Fix FutureWarning for deprecated fill_method in pandas pct_change()

Updated all pct_change() calls to explicitly use fill_method=None to prevent
the deprecation warning: "The default fill_method='pad' in Series.pct_change
is deprecated and will be removed in a future version."

Changes:
- utils.py: Fixed pct_change() in _prepare_returns, download_returns, and _prepare_benchmark
- _plotting/wrappers.py: Fixed pct_change() in portfolio calculations
- All instances now use fill_method=None with explicit fillna(0) where needed

This ensures compatibility with pandas 2.x and future versions.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

Author: ranaroussi

CHANGELOG.md

@@ -16,6 +16,11 @@ Changelog
   - Data is converted to UTC then made timezone-naive for consistent comparisons
   - Fixes "Cannot compare dtypes datetime64[ns] and datetime64[ns, UTC]" errors
 
+- Fixed FutureWarning for pandas pct_change():
+  - Updated all pct_change() calls to use fill_method=None parameter
+  - Prevents "fill_method='pad' is deprecated" warnings in pandas 2.x
+  - Ensures compatibility with future pandas versions
+
 0.0.75
 ------
 

quantstats/_plotting/wrappers.py

@@ -161,7 +161,7 @@ def snapshot(
     # Select color scheme based on grayscale preference
     colors = _GRAYSCALE_COLORS if grayscale else _FLATUI_COLORS
     # Convert to portfolio format and calculate percentage changes
-    returns = _utils.make_portfolio(returns.dropna(), 1, mode).pct_change().fillna(0)
+    returns = _utils.make_portfolio(returns.dropna(), 1, mode).pct_change(fill_method=None).fillna(0)
 
     # Use current figure size if not specified
     if figsize is None:

quantstats/utils.py

@@ -610,10 +610,10 @@ def _prepare_returns(data, rf=0.0, nperiods=None):
             col_clean = data[col].dropna()
             # Check if data looks like prices (positive values > 1)
             if col_clean.min() >= 0 and col_clean.max() > 1:
-                data[col] = data[col].pct_change()
+                data[col] = data[col].pct_change(fill_method=None)
     # Process Series data
     elif data.min() >= 0 and data.max() > 1:
-        data = data.pct_change()
+        data = data.pct_change(fill_method=None)
 
     # cleanup data - replace infinite values with NaN
     data = data.replace([_np.inf, -_np.inf], float("NaN"))
@@ -688,8 +688,8 @@ def download_returns(ticker, period="max", proxy=None):
         params["period"] = period
 
     # Download data and calculate returns
-    df = safe_yfinance_download(proxy=proxy, **params)["Close"].pct_change()  # type: ignore
-    df = df.tz_localize(None)
+    df = safe_yfinance_download(proxy=proxy, **params)["Close"].pct_change(fill_method=None)  # type: ignore
+    df = df.fillna(0).tz_localize(None)
     return df
 
 
@@ -720,7 +720,7 @@ def _prepare_benchmark(benchmark=None, period="max", rf=0.0, prepare_returns=Tru
         benchmark = (
             benchmark_prices.reindex(new_index, method="bfill")
             .reindex(period)
-            .pct_change()
+            .pct_change(fill_method=None)
             .fillna(0)
         )
         benchmark = benchmark[benchmark.index.isin(period)]