quantstats - pypi Package Compare versions

Comparing version 0.0.75 to 0.0.76

PKG-INFO

 Metadata-Version: 2.4
 Name: QuantStats
-Version: 0.0.75
+Version: 0.0.76
 Summary: Portfolio analytics for quants
@@ -5,0 +5,0 @@ Home-page: https://github.com/ranaroussi/quantstats

QuantStats.egg-info/PKG-INFO

 Metadata-Version: 2.4
 Name: QuantStats
-Version: 0.0.75
+Version: 0.0.76
 Summary: Portfolio analytics for quants
@@ -5,0 +5,0 @@ Home-page: https://github.com/ranaroussi/quantstats

quantstats/_compat.py

@@ -61,2 +61,32 @@ #!/usr/bin/env python
 
+def normalize_timezone(data: Union[pd.Series, pd.DataFrame]) -> Union[pd.Series, pd.DataFrame]:
+    """
+    Normalize timezone information for consistent comparisons.
+    
+    If data has timezone info, converts to UTC then removes timezone info.
+    This ensures all data can be compared regardless of original timezone.
+    
+    Parameters
+    ----------
+    data : pd.Series or pd.DataFrame
+        Time series data with DatetimeIndex
+        
+    Returns
+    -------
+    pd.Series or pd.DataFrame
+        Data with timezone-naive DatetimeIndex
+    """
+    if not isinstance(data.index, pd.DatetimeIndex):
+        return data
+    
+    # If timezone aware, convert to UTC then make naive
+    if data.index.tz is not None:
+        result = data.copy()
+        result.index = result.index.tz_convert('UTC').tz_localize(None)
+        return result
+    
+    # Already timezone naive, return as is
+    return data
+
+
 def safe_resample(data: Union[pd.Series, pd.DataFrame],
@@ -71,3 +101,4 @@ freq: str,
     frequency aliases and aggregation methods that are compatible across
-    different pandas versions.
+    different pandas versions. It also normalizes timezones to ensure
+    consistent comparisons.
 
@@ -89,3 +120,4 @@ Parameters
     pd.Series or pd.DataFrame
-        The resampled data with the specified frequency and aggregation
+        The resampled data with the specified frequency and aggregation,
+        with timezone normalized to UTC if present, or naive if not
 
@@ -109,30 +141,34 @@ Examples
     # This approach avoids deprecation warnings and ensures compatibility
+    result = None
     if isinstance(func_name, str):
         # Map common aggregation functions to their pandas methods
         if func_name == "sum":
-            return resampler.sum(**kwargs)
+            result = resampler.sum(**kwargs)
         elif func_name == "mean":
-            return resampler.mean(**kwargs)
+            result = resampler.mean(**kwargs)
         elif func_name == "std":
-            return resampler.std(**kwargs)
+            result = resampler.std(**kwargs)
         elif func_name == "count":
-            return resampler.count(**kwargs)
+            result = resampler.count(**kwargs)
         elif func_name == "min":
-            return resampler.min(**kwargs)
+            result = resampler.min(**kwargs)
         elif func_name == "max":
-            return resampler.max(**kwargs)
+            result = resampler.max(**kwargs)
         elif func_name == "first":
-            return resampler.first(**kwargs)
+            result = resampler.first(**kwargs)
         elif func_name == "last":
-            return resampler.last(**kwargs)
+            result = resampler.last(**kwargs)
         else:
             # Try to find the method on the resampler object
             if hasattr(resampler, func_name):
-                return getattr(resampler, func_name)(**kwargs)
+                result = getattr(resampler, func_name)(**kwargs)
             else:
                 # Fallback to apply for custom string functions
-                return resampler.apply(func_name, **kwargs)
+                result = resampler.apply(func_name, **kwargs)
     else:
         # For callable functions, use apply method
-        return resampler.apply(func_name, **kwargs)
+        result = resampler.apply(func_name, **kwargs)
+    
+    # Normalize timezone to ensure consistent comparisons
+    return normalize_timezone(result)
 
@@ -139,0 +175,0 @@

quantstats/_plotting/wrappers.py

@@ -164,3 +164,3 @@ #!/usr/bin/env python
     # 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)
 
@@ -167,0 +167,0 @@ # Use current figure size if not specified

quantstats/utils.py

@@ -455,2 +455,7 @@ #!/usr/bin/env python
     """
+    # Normalize timezone for consistency before aggregation
+    # Convert to UTC if timezone-aware, then make naive
+    if hasattr(returns.index, 'tz') and returns.index.tz is not None:
+        returns = returns.tz_convert('UTC').tz_localize(None)
+    
     # Return original data if no period specified or daily period
@@ -566,4 +571,6 @@ if period is None or "day" in period:
 
-    # Remove timezone information for consistency
-    data = data.tz_localize(None)
+    # Normalize timezone information for consistency
+    # Convert to UTC if timezone-aware, then make naive
+    if hasattr(data.index, 'tz') and data.index.tz is not None:
+        data = data.tz_convert('UTC').tz_localize(None)
     return data
@@ -608,6 +615,6 @@
             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)
 
@@ -640,4 +647,6 @@ # cleanup data - replace infinite values with NaN
 
-    # Remove timezone information for consistency
-    data = data.tz_localize(None)
+    # Normalize timezone information for consistency
+    # Convert to UTC if timezone-aware, then make naive
+    if hasattr(data.index, 'tz') and data.index.tz is not None:
+        data = data.tz_convert('UTC').tz_localize(None)
 
@@ -686,4 +695,4 @@ # Cache the result
     # 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
@@ -719,3 +728,3 @@
             .reindex(period)
-            .pct_change()
+            .pct_change(fill_method=None)
             .fillna(0)
@@ -725,4 +734,7 @@ )
 
-    # Remove timezone information
-    benchmark = benchmark.tz_localize(None)
+    # Normalize timezone information for consistent comparisons
+    # Convert to UTC if timezone-aware, then make naive
+    if hasattr(benchmark.index, 'tz') and benchmark.index.tz is not None:
+        benchmark = benchmark.tz_convert('UTC').tz_localize(None)
+    # If already timezone-naive, no action needed
 
@@ -729,0 +741,0 @@ # Prepare returns or return raw data

quantstats/version.py

@@ -1,1 +0,1 @@
-version = "0.0.75"
+version = "0.0.76"

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Improved metrics

Total package byte prevSize

410165

1.03%

Lines of code

9398

0.74%