ENH: added guards against bad interval data

Author: adamklein

pandas/core/datetools.py

@@ -287,6 +287,8 @@ def __init__(self, value=None, freq=None,
         elif isinstance(value, datetime):
             dt = value
         elif isinstance(value, (int, long)):
+            if value <= 0:
+                raise ValueError("Value must be positive")
             self.ordinal = value
         else:
             raise ValueError("Value must be string or datetime")

pandas/core/index.py

@@ -1951,6 +1951,9 @@ def __new__(cls, data=None,
                 else:
                     data = data.astype('i8')
 
+        if (data <= 0).any():
+            raise ValueError("Found illegal (<= 0) values in data")
+
         subarr = data.view(cls)
         subarr.name = name
         subarr.freq = freq

pandas/tests/test_interval.py

@@ -12,6 +12,8 @@
 from numpy.ma.testutils import assert_equal
 from pandas.core.datetools import Interval
 from pandas.core.index import IntervalIndex
+import pandas.core.datetools as datetools
+import numpy as np
 
 class TestIntervalProperties(TestCase):
     "Test properties such as year, month, weekday, etc...."
@@ -899,6 +901,13 @@ def test_resample(self):
         self.assertEquals(ii7.resample('H', 'S'), ii5)
         self.assertEquals(ii7.resample('Min', 'S'), ii6)
 
+    def test_badinput(self):
+        self.assertRaises(datetools.DateParseError, Interval, '1/1/-2000', 'A')
+        self.assertRaises(ValueError, Interval, -2000, 'A')
+        self.assertRaises(ValueError, Interval, 0, 'A')
+        self.assertRaises(ValueError, IntervalIndex, [-1, 0, 1], 'A')
+        self.assertRaises(ValueError, IntervalIndex, np.array([-1, 0, 1]), 'A')
+
 class TestMethods(TestCase):
     "Base test class for MaskedArrays."