STY: absolute imports

pandas/core/arrays/categorical.py

@@ -46,6 +46,11 @@
 from pandas.core.accessor import PandasDelegate, delegate_names
 import pandas.core.algorithms as algorithms
 from pandas.core.algorithms import _get_data_algo, factorize, take, take_1d, unique1d
+from pandas.core.arrays.base import (
+    ExtensionArray,
+    _extension_array_shared_docs,
+    try_cast_to_ea,
+)
 from pandas.core.base import NoNewAttributesMixin, PandasObject, _shared_docs
 import pandas.core.common as com
 from pandas.core.construction import array, extract_array, sanitize_array
@@ -56,8 +61,6 @@
 
 from pandas.io.formats import console
 
-from .base import ExtensionArray, _extension_array_shared_docs, try_cast_to_ea
-
 
 def _cat_compare_op(op):
     opname = f"__{op.__name__}__"

pandas/core/arrays/datetimelike.py

@@ -40,6 +40,7 @@
 
 from pandas.core import missing, nanops, ops
 from pandas.core.algorithms import checked_add_with_arr, take, unique1d, value_counts
+from pandas.core.arrays.base import ExtensionArray, ExtensionOpsMixin
 import pandas.core.common as com
 from pandas.core.indexers import check_bool_array_indexer
 from pandas.core.ops.common import unpack_zerodim_and_defer
@@ -48,8 +49,6 @@
 from pandas.tseries import frequencies
 from pandas.tseries.offsets import DateOffset, Tick
 
-from .base import ExtensionArray, ExtensionOpsMixin
-
 
 def _datetimelike_array_cmp(cls, op):
     """

pandas/core/arrays/numpy_.py

@@ -17,13 +17,12 @@
 from pandas import compat
 from pandas.core import nanops
 from pandas.core.algorithms import searchsorted, take, unique
+from pandas.core.arrays.base import ExtensionArray, ExtensionOpsMixin
 import pandas.core.common as com
 from pandas.core.construction import extract_array
 from pandas.core.indexers import check_bool_array_indexer
 from pandas.core.missing import backfill_1d, pad_1d
 
-from .base import ExtensionArray, ExtensionOpsMixin
-
 
 class PandasDtype(ExtensionDtype):
     """

pandas/core/arrays/sparse/array.py

@@ -39,6 +39,7 @@
 
 import pandas.core.algorithms as algos
 from pandas.core.arrays import ExtensionArray, ExtensionOpsMixin
+from pandas.core.arrays.sparse.dtype import SparseDtype
 from pandas.core.base import PandasObject
 import pandas.core.common as com
 from pandas.core.construction import sanitize_array
@@ -48,8 +49,6 @@
 
 import pandas.io.formats.printing as printing
 
-from .dtype import SparseDtype
-
 # ----------------------------------------------------------------------------
 # Array
 

pandas/core/arrays/sparse/dtype.py

@@ -175,7 +175,7 @@ def construct_array_type(cls):
         -------
         type
         """
-        from .array import SparseArray
+        from pandas.core.arrays.sparse.array import SparseArray
 
         return SparseArray
 

pandas/core/arrays/timedeltas.py

@@ -37,13 +37,12 @@
 
 from pandas.core import nanops
 from pandas.core.algorithms import checked_add_with_arr
+from pandas.core.arrays import datetimelike as dtl
 import pandas.core.common as com
 
 from pandas.tseries.frequencies import to_offset
 from pandas.tseries.offsets import Tick
 
-from . import datetimelike as dtl
-
 _BAD_DTYPE = "dtype {dtype} cannot be converted to timedelta64[ns]"
 
 

pandas/core/dtypes/api.py

@@ -1,6 +1,6 @@
 # flake8: noqa
 
-from .common import (
+from pandas.core.dtypes.common import (
     is_array_like,
     is_bool,
     is_bool_dtype,

pandas/core/dtypes/cast.py

@@ -9,7 +9,7 @@
 from pandas._libs.tslibs.timezones import tz_compare
 from pandas.util._validators import validate_bool_kwarg
 
-from .common import (
+from pandas.core.dtypes.common import (
     _INT64_DTYPE,
     _NS_DTYPE,
     _POSSIBLY_CAST_DTYPES,
@@ -42,17 +42,22 @@
     is_unsigned_integer_dtype,
     pandas_dtype,
 )
-from .dtypes import DatetimeTZDtype, ExtensionDtype, IntervalDtype, PeriodDtype
-from .generic import (
+from pandas.core.dtypes.dtypes import (
+    DatetimeTZDtype,
+    ExtensionDtype,
+    IntervalDtype,
+    PeriodDtype,
+)
+from pandas.core.dtypes.generic import (
     ABCDataFrame,
     ABCDatetimeArray,
     ABCDatetimeIndex,
     ABCPeriodArray,
     ABCPeriodIndex,
     ABCSeries,
 )
-from .inference import is_list_like
-from .missing import isna, notna
+from pandas.core.dtypes.inference import is_list_like
+from pandas.core.dtypes.missing import isna, notna
 
