BryanCutler commented on a change in pull request #24844: [SPARK-28003][PYTHON]
Allow NaT values when creating Spark dataframe from pandas with Arrow
URL: https://github.com/apache/spark/pull/24844#discussion_r293038513
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File path: python/pyspark/sql/tests/test_arrow.py
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@@ -383,6 +383,19 @@ def test_timestamp_dst(self):
assert_frame_equal(pdf, df_from_python.toPandas())
assert_frame_equal(pdf, df_from_pandas.toPandas())
+ def test_timestamp_nat(self):
+ import pandas as pd
+ dt1 = [pd.NaT, pd.Timestamp('2019-06-11')] * 100
+ dt2 = [None, pd.Timestamp('2019-06-11')] * 100
+ pdf1 = pd.DataFrame({'time': dt1})
+ pdf2 = pd.DataFrame({'time': dt2})
+
+ df1 = self.spark.createDataFrame(pdf1)
+ df2 = self.spark.createDataFrame(pdf2)
Review comment:
I think you can just combine these to 1 DataFrame, but I think it would be
good to also check against toPandas without Arrow
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