Remove xfails and workarounds for datetime inputs into pygmt.info (#1236)

* Remove xfails on pygmt.info tests with a time column

Upstream bug resolved with GMT 6.2.0rc1 so the expected failure (xfail) decorators can be removed now.

* Remove coltypes="0T" workaround since datetime inputs to pygmt.info is ok now

Author: weiji14

pygmt/tests/test_info.py

@@ -55,19 +55,13 @@ def test_info_numpy_array_time_column():
     Make sure info works on a numpy.ndarray input with a datetime type.
     """
     table = pd.date_range(start="2020-01-01", periods=5).to_numpy()
-    # Please remove coltypes="0T" workaround after
-    # https://github.com/GenericMappingTools/gmt/issues/4241 is resolved
-    output = info(table=table, coltypes="0T")
+    output = info(table=table)
     expected_output = (
         "<vector memory>: N = 5 <2020-01-01T00:00:00/2020-01-05T00:00:00>\n"
     )
     assert output == expected_output
 
 
-@pytest.mark.xfail(
-    reason="UNIX timestamps returned instead of ISO datetime, should work on GMT 6.2.0 "
-    "after https://github.com/GenericMappingTools/gmt/issues/4241 is resolved",
-)
 def test_info_pandas_dataframe_time_column():
     """
     Make sure info works on pandas.DataFrame inputs with a time column.
@@ -85,10 +79,6 @@ def test_info_pandas_dataframe_time_column():
     assert output == expected_output
 
 
-@pytest.mark.xfail(
-    reason="UNIX timestamp returned instead of ISO datetime, should work on GMT 6.2.0 "
-    "after https://github.com/GenericMappingTools/gmt/issues/4241 is resolved",
-)
 def test_info_xarray_dataset_time_column():
     """
     Make sure info works on xarray.Dataset 1D inputs with a time column.
@@ -143,9 +133,7 @@ def test_info_per_column_with_time_inputs():
     Make sure the per_column option works with time inputs.
     """
     table = pd.date_range(start="2020-01-01", periods=5).to_numpy()
-    # Please remove coltypes="0T" workaround after
-    # https://github.com/GenericMappingTools/gmt/issues/4241 is resolved
-    output = info(table=table, per_column=True, coltypes="0T")
+    output = info(table=table, per_column=True)
     npt.assert_equal(
         actual=output, desired=["2020-01-01T00:00:00", "2020-01-05T00:00:00"]
     )