Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/18378#discussion_r123380675
--- Diff: python/pyspark/sql/tests.py ---
@@ -2274,6 +2274,21 @@ def count_bucketed_cols(names,
table="pyspark_bucket"):
.mode("overwrite").saveAsTable("pyspark_bucket"))
self.assertSetEqual(set(data),
set(self.spark.table("pyspark_bucket").collect()))
+ def test_to_pandas(self):
+ import numpy as np
+ schema = StructType().add("a", IntegerType()).add("b",
StringType())\
+ .add("c", BooleanType()).add("d", FloatType())
+ data = [
+ (1, "foo", True, 3.0), (2, "foo", True, 5.0),
+ (3, "bar", False, -1.0), (4, "bar", False, 6.0),
+ ]
+ df = self.spark.createDataFrame(data, schema)
+ types = df.toPandas().dtypes
--- End diff --
Could we check and skip if `pandas` is not able to import (`numpy` is a
Pandas dependency. So checking Pandas alone should be fine)?
```python
try:
import pandas
_have_pandas = True
except:
# No Pandas, but that's okay, we'll skip those tests
pass
...
@unittest.skipIf(not _have_pandas, "Pandas not installed")
def test_to_pandas(self):
...
```
I at least see the doctest is being skipped, `>>> df.toPandas() # doctest:
+SKIP`.
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