Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/18933#discussion_r133254340
--- Diff: python/pyspark/sql/tests.py ---
@@ -2507,6 +2507,37 @@ def test_to_pandas(self):
self.assertEquals(types[2], np.bool)
self.assertEquals(types[3], np.float32)
+ @unittest.skipIf(not _have_pandas, "Pandas not installed")
+ def test_to_pandas_timezone_aware(self):
+ import pandas as pd
+ from dateutil import tz
+ tzlocal = tz.tzlocal()
+ ts = datetime.datetime(1970, 1, 1)
+ pdf = pd.DataFrame.from_records([[ts]], columns=['ts'])
+
+ self.spark.conf.set('spark.sql.session.timeZone',
'America/Los_Angeles')
+
+ schema = StructType().add("ts", TimestampType())
+ df = self.spark.createDataFrame([(ts,)], schema)
+
+ pdf_naive = df.toPandas()
+ self.assertEqual(pdf_naive['ts'][0].tzinfo, None)
+ self.assertTrue(pdf_naive.equals(pdf))
--- End diff --
This is not really a test that `df.toPandas()` is time zone naive. If that
was true then you should be able to do
```
df = self.spark.createDataFrame([(ts,)], schema)
os.environ["TZ"] = "America/New_York"
time.tzset()
pdf_naive = df.toPandas()
self.assertTrue(pdf_naive.equals(pdf))
```
but this will fail because `toPandas()` does a conversion to local time,
which is what the original data happens to be
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