importing from top level pandas

Author: ryankarlos

pandas/core/reshape/concat.py

@@ -2,19 +2,17 @@
 concat routines
 """
 
-import numpy as np
-
 import pandas.core.dtypes.concat as _concat
 
-from pandas import compat
+from pandas import Index, MultiIndex, compat, np
 from pandas.core import common as com
 from pandas.core.arrays.categorical import (
     _factorize_from_iterable, _factorize_from_iterables)
 from pandas.core.frame import DataFrame
 from pandas.core.generic import NDFrame
 from pandas.core.index import (
-    Index, MultiIndex, _all_indexes_same, _get_consensus_names,
-    _get_objs_combined_axis, ensure_index)
+    _all_indexes_same, _get_consensus_names, _get_objs_combined_axis,
+    ensure_index)
 import pandas.core.indexes.base as ibase
 from pandas.core.internals import concatenate_block_managers
 from pandas.core.series import Series

pandas/core/reshape/tile.py

@@ -3,27 +3,19 @@
 """
 from functools import partial
 
-import numpy as np
-
 from pandas._libs.lib import infer_dtype
-from pandas._libs.tslibs.timedeltas import Timedelta
-from pandas._libs.tslibs.timestamps import Timestamp
 
 from pandas.core.dtypes.common import (
     _NS_DTYPE, ensure_int64, is_categorical_dtype, is_datetime64_dtype,
     is_datetime64tz_dtype, is_datetime_or_timedelta_dtype, is_integer,
     is_scalar, is_timedelta64_dtype)
-from pandas.core.dtypes.missing import isna
 
+from pandas import (
+    Categorical, Index, Interval, IntervalIndex, Timedelta, Timestamp, isna,
+    np, to_datetime, to_timedelta)
 import pandas.core.algorithms as algos
-from pandas.core.arrays.categorical import Categorical
-from pandas.core.arrays.interval import Interval
-from pandas.core.index import Index
-from pandas.core.indexes.interval import IntervalIndex
 import pandas.core.nanops as nanops
 from pandas.core.series import Series
-from pandas.core.tools.datetimes import to_datetime
-from pandas.core.tools.timedeltas import to_timedelta
 
 
 def cut(x, bins, right=True, labels=None, retbins=False, precision=3,