 _int8_max = np.iinfo(np.int8).max
 _int16_max = np.iinfo(np.int16).max

pandas/core/dtypes/dtypes.py

@@ -9,10 +9,9 @@
 from pandas._libs.tslibs import NaT, Period, Timestamp, timezones
 from pandas._typing import Ordered
 
+from pandas.core.dtypes.base import ExtensionDtype
 from pandas.core.dtypes.generic import ABCCategoricalIndex, ABCDateOffset, ABCIndexClass
-
-from .base import ExtensionDtype
-from .inference import is_bool, is_list_like
+from pandas.core.dtypes.inference import is_bool, is_list_like
 
 str_type = str
 

pandas/core/dtypes/missing.py

@@ -9,7 +9,7 @@
 import pandas._libs.missing as libmissing
 from pandas._libs.tslibs import NaT, iNaT
 
-from .common import (
+from pandas.core.dtypes.common import (
     _NS_DTYPE,
     _TD_DTYPE,
     ensure_object,
@@ -31,7 +31,7 @@
     needs_i8_conversion,
     pandas_dtype,
 )
-from .generic import (
+from pandas.core.dtypes.generic import (
     ABCDatetimeArray,
     ABCExtensionArray,
     ABCGeneric,
@@ -40,7 +40,7 @@
     ABCSeries,
     ABCTimedeltaArray,
 )
-from .inference import is_list_like
+from pandas.core.dtypes.inference import is_list_like
 
 isposinf_scalar = libmissing.isposinf_scalar
 isneginf_scalar = libmissing.isneginf_scalar

pandas/core/indexes/base.py

@@ -277,11 +277,11 @@ def __new__(
         cls, data=None, dtype=None, copy=False, name=None, tupleize_cols=True, **kwargs,
     ) -> "Index":
 
-        from .range import RangeIndex
+        from pandas.core.indexes.range import RangeIndex
         from pandas import PeriodIndex, DatetimeIndex, TimedeltaIndex
-        from .numeric import Float64Index, Int64Index, UInt64Index
-        from .interval import IntervalIndex
-        from .category import CategoricalIndex
+        from pandas.core.indexes.numeric import Float64Index, Int64Index, UInt64Index
+        from pandas.core.indexes.interval import IntervalIndex
+        from pandas.core.indexes.category import CategoricalIndex
 
         name = maybe_extract_name(name, data, cls)
 
@@ -408,7 +408,7 @@ def __new__(
                 if data and all(isinstance(e, tuple) for e in data):
                     # we must be all tuples, otherwise don't construct
                     # 10697
-                    from .multi import MultiIndex
+                    from pandas.core.indexes.multi import MultiIndex
 
                     return MultiIndex.from_tuples(
                         data, names=name or kwargs.get("names")
@@ -679,7 +679,7 @@ def astype(self, dtype, copy=True):
             return self.copy() if copy else self
 
         elif is_categorical_dtype(dtype):
-            from .category import CategoricalIndex
+            from pandas.core.indexes.category import CategoricalIndex
 
             return CategoricalIndex(self.values, name=self.name, dtype=dtype, copy=copy)
 
@@ -1514,7 +1514,7 @@ def droplevel(self, level=0):
             result._name = new_names[0]
             return result
         else:
-            from .multi import MultiIndex
+            from pandas.core.indexes.multi import MultiIndex
 
             return MultiIndex(
                 levels=new_levels,
@@ -3328,7 +3328,7 @@ def join(self, other, how="left", level=None, return_indexers=False, sort=False)
             return join_index
 
     def _join_multi(self, other, how, return_indexers=True):
-        from .multi import MultiIndex
+        from pandas.core.indexes.multi import MultiIndex
         from pandas.core.reshape.merge import _restore_dropped_levels_multijoin
 
         # figure out join names
@@ -3435,7 +3435,7 @@ def _join_level(
         MultiIndex will not be changed; otherwise, it will tie out
         with `other`.
         """
-        from .multi import MultiIndex
+        from pandas.core.indexes.multi import MultiIndex
 
         def _get_leaf_sorter(labels):
             """
@@ -4519,7 +4519,7 @@ def map(self, mapper, na_action=None):
             a MultiIndex will be returned.
         """
 
-        from .multi import MultiIndex
+        from pandas.core.indexes.multi import MultiIndex
 
         new_values = super()._map_values(mapper, na_action=na_action)
 
