Merge pull request #218 from bashtage/final-panel-removal

MAINT: Remove pd.Panel

Author: bashtage

doc/source/spelling_wordlist.txt

@@ -114,3 +114,5 @@ csc
 tstats
 np
 orthogonalize
+MultiIndex
+multiindex

examples/panel_data-formats.ipynb

@@ -18,7 +18,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Multi Index DataFrames\n",
+    "## MultiIndex DataFrames\n",
     "The most precise data format to use is a MultiIndex `DataFrame`.  This is the most precise since only single columns can preserve all types within a panel.  For example, it is not possible to span a single Categorical variable across multiple columns when using a pandas `Panel`. \n",
     "\n",
     "This example uses the job training data to construct a MultiIndex `DataFrame` using the `set_index` command. The entity index is `fcode` and the time index is `year`."
@@ -39,7 +39,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Here `set_index` is used to set the multi index using the firm code (entity) and year (time)."
+    "Here `set_index` is used to set the MultiIndex using the firm code (entity) and year (time)."
    ]
   },
   {

linearmodels/tests/test_utility.py

@@ -185,23 +185,34 @@ def test_format_wide():
     assert max(map(lambda v: len(v), out)) <= 80
 
 
-@pytest.mark.skipif(MISSING_PANEL, reason='pd.Panel is not installed')
-@pytest.mark.filterwarnings('ignore::FutureWarning')
-@pytest.mark.filterwarnings('ignore::DeprecationWarning')
 def test_panel_to_midf():
     x = np.random.standard_normal((3, 7, 100))
-    expected = pd.Panel(x).to_frame()
     df = panel_to_frame(x, list(range(3)), list(range(7)), list(range(100)))
+    mi = pd.MultiIndex.from_product([list(range(7)), list(range(100))])
+    expected = pd.DataFrame(index=mi, columns=[0, 1, 2])
+    for i in range(3):
+        expected[i] = x[i].ravel()
+    expected.index.names = ["major", "minor"]
     pd.testing.assert_frame_equal(df, expected)
 
-    expected = pd.Panel(x).swapaxes(1, 2).to_frame(filter_observations=False)
-    df = panel_to_frame(x, list(range(3)), list(range(7)), list(range(100)), True)
-    pd.testing.assert_frame_equal(df, expected)
+    expected2 = expected.copy()
+    expected2 = expected2.sort_index(level=[1, 0])
+    expected2.index = expected2.index.swaplevel(0, 1)
+    expected2.index.names = ["major", "minor"]
+    df2 = panel_to_frame(x, list(range(3)), list(range(7)), list(range(100)), True)
+    pd.testing.assert_frame_equal(df2, expected2)
+
     entities = list(map(''.join, [[random.choice(string.ascii_lowercase) for __ in range(10)]
                                   for _ in range(100)]))
     times = pd.date_range('1999-12-31', freq='A-DEC', periods=7)
     var_names = ['x.{0}'.format(i) for i in range(1, 4)]
-    expected = pd.Panel(x, items=var_names, major_axis=times, minor_axis=entities)
-    expected = expected.swapaxes(1, 2).to_frame(filter_observations=False)
-    df = panel_to_frame(x, var_names, times, entities, True)
-    pd.testing.assert_frame_equal(df, expected)
+    df3 = panel_to_frame(x, var_names, times, entities, True)
+    mi = pd.MultiIndex.from_product([times, entities])
+    expected3 = pd.DataFrame(index=mi, columns=var_names)
+    for i in range(1, 4):
+        expected3['x.{0}'.format(i)] = x[i-1].ravel()
+    expected3.index = expected3.index.swaplevel(0, 1)
+    mi = pd.MultiIndex.from_product([entities, times])
+    expected3 = expected3.loc[mi]
+    expected3.index.names = ["major", "minor"]
+    pd.testing.assert_frame_equal(df3, expected3)

linearmodels/utility.py

@@ -555,6 +555,8 @@ def panel_to_frame(x, items, major_axis, minor_axis, swap=False):
         List like object with major_axis labels
     minor_axis : list-like
         List like object with minor_axis labels
+    swap : bool
+        Swap is major and minor axes
 
     Notes
     -----