PERF: Use shallow copies/defer copies in io

pandas/io/json/_json.py

@@ -369,18 +369,22 @@ def __init__(
             msg = "Overlapping names between the index and columns"
             raise ValueError(msg)
 
-        obj = obj.copy()
         timedeltas = obj.select_dtypes(include=["timedelta"]).columns
+        copied = False
         if len(timedeltas):
+            obj = obj.copy()
+            copied = True
             obj[timedeltas] = obj[timedeltas].map(lambda x: x.isoformat())
-        # Convert PeriodIndex to datetimes before serializing
-        if isinstance(obj.index.dtype, PeriodDtype):
-            obj.index = obj.index.to_timestamp()
 
         # exclude index from obj if index=False
         if not self.index:
             self.obj = obj.reset_index(drop=True)
         else:
+            # Convert PeriodIndex to datetimes before serializing
+            if isinstance(obj.index.dtype, PeriodDtype):
+                if not copied:
+                    obj = obj.copy(deep=False)
+                obj.index = obj.index.to_timestamp()
             self.obj = obj.reset_index(drop=False)
         self.date_format = "iso"
         self.orient = "records"

pandas/io/json/_table_schema.py

@@ -114,7 +114,7 @@ def set_default_names(data):
             )
         return data
 
-    data = data.copy()
+    data = data.copy(deep=False)
     if data.index.nlevels > 1:
         data.index.names = com.fill_missing_names(data.index.names)
     else:

pandas/io/sql.py

@@ -1014,7 +1014,7 @@ def _execute_insert_multi(self, conn, keys: list[str], data_iter) -> int:
 
     def insert_data(self) -> tuple[list[str], list[np.ndarray]]:
         if self.index is not None:
-            temp = self.frame.copy()
+            temp = self.frame.copy(deep=False)
             temp.index.names = self.index
             try:
                 temp.reset_index(inplace=True)