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Adding a warning when dropping NA values for panel.to_frame #7879 #8063

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19391f8
Adding a warning when dropping NA values for panel.to_frame #7879
Magellanea Aug 18, 2014
63d5a3e
Adding missing import statement for warnings module
Magellanea Aug 18, 2014
f0f75fc
modify test cases to use tm.assert_produces_warning
Magellanea Aug 20, 2014
3bd040e
Minor fix - allow warning repetition from same source
Magellanea Aug 20, 2014
982c828
change ```filter_observation``` to be true by default, change other t…
Magellanea Aug 22, 2014
2e0180d
Fix tests for sparse module
Magellanea Aug 22, 2014
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3 changes: 3 additions & 0 deletions pandas/core/panel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -858,6 +858,9 @@ def to_frame(self, filter_observations=True):
mask = com.notnull(self.values).all(axis=0)
# size = mask.sum()
selector = mask.ravel()
if not np.all(selector):
warnings.warn("NaN values found\
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You'll need to import warnings in this file too

empty values will be dropped", RuntimeWarning)
else:
# size = N * K
selector = slice(None, None)
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32 changes: 31 additions & 1 deletion pandas/tests/test_panel.py
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Expand Up @@ -5,7 +5,7 @@
import nose

import numpy as np

import warnings
from pandas import Series, DataFrame, Index, isnull, notnull, pivot, MultiIndex
from pandas.core.datetools import bday
from pandas.core.panel import Panel
Expand Down Expand Up @@ -1556,6 +1556,36 @@ def test_to_frame_multi_drop_level(self):
expected = DataFrame({'i1': [1., 2], 'i2': [1., 2]}, index=exp_idx)
assert_frame_equal(result, expected)

def test_to_frame_na_drop_warnings(self):
def create_a_panel_with_na_vals(filter_observations=True):
df1 = DataFrame(np.random.randn(2, 3), columns=['A', 'B', 'C'],
index=['foo', 'bar'])
df2 = DataFrame(np.random.randn(2, 3), columns=['A', 'B', 'C'],
index=['foo', 'bar'])
df2.loc['foo', 'B'] = np.nan
dict_with_dropped_vals = {'df1': df1, 'df2': df2}
Panel(dict_with_dropped_vals).\
to_frame(filter_observations=filter_observations)

def create_a_panel_without_na_vals(filter_observations=True):
df1 = DataFrame(np.random.randn(2, 3), columns=['A', 'B', 'C'],
index=['foo', 'bar'])
df2 = DataFrame(np.random.randn(2, 3), columns=['A', 'B', 'C'],
index=['foo', 'bar'])
dict_with_dropped_vals = {'df1': df1, 'df2': df2}
Panel(dict_with_dropped_vals).\
to_frame(filter_observations=filter_observations)
with warnings.catch_warnings(record=True) as w:
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We have a context manger called assert_produces_warning in pandas/util/testing (usually imported as tm).

You can call it like

with tm.assert_produces_warning(RuntimeWarning):
    panel.to_frame()

then break each of your test cases into to separate lines. You can also check that a warning isn't raised with

with tm.assert_produces_warning(False)

warnings.simplefilter("always")
create_a_panel_with_na_vals()
create_a_panel_with_na_vals(False)
create_a_panel_without_na_vals()
create_a_panel_without_na_vals(False)
self.assertEqual(len(w), 1)
self.assertTrue(issubclass(w[0].category, RuntimeWarning))
self.assertEqual(str(w[0].message),
"NaN values found, empty values will be dropped")

def test_to_panel_na_handling(self):
df = DataFrame(np.random.randint(0, 10, size=20).reshape((10, 2)),
index=[[0, 0, 0, 0, 0, 0, 1, 1, 1, 1],
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