Respond to comments from jreback

Author: invisibleroads

ci/requirements-2.6.txt

@@ -14,4 +14,3 @@ numexpr=1.4.2
 pymysql=0.6.0
 sqlalchemy=0.7.8
 xlsxwriter=0.4.6
-blosc

ci/requirements-2.7.txt

@@ -23,4 +23,3 @@ beautiful-soup=4.2.1
 httplib2=0.8
 python-gflags=2.0
 google-api-python-client=1.2
-blosc

ci/requirements-2.7_32.txt

@@ -9,4 +9,3 @@ matplotlib
 openpyxl
 xlrd
 scipy
-blosc

ci/requirements-2.7_64.txt

@@ -9,4 +9,3 @@ matplotlib
 openpyxl
 xlrd
 scipy
-blosc

ci/requirements-2.7_LOCALE.txt

@@ -16,4 +16,3 @@ scipy=0.11.0
 beautiful-soup=4.2.1
 statsmodels=0.4.3
 bigquery=2.0.17
-blosc

ci/requirements-2.7_SLOW.txt

@@ -23,4 +23,3 @@ beautiful-soup
 httplib2
 python-gflags
 google-api-python-client
-blosc

ci/requirements-3.2.txt

@@ -13,4 +13,3 @@ html5lib
 scipy==0.12.0
 beautifulsoup4==4.2.1
 statsmodels==0.5.0
-blosc

ci/requirements-3.3.txt

@@ -15,4 +15,3 @@ lxml=3.2.1
 scipy
 beautiful-soup=4.2.1
 statsmodels
-blosc

ci/requirements-3.4.txt

@@ -17,4 +17,3 @@ sqlalchemy
 bottleneck
 pymysql==0.6.3
 psycopg2
-blosc

ci/requirements-3.4_32.txt

@@ -8,4 +8,3 @@ scipy
 numexpr
 pytables
 matplotlib
-blosc

ci/requirements-3.4_64.txt

@@ -8,4 +8,3 @@ scipy
 numexpr
 pytables
 matplotlib
-blosc

ci/requirements-3.4_SLOW.txt

@@ -17,4 +17,3 @@ sqlalchemy
 bottleneck
 pymysql
 psycopg2
-blosc

ci/script.sh

@@ -16,7 +16,7 @@ fi
 "$TRAVIS_BUILD_DIR"/ci/build_docs.sh 2>&1 > /tmp/doc.log &
 # doc build log will be shown after tests
 
-pip install -U blosc
+pip install -U blosc  # See https://github.com/pydata/pandas/pull/9783
 python -c 'import blosc; blosc.print_versions()'
 
 echo nosetests --exe -A "$NOSE_ARGS" pandas --with-xunit --xunit-file=/tmp/nosetests.xml

pandas/io/tests/test_packers.py

@@ -447,18 +447,22 @@ def test_sparse_panel(self):
 
 
 class TestCompression(TestPackers):
+    """See https://github.com/pydata/pandas/pull/9783
+    """
 
     def setUp(self):
         super(TestCompression, self).setUp()
         data = {
-            'A': np.arange(1000, dtype=float),
-            'B': range(1000),
+            'A': np.arange(1000, dtype=np.float64),
+            'B': np.arange(1000, dtype=np.int32),
             'C': list(100 * 'abcdefghij'),
+            'D': date_range(datetime.datetime(2015, 4, 1), periods=1000),
+            'E': [datetime.timedelta(days=x) for x in range(1000)],
         }
         self.frame = {
-            'float': DataFrame(dict([(k, data[k]) for k in ['A', 'A']])),
-            'int': DataFrame(dict([(k, data[k]) for k in ['B', 'B']])),
-            'mixed': DataFrame(dict([(k, data[k]) for k in ['A', 'B', 'C']])),
+            'float': DataFrame(dict((k, data[k]) for k in ['A', 'A'])),
+            'int': DataFrame(dict((k, data[k]) for k in ['B', 'B'])),
+            'mixed': DataFrame(data),
         }
 
     def test_plain(self):