[Backport ##14416] BUG: Concat with axis rows

closes #14369

Author: Brandon M. Burroughs <[email protected]>

Closes #14416 from brandonmburroughs/concat_with_axis_rows and squashes the following commits:

9aa260d [Brandon M. Burroughs] Changing axis handling to depend on object passed
49442be [Brandon M. Burroughs] Using dataframe _get_axis_number instance method
64702fb [Brandon M. Burroughs] Updating documentation for concat
fdd5260 [Brandon M. Burroughs] Removing duplicate expected dfs
3f08b07 [Brandon M. Burroughs] Adding concat tests for axis 0, 1, and 'index'
cf3f998 [Brandon M. Burroughs] Adding ValueError test for concat Series axis 'columns'
a6694b9 [Brandon M. Burroughs] Updating documentation
584ebd2 [Brandon M. Burroughs] BUG: Allow concat to take string axis names

(cherry picked from commit fd3be00)

Author: brandonmburroughs

doc/source/whatsnew/v0.19.1.txt

@@ -44,6 +44,7 @@ Bug Fixes
 
 
 - Bug in ``pd.concat`` where names of the ``keys`` were not propagated to the resulting ``MultiIndex`` (:issue:`14252`)
+- Bug in ``pd.concat`` where ``axis`` cannot take string parameters ``'rows'`` or ``'columns'`` (:issue:`14369`)
 - Bug in ``MultiIndex.set_levels`` where illegal level values were still set after raising an error (:issue:`13754`)
 - Bug in ``DataFrame.to_json`` where ``lines=True`` and a value contained a ``}`` character (:issue:`14391`)
 - Bug in ``df.groupby`` causing an ``AttributeError`` when grouping a single index frame by a column and the index level (:issue`14327`)

pandas/tests/frame/test_combine_concat.py

@@ -347,6 +347,65 @@ def test_concat_named_keys(self):
                                              names=[None, None]))
         assert_frame_equal(concatted_unnamed, expected_unnamed)
 
+    def test_concat_axis_parameter(self):
+        # GH 14369
+        df1 = pd.DataFrame({'A': [0.1, 0.2]}, index=range(2))
+        df2 = pd.DataFrame({'A': [0.3, 0.4]}, index=range(2))
+
+        # Index/row/0 DataFrame
+        expected_index = pd.DataFrame(
+            {'A': [0.1, 0.2, 0.3, 0.4]}, index=[0, 1, 0, 1])
+
+        concatted_index = pd.concat([df1, df2], axis='index')
+        assert_frame_equal(concatted_index, expected_index)
+
+        concatted_row = pd.concat([df1, df2], axis='rows')
+        assert_frame_equal(concatted_row, expected_index)
+
+        concatted_0 = pd.concat([df1, df2], axis=0)
+        assert_frame_equal(concatted_0, expected_index)
+
+        # Columns/1 DataFrame
+        expected_columns = pd.DataFrame(
+            [[0.1, 0.3], [0.2, 0.4]], index=[0, 1], columns=['A', 'A'])
+
+        concatted_columns = pd.concat([df1, df2], axis='columns')
+        assert_frame_equal(concatted_columns, expected_columns)
+
+        concatted_1 = pd.concat([df1, df2], axis=1)
+        assert_frame_equal(concatted_1, expected_columns)
+
+        series1 = pd.Series([0.1, 0.2])
+        series2 = pd.Series([0.3, 0.4])
+
+        # Index/row/0 Series
+        expected_index_series = pd.Series(
+            [0.1, 0.2, 0.3, 0.4], index=[0, 1, 0, 1])
+
+        concatted_index_series = pd.concat([series1, series2], axis='index')
+        assert_series_equal(concatted_index_series, expected_index_series)
+
+        concatted_row_series = pd.concat([series1, series2], axis='rows')
+        assert_series_equal(concatted_row_series, expected_index_series)
+
+        concatted_0_series = pd.concat([series1, series2], axis=0)
+        assert_series_equal(concatted_0_series, expected_index_series)
+
+        # Columns/1 Series
+        expected_columns_series = pd.DataFrame(
+            [[0.1, 0.3], [0.2, 0.4]], index=[0, 1], columns=[0, 1])
+
+        concatted_columns_series = pd.concat(
+            [series1, series2], axis='columns')
+        assert_frame_equal(concatted_columns_series, expected_columns_series)
+
+        concatted_1_series = pd.concat([series1, series2], axis=1)
+        assert_frame_equal(concatted_1_series, expected_columns_series)
+
+        # Testing ValueError
+        with assertRaisesRegexp(ValueError, 'No axis named'):
+            pd.concat([series1, series2], axis='something')
+
 
 class TestDataFrameCombineFirst(tm.TestCase, TestData):
 

pandas/tools/merge.py

@@ -1283,7 +1283,7 @@ def concat(objs, axis=0, join='outer', join_axes=None, ignore_index=False,
         argument, unless it is passed, in which case the values will be
         selected (see below). Any None objects will be dropped silently unless
         they are all None in which case a ValueError will be raised
-    axis : {0, 1, ...}, default 0
+    axis : {0/'index', 1/'columns'}, default 0
         The axis to concatenate along
     join : {'inner', 'outer'}, default 'outer'
         How to handle indexes on other axis(es)
@@ -1411,6 +1411,12 @@ def __init__(self, objs, axis=0, join='outer', join_axes=None,
             sample = objs[0]
         self.objs = objs
 
+        # Standardize axis parameter to int
+        if isinstance(sample, Series):
+            axis = DataFrame()._get_axis_number(axis)
+        else:
+            axis = sample._get_axis_number(axis)
+
         # Need to flip BlockManager axis in the DataFrame special case
         self._is_frame = isinstance(sample, DataFrame)
         if self._is_frame: