Fix count API issue about ignoring nan values (#17779)

Fixes: #17768 

This PR fixes the `count` api to match default dtype behavior where `nan`'s are not counted as valid elements. But retains counting `nan`'s as valid in non-pandas compatibility modes because that is what pandas nullable dtypes do.

Authors:
  - GALI PREM SAGAR (https://github.com/galipremsagar)

Approvers:
  - Matthew Roeschke (https://github.com/mroeschke)

URL: #17779

python/cudf/cudf/core/dataframe.py

@@ -6409,7 +6409,20 @@ def count(self, axis=0, numeric_only=False):
             raise NotImplementedError("Only axis=0 is currently supported.")
         length = len(self)
         return Series._from_column(
-            as_column([length - col.null_count for col in self._columns]),
+            as_column(
+                [
+                    length
+                    - (
+                        col.null_count
+                        + (
+                            col.nan_count
+                            if cudf.get_option("mode.pandas_compatible")
+                            else 0
+                        )
+                    )
+                    for col in self._columns
+                ]
+            ),
             index=cudf.Index(self._column_names),
         )
 

python/cudf/cudf/core/series.py

@@ -2712,7 +2712,10 @@ def count(self):
 
             Parameters currently not supported is `level`.
         """
-        return self.valid_count
+        valid_count = self.valid_count
+        if cudf.get_option("mode.pandas_compatible"):
+            return valid_count - self._column.nan_count
+        return valid_count
 
     @_performance_tracking
     def mode(self, dropna=True):

python/cudf/cudf/tests/input_output/test_parquet.py

@@ -8,7 +8,7 @@
 from cudf._fuzz_testing.utils import compare_dataframe
 
 
-def test_parquet_long_list():
+def test_parquet_long_list(tmpdir):
     # This test generates int and string list columns, where each has a row that is very large.
     # When generated by the cudf writer these long rows are contained on a single page,
     # but when generated by pyarrow they span several pages.
@@ -41,7 +41,7 @@ def test_parquet_long_list():
     )
 
     # Write the table to a parquet file using pyarrow
-    file_name = "long_row_list_test.pq"
+    file_name = tmpdir.join("long_row_list_test.pq")
     # https://arrow.apache.org/docs/python/generated/pyarrow.parquet.write_table.html
     pq.write_table(
         generated_table,

python/cudf/cudf/tests/test_series.py

@@ -3019,3 +3019,18 @@ def test_roundtrip_series_plc_column(ps):
     expect = cudf.Series(ps)
     actual = cudf.Series.from_pylibcudf(*expect.to_pylibcudf())
     assert_eq(expect, actual)
+
+
+def test_series_dataframe_count_float():
+    gs = cudf.Series([1, 2, 3, None, np.nan, 10], nan_as_null=False)
+    ps = cudf.Series([1, 2, 3, None, np.nan, 10])
+
+    with cudf.option_context("mode.pandas_compatible", True):
+        assert_eq(ps.count(), gs.count())
+        assert_eq(ps.to_frame().count(), gs.to_frame().count())
+    with cudf.option_context("mode.pandas_compatible", False):
+        assert_eq(gs.count(), gs.to_pandas(nullable=True).count())
+        assert_eq(
+            gs.to_frame().count(),
+            gs.to_frame().to_pandas(nullable=True).count(),
+        )