CLN: catch specific exceptions in frame.py (pandas-dev#29258)

Author: jbrockmendel

pandas/core/frame.py

@@ -1666,11 +1666,12 @@ def from_records(
             else:
                 try:
                     index_data = [arrays[arr_columns.get_loc(field)] for field in index]
+                except (KeyError, TypeError):
+                    # raised by get_loc, see GH#29258
+                    result_index = index
+                else:
                     result_index = ensure_index_from_sequences(index_data, names=index)
-
                     exclude.update(index)
-                except Exception:
-                    result_index = index
 
         if any(exclude):
             arr_exclude = [x for x in exclude if x in arr_columns]
@@ -3625,11 +3626,11 @@ def reindexer(value):
                 # GH 4107
                 try:
                     value = value.reindex(self.index)._values
-                except Exception as e:
-
-                    # duplicate axis
+                except ValueError as err:
+                    # raised in MultiIndex.from_tuples, see test_insert_error_msmgs
                     if not value.index.is_unique:
-                        raise e
+                        # duplicate axis
+                        raise err
 
                     # other
                     raise TypeError(
@@ -7796,7 +7797,8 @@ def f(x):
                     # TODO: combine with hasattr(result, 'dtype') further down
                     # hard since we don't have `values` down there.
                     result = np.bool_(result)
-            except Exception as e:
+            except TypeError as err:
+                # e.g. in nanops trying to convert strs to float
 
                 # try by-column first
                 if filter_type is None and axis == 0:
@@ -7826,7 +7828,7 @@ def f(x):
                     raise NotImplementedError(
                         "Handling exception with filter_type {f} not"
                         "implemented.".format(f=filter_type)
-                    ) from e
+                    ) from err
                 with np.errstate(all="ignore"):
                     result = f(data.values)
                 labels = data._get_agg_axis(axis)