+    #    (so that at the first available date, M2_index = 100)
+    m2_indexed = (m2_shifted["value"] / m2_shifted["value"].iloc[0]) * 100
+
+    # 4) Create figure + axes
     fig, ax1 = plt.subplots(figsize=(width, height), dpi=dpi)
+    # (White background is default, so no style override is needed.)
+
+    # 5) Plot Bitcoin (orange) ON A LOGARITHMIC Y-AXIS
     ax1.plot(
-        btc_common.index, btc_common["value"], label="Bitcoin (LHS)", color="#1f77b4"
+        btc_common.index,
+        btc_common["value"],
+        label="Bitcoin (USD, log-scale)",
+        color="#f7931a",  # Bitcoin-orange
+        linewidth=2.0,
     )
-    ax1.set_ylabel("Price (USD)")
+    ax1.set_yscale("log")                     # ← LOG SCALE
+    ax1.set_ylabel("Bitcoin Price (USD, log)", color="#333333")
+    ax1.tick_params(axis="y", colors="#333333")
     ax1.grid(axis="y", linestyle="--", alpha=0.3)
 
+    # 6) Plot M2 index (green) on a LINEAR right‐hand axis
     ax2 = ax1.twinx()
     ax2.plot(
-        m2_shifted.index, m2_shifted["value"], label="Global M2 (RHS)", color="#ff7f0e"
+        m2_indexed.index,
+        m2_indexed,
+        label="Global M2 Index (base 100)",
+        color="#00aa00",  # dark-green for contrast
+        linewidth=2.0,
     )
-    ax2.set_ylabel("Global M2")
+    ax2.set_ylabel("Global M2 Index (linear)", color="#333333")
+    ax2.tick_params(axis="y", colors="#333333")
+    # (No grid on ax2 to keep it clean.)
 
-    ax1.set_xlim(common_start, common_end + relativedelta(years=extend_years))
-    ax1.xaxis.set_major_locator(mdates.YearLocator(base=5))
-    ax1.xaxis.set_minor_locator(mdates.YearLocator())
-    ax1.xaxis.set_major_formatter(mdates.DateFormatter("%Y"))
+    # 7) Extend x‐axis to give “future blank space”
+    x_end_extended = common_end + relativedelta(years=extend_years)
+    ax1.set_xlim(common_start, x_end_extended)
 
+    # 8) Monthly x-ticks (e.g., “Aug, Sep, Oct…”)
+    ax1.xaxis.set_major_locator(mdates.MonthLocator(interval=1))
+    ax1.xaxis.set_major_formatter(mdates.DateFormatter("%b"))
+    ax1.xaxis.set_minor_locator(mdates.MonthLocator(bymonthday=15))
+    plt.setp(ax1.get_xticklabels(), rotation=0, ha="center")
+
+    # 9) Combine legends from both axes
     lines1, labels1 = ax1.get_legend_handles_labels()
     lines2, labels2 = ax2.get_legend_handles_labels()
-    ax1.legend(lines1 + lines2, labels1 + labels2, loc="upper left", frameon=False)
+    ax1.legend(
+        lines1 + lines2,
+        labels1 + labels2,
+        loc="upper left",
+        frameon=False,
+        fontsize=10,
+    )
 
     fig.tight_layout()
     return fig
@@ -127,7 +162,7 @@ def main(argv: list[str] | None = None) -> plt.Figure:
     p.add_argument(
         "--offset",
         type=int,
-        default=94,
+        default=94,  # M2 leads by 94 days
         help="shift M2 by this many days (positive = M2 leads)",
     )
     p.add_argument(
@@ -162,17 +197,16 @@ def main(argv: list[str] | None = None) -> plt.Figure:
 
     btc, m2 = fetch_series(start_dt, end_dt, args.btc_series, args.m2_series, args.db)
 
-    # ─── Drop any rows where the FRED tables had NULLs in "value" ──────────────────
+    # Drop rows with null “value”
     btc = btc.dropna(subset=["value"])
     m2 = m2.dropna(subset=["value"])
-    # ────────────────────────────────────────────────────────────────────────────────
 
     validate_series(btc, m2, args.btc_series, args.m2_series)
     fig = plot_bitcoin_m2(
         btc,
         m2,
-        args.offset,
-        args.extend_years,
+        offset_days=args.offset,
+        extend_years=args.extend_years,
         width=args.width,
         height=args.height,
         dpi=args.dpi,