Enhance zip calls with strict parameter

Added 'strict=True' parameter to zip calls for better error handling.

Author: IngramBJ

pandas/core/reshape/encoding.py

@@ -211,7 +211,7 @@ def check_len(item, name: str) -> None:
             # columns to prepend to result.
             with_dummies = [data.select_dtypes(exclude=dtypes_to_encode)]
 
-        for col, pre, sep in zip(data_to_encode.items(), prefix, prefix_sep):
+        for col, pre, sep in zip(data_to_encode.items(), prefix, prefix_sep, strict=True):
             # col is (column_name, column), use just column data here
             dummy = _get_dummies_1d(
                 col[1],
@@ -325,15 +325,15 @@ def get_empty_frame(data) -> DataFrame:
         codes = codes[mask]
         n_idx = np.arange(N)[mask]
 
-        for ndx, code in zip(n_idx, codes):
+        for ndx, code in zip(n_idx, codes, strict=True):
             sp_indices[code].append(ndx)
 
         if drop_first:
             # remove first categorical level to avoid perfect collinearity
             # GH12042
             sp_indices = sp_indices[1:]
             dummy_cols = dummy_cols[1:]
-        for col, ixs in zip(dummy_cols, sp_indices):
+        for col, ixs in zip(dummy_cols, sp_indices, strict=True):
             sarr = SparseArray(
                 np.ones(len(ixs), dtype=dtype),
                 sparse_index=IntIndex(N, ixs),
@@ -538,7 +538,7 @@ def from_dummies(
                 raise ValueError(len_msg)
         elif isinstance(default_category, Hashable):
             default_category = dict(
-                zip(variables_slice, [default_category] * len(variables_slice))
+                zip(variables_slice, [default_category] * len(variables_slice), strict=True)
             )
         else:
             raise TypeError(