@@ -5240,7 +5240,7 @@ def ensure_index_from_sequences(sequences, names=None):
     --------
     ensure_index
     """
-    from .multi import MultiIndex
+    from pandas.core.indexes.multi import MultiIndex
 
     if len(sequences) == 1:
         if names is not None:
@@ -5301,7 +5301,7 @@ def ensure_index(index_like, copy=False):
         converted, all_arrays = lib.clean_index_list(index_like)
 
         if len(converted) > 0 and all_arrays:
-            from .multi import MultiIndex
+            from pandas.core.indexes.multi import MultiIndex
 
             return MultiIndex.from_arrays(converted)
         else:

pandas/core/indexes/datetimelike.py

@@ -40,18 +40,17 @@
 from pandas.core.arrays.datetimelike import DatetimeLikeArrayMixin
 import pandas.core.indexes.base as ibase
 from pandas.core.indexes.base import Index, _index_shared_docs
-from pandas.core.indexes.numeric import Int64Index
-from pandas.core.ops import get_op_result_name
-from pandas.core.tools.timedeltas import to_timedelta
-
-from pandas.tseries.frequencies import DateOffset, to_offset
-
-from .extension import (
+from pandas.core.indexes.extension import (
     ExtensionIndex,
     inherit_names,
     make_wrapped_arith_op,
     make_wrapped_comparison_op,
 )
+from pandas.core.indexes.numeric import Int64Index
+from pandas.core.ops import get_op_result_name
+from pandas.core.tools.timedeltas import to_timedelta
+
+from pandas.tseries.frequencies import DateOffset, to_offset
 
 _index_doc_kwargs = dict(ibase._index_doc_kwargs)
 

pandas/core/indexes/extension.py

@@ -10,10 +10,9 @@
 from pandas.core.dtypes.generic import ABCSeries
 
 from pandas.core.arrays import ExtensionArray
+from pandas.core.indexes.base import Index
 from pandas.core.ops import get_op_result_name
 
-from .base import Index
-
 
 def inherit_from_data(name: str, delegate, cache: bool = False):
     """

pandas/core/indexes/interval.py

@@ -51,16 +51,18 @@
     maybe_extract_name,
 )
 from pandas.core.indexes.datetimes import DatetimeIndex, date_range
-from pandas.core.indexes.extension import make_wrapped_comparison_op
+from pandas.core.indexes.extension import (
+    ExtensionIndex,
+    inherit_names,
+    make_wrapped_comparison_op,
+)
 from pandas.core.indexes.multi import MultiIndex
 from pandas.core.indexes.timedeltas import TimedeltaIndex, timedelta_range
 from pandas.core.ops import get_op_result_name
 
 from pandas.tseries.frequencies import to_offset
 from pandas.tseries.offsets import DateOffset
 
-from .extension import ExtensionIndex, inherit_names
-
 _VALID_CLOSED = {"left", "right", "both", "neither"}
 _index_doc_kwargs = dict(ibase._index_doc_kwargs)
 

pandas/core/indexes/multi.py

@@ -2931,7 +2931,7 @@ def get_locs(self, seq):
         >>> mi.get_locs([[True, False, True], slice('e', 'f')])  # doctest: +SKIP
         array([2], dtype=int64)
         """
-        from .numeric import Int64Index
+        from pandas.core.indexes.numeric import Int64Index
 
         # must be lexsorted to at least as many levels
         true_slices = [i for (i, s) in enumerate(com.is_true_slices(seq)) if s]

pandas/core/internals/managers.py

@@ -34,10 +34,7 @@
 from pandas.core.base import PandasObject
 from pandas.core.indexers import maybe_convert_indices
 from pandas.core.indexes.api import Index, MultiIndex, ensure_index
-
-from pandas.io.formats.printing import pprint_thing
-
-from .blocks import (
+from pandas.core.internals.blocks import (
     Block,
     CategoricalBlock,
     DatetimeTZBlock,
@@ -49,13 +46,15 @@
     get_block_type,
     make_block,
 )
-from .concat import (  # all for concatenate_block_managers
+from pandas.core.internals.concat import (  # all for concatenate_block_managers
     combine_concat_plans,
     concatenate_join_units,
     get_mgr_concatenation_plan,
     is_uniform_join_units,
 )
 
+from pandas.io.formats.printing import pprint_thing
+
 # TODO: flexible with index=None and/or items=None
 
 

pandas/core/ops/missing.py

@@ -27,7 +27,7 @@
 
 from pandas.core.dtypes.common import is_float_dtype, is_integer_dtype, is_scalar
 
-from .roperator import rdivmod, rfloordiv, rmod
+from pandas.core.ops.roperator import rdivmod, rfloordiv, rmod
 
 
 def fill_zeros(result, x, y):

pandas/io/json/_json.py

@@ -24,11 +24,10 @@
     infer_compression,
     stringify_path,
 )
+from pandas.io.json._normalize import convert_to_line_delimits
+from pandas.io.json._table_schema import build_table_schema, parse_table_schema
 from pandas.io.parsers import _validate_integer
 
-from ._normalize import convert_to_line_delimits
-from ._table_schema import build_table_schema, parse_table_schema
-
 loads = json.loads
 dumps = json.dumps