fix: boolean and date failures with empty data

src/ydata_profiling/model/pandas/describe_boolean_pandas.py

@@ -1,6 +1,7 @@
 from typing import Tuple
 
 import pandas as pd
+import numpy as np
 
 from ydata_profiling.config import Settings
 from ydata_profiling.model.pandas.imbalance_pandas import column_imbalance_score
@@ -26,9 +27,15 @@ def pandas_describe_boolean_1d(
         A dict containing calculated series description values.
     """
 
-    value_counts = summary["value_counts_without_nan"]
-    summary.update({"top": value_counts.index[0], "freq": value_counts.iloc[0]})
-
-    summary["imbalance"] = column_imbalance_score(value_counts, len(value_counts))
+    value_counts: pd.Series = summary["value_counts_without_nan"]
+    if not value_counts.empty:
+        summary.update({"top": value_counts.index[0], "freq": value_counts.iloc[0]})
+        summary["imbalance"] = column_imbalance_score(value_counts, len(value_counts))
+    else:
+        summary.update({
+            "top": np.nan,
+            "freq": 0,
+            "imbalance": 0,
+        })
 
     return config, series, summary

src/ydata_profiling/model/pandas/describe_date_pandas.py

@@ -29,16 +29,26 @@ def pandas_describe_date_1d(
     Returns:
         A dict containing calculated series description values.
     """
-    summary.update(
-        {
-            "min": pd.Timestamp.to_pydatetime(series.min()),
-            "max": pd.Timestamp.to_pydatetime(series.max()),
-        }
-    )
-
-    summary["range"] = summary["max"] - summary["min"]
-
-    values = series.values.astype(np.int64) // 10**9
+    if summary["value_counts_without_nan"].empty:
+        values = series.values
+        summary.update(
+            {
+                "min": pd.NaT,
+                "max": pd.NaT,
+                "range": 0,
+            }
+        )
+    else:
+        summary.update(
+            {
+                "min": pd.Timestamp.to_pydatetime(series.min()),
+                "max": pd.Timestamp.to_pydatetime(series.max()),
+            }
+        )
+
+        summary["range"] = summary["max"] - summary["min"]
+
+        values = series.values.astype(np.int64) // 10**9
 
     if config.vars.num.chi_squared_threshold > 0.0:
         summary["chi_squared"] = chi_square(values)

src/ydata_profiling/report/structure/variables/render_date.py

@@ -103,13 +103,14 @@ def render_date(config: Settings, summary: Dict[str, Any]) -> Dict[str, Any]:
         )
 
     # Bottom
+    n_bins = len(summary['histogram'][1]) - 1 if summary['histogram'] else 0
     bottom = Container(
         [
             Image(
                 hist_data,
                 image_format=image_format,
                 alt="Histogram",
-                caption=f"<strong>Histogram with fixed size bins</strong> (bins={len(summary['histogram'][1]) - 1})",
+                caption=f"<strong>Histogram with fixed size bins</strong> (bins={n_bins})",
                 name="Histogram",
                 anchor_id=f"{varid}histogram",
             )