correct doc for DF.count (#683)

Rubtsowa · web-flow · commit 689077d87673 · 2020-03-22T10:59:55.000+03:00
diff --git a/examples/dataframe/dataframe_count.py b/examples/dataframe/dataframe_count.py
@@ -0,0 +1,47 @@
+# *****************************************************************************
+# Copyright (c) 2020, Intel Corporation All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+#     Redistributions of source code must retain the above copyright notice,
+#     this list of conditions and the following disclaimer.
+#
+#     Redistributions in binary form must reproduce the above copyright notice,
+#     this list of conditions and the following disclaimer in the documentation
+#     and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
+# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
+# OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
+# WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
+# OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE,
+# EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+# result
+# A    4
+# B    4
+# C    3
+# dtype: int64
+
+import pandas as pd
+import numpy as np
+from numba import njit
+
+
+@njit
+def dataframe_count():
+    df = pd.DataFrame({"A": [.2, .0, .6, .2],
+                       "B": [2, 0, 6, 2],
+                       "C": [-1, np.nan, 1, np.inf]})
+
+    return df.count()
+
+
+print(dataframe_count())
diff --git a/sdc/datatypes/hpat_pandas_dataframe_functions.py b/sdc/datatypes/hpat_pandas_dataframe_functions.py
@@ -1112,26 +1112,42 @@ def prod_overload(df, axis=None, skipna=None, level=None, numeric_only=None, min
 @sdc_overload_method(DataFrameType, 'count')
 def count_overload(df, axis=0, level=None, numeric_only=False):
     """
-    Pandas DataFrame method :meth:`pandas.DataFrame.count` implementation.
-    .. only:: developer
+    Intel Scalable Dataframe Compiler User Guide
+    ********************************************
 
-    Test: python -m sdc.runtests -k sdc.tests.test_dataframe.TestDataFrame.test_count*
+    Pandas API: pandas.DataFrame.count
 
-    Parameters
+    Limitations
     -----------
-    df: :class:`pandas.DataFrame`
-      input arg
-    axis:
-      *unsupported*
-    level:
-      *unsupported*
-    numeric_only:
-      *unsupported*
+    Parameters ``axis``, ``level`` and ``numeric_only`` are unsupported.
 
-    Returns
-    -------
-    :obj:`pandas.Series` or `pandas.DataFrame`
-      for each column/row the number of non-NA/null entries. If level is specified returns a DataFrame.
+    Examples
+    --------
+    .. literalinclude:: ../../../examples/dataframe/dataframe_count.py
+       :language: python
+       :lines: 33-
+       :caption: Count non-NA cells for each column or row.
+       :name: ex_dataframe_count
+
+    .. command-output:: python ./dataframe/dataframe_count.py
+       :cwd: ../../../examples
+
+    .. seealso::
+        :ref:`Series.count <pandas.Series.count>`
+            Number of non-NA elements in a Series.
+        :ref:`DataFrame.shape <pandas.DataFrame.shape>`
+            Number of DataFrame rows and columns (including NA elements).
+        :ref:`DataFrame.isna <pandas.DataFrame.isna>`
+            Boolean same-sized DataFrame showing places of NA elements.
+
+    Intel Scalable Dataframe Compiler Developer Guide
+    *************************************************
+
+    Pandas DataFrame method :meth:`pandas.DataFrame.count` implementation.
+
+        .. only:: developer
+
+            Test: python -m sdc.runtests -k sdc.tests.test_dataframe.TestDataFrame.test_count*
     """
 
     name = 'count'
