Fix tests using pd.datetime

pandas-dev · Dec 27, 2019 · 15d6e12 · 15d6e12
1 parent b45a47d
commit 15d6e12
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Showing 7 changed files with 13 additions and 10 deletions.
diff --git a/pandas/tests/api/test_api.py b/pandas/tests/api/test_api.py
@@ -93,7 +93,7 @@ class TestPDApi(Base):
     ]
     if not compat.PY37:
         classes.extend(["Panel", "SparseSeries", "SparseDataFrame"])
-        deprecated_modules.extend("datetime")
+        deprecated_modules.append("datetime")
 
     # these are already deprecated; awaiting removal
     deprecated_classes: List[str] = []

diff --git a/pandas/tests/dtypes/test_common.py b/pandas/tests/dtypes/test_common.py
@@ -1,3 +1,4 @@
+from datetime import datetime
 from typing import List
 
 import numpy as np
@@ -488,7 +489,7 @@ def test_is_numeric_v_string_like():
 
 
 def test_is_datetimelike_v_numeric():
-    dt = np.datetime64(pd.datetime(2017, 1, 1))
+    dt = np.datetime64(datetime(2017, 1, 1))
 
     assert not com.is_datetimelike_v_numeric(1, 1)
     assert not com.is_datetimelike_v_numeric(dt, dt)

diff --git a/pandas/tests/frame/indexing/test_indexing.py b/pandas/tests/frame/indexing/test_indexing.py
@@ -1146,18 +1146,18 @@ def test_setitem_mixed_datetime(self):
             {
                 "a": [0, 0, 0, 0, 13, 14],
                 "b": [
-                    pd.datetime(2012, 1, 1),
+                    datetime(2012, 1, 1),
                     1,
                     "x",
                     "y",
-                    pd.datetime(2013, 1, 1),
-                    pd.datetime(2014, 1, 1),
+                    datetime(2013, 1, 1),
+                    datetime(2014, 1, 1),
                 ],
             }
         )
         df = pd.DataFrame(0, columns=list("ab"), index=range(6))
         df["b"] = pd.NaT
-        df.loc[0, "b"] = pd.datetime(2012, 1, 1)
+        df.loc[0, "b"] = datetime(2012, 1, 1)
         df.loc[1, "b"] = 1
         df.loc[[2, 3], "b"] = "x", "y"
         A = np.array(

diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
@@ -1716,7 +1716,7 @@ def test_pivot_table_values_key_error():
     df = pd.DataFrame(
         {
             "eventDate": pd.date_range(
-                pd.datetime.today(), periods=20, freq="M"
+                datetime.today(), periods=20, freq="M"
             ).tolist(),
             "thename": range(0, 20),
         }

diff --git a/pandas/tests/indexing/test_iloc.py b/pandas/tests/indexing/test_iloc.py
@@ -1,5 +1,6 @@
 """ test positional based indexing with iloc """
 
+from datetime import datetime
 from warnings import catch_warnings, simplefilter
 
 import numpy as np
@@ -122,7 +123,7 @@ def check(result, expected):
         [
             ([slice(None), ["A", "D"]]),
             (["1", "2"], slice(None)),
-            ([pd.datetime(2019, 1, 1)], slice(None)),
+            ([datetime(2019, 1, 1)], slice(None)),
         ],
     )
     def test_iloc_non_integer_raises(self, index, columns, index_vals, column_vals):

diff --git a/pandas/tests/io/excel/test_writers.py b/pandas/tests/io/excel/test_writers.py
@@ -252,7 +252,7 @@ def test_read_excel_parse_dates(self, ext):
             res = pd.read_excel(pth, parse_dates=["date_strings"], index_col=0)
             tm.assert_frame_equal(df, res)
 
-            date_parser = lambda x: pd.datetime.strptime(x, "%m/%d/%Y")
+            date_parser = lambda x: datetime.strptime(x, "%m/%d/%Y")
             res = pd.read_excel(
                 pth, parse_dates=["date_strings"], date_parser=date_parser, index_col=0
             )

diff --git a/pandas/tests/io/sas/test_sas7bdat.py b/pandas/tests/io/sas/test_sas7bdat.py
@@ -1,3 +1,4 @@
+from datetime import datetime
 import io
 import os
 from pathlib import Path
@@ -23,7 +24,7 @@ def setup_method(self, datapath):
         for j in 1, 2:
             fname = os.path.join(self.dirpath, f"test_sas7bdat_{j}.csv")
             df = pd.read_csv(fname)
-            epoch = pd.datetime(1960, 1, 1)
+            epoch = datetime(1960, 1, 1)
             t1 = pd.to_timedelta(df["Column4"], unit="d")
             df["Column4"] = epoch + t1
             t2 = pd.to_timedelta(df["Column12"], unit="d")