BUG: Fix precision loss in read_json

Fixes pandas-dev#20608

Author: fawazahmed0

pandas/io/json/_json.py

@@ -1168,6 +1168,7 @@ def _try_convert_data(
         """
         Try to parse a Series into a column by inferring dtype.
         """
+        org_data = data
         # don't try to coerce, unless a force conversion
         if use_dtypes:
             if not self.dtype:
@@ -1222,7 +1223,7 @@ def _try_convert_data(
         if len(data) and data.dtype in ("float", "object"):
             # coerce ints if we can
             try:
-                new_data = data.astype("int64")
+                new_data = org_data.astype("int64")
                 if (new_data == data).all():
                     data = new_data
                     converted = True

pandas/tests/io/json/test_pandas.py

@@ -2286,3 +2286,15 @@ def test_read_json_lines_rangeindex():
     result = read_json(StringIO(data), lines=True).index
     expected = RangeIndex(2)
     tm.assert_index_equal(result, expected, exact=True)
+
+
+def test_large_number():
+    assert (
+        read_json(
+            StringIO('["9999999999999999"]'),
+            orient="values",
+            typ="series",
+            convert_dates=False,
+        )[0]
+        == 9999999999999999
+    )