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https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
[DataFrame] MVP (1/4) (#1495)
* Implement __{getitem, delitem, copy, deepcopy}__
* Implement all(), any()
* Revert "Implement all(), any()"
This reverts commit 784052414f063662cdb30943297dc9ddfd3ca300.
* Address Comments + Fix axis indexing
* Update syntax for test_axes
* Implement bfill, bool, count
* Implement round
* Resolve bfill inplace issue
* Deimplement bfill; wait for the distributed version
* Fix format
* Copy df for __delitem__
This commit is contained in:
Simon Mo
Robert Nishihara
parent
b948405532
commit
0a79442954
2 changed files with 194 additions and 61 deletions
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@ -15,7 +15,8 @@ class DataFrame(object):
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Args:
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df ([ObjectID]): The list of ObjectIDs that contain the dataframe
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partitions.
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columns ([str]): The list of column names for this dataframe.
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columns (pandas.Index): The column names for this dataframe, in
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pandas Index object.
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"""
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assert(len(df) > 0)
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@ -36,7 +37,13 @@ class DataFrame(object):
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The union of all indexes across the partitions.
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"""
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indices = ray.get(self._map_partitions(lambda df: df.index)._df)
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return indices[0].append(indices[1:])
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if isinstance(indices[0], pd.RangeIndex):
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merged = indices[0]
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for index in indices[1:]:
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merged = merged.union(index)
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return merged
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else:
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return indices[0].append(indices[1:])
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@property
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def size(self):
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@ -346,11 +353,49 @@ class DataFrame(object):
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def all(self, axis=None, bool_only=None, skipna=None, level=None,
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**kwargs):
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raise NotImplementedError("Not Yet implemented.")
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"""Return whether all elements are True over requested axis
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Note:
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If axis=None or axis=0, this call applies df.all(axis=1)
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to the transpose of df.
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"""
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if axis is None or axis == 0:
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df = self.T
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axis = 1
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ordered_index = df.columns
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else:
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df = self
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ordered_index = df.index
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mapped = df._map_partitions(lambda df: df.all(axis,
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bool_only,
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skipna,
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level,
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**kwargs))
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return to_pandas(mapped)[ordered_index]
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def any(self, axis=None, bool_only=None, skipna=None, level=None,
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**kwargs):
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raise NotImplementedError("Not Yet implemented.")
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"""Return whether all elements are True over requested axis
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Note:
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If axis=None or axis=0, this call applies df.all(axis=1)
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to the transpose of df.
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"""
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if axis is None or axis == 0:
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df = self.T
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axis = 1
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ordered_index = df.columns
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else:
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df = self
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ordered_index = df.index
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mapped = df._map_partitions(lambda df: df.any(axis,
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bool_only,
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skipna,
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level,
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**kwargs))
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return to_pandas(mapped)[ordered_index]
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def append(self, other, ignore_index=False, verify_integrity=False):
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raise NotImplementedError("Not Yet implemented.")
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@ -389,7 +434,21 @@ class DataFrame(object):
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raise NotImplementedError("Not Yet implemented.")
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def bool(self):
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raise NotImplementedError("Not Yet implemented.")
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"""Return the bool of a single element PandasObject.
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This must be a boolean scalar value, either True or False. Raise a
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ValueError if the PandasObject does not have exactly 1 element, or that
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element is not boolean
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"""
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shape = self.shape
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if shape != (1,) and shape != (1, 1):
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raise ValueError("""The PandasObject does not have exactly
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1 element. Return the bool of a single
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element PandasObject. The truth value is
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ambiguous. Use a.empty, a.item(), a.any()
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or a.all().""")
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else:
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return to_pandas(self).bool()
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def boxplot(self, column=None, by=None, ax=None, fontsize=None, rot=0,
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grid=True, figsize=None, layout=None, return_type=None,
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@ -429,7 +488,15 @@ class DataFrame(object):
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raise NotImplementedError("Not Yet implemented.")
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def count(self, axis=0, level=None, numeric_only=False):
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raise NotImplementedError("Not Yet implemented.")
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if axis == 1:
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original_index = self.index
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return self.T.count(axis=0,
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level=level,
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numeric_only=numeric_only)[original_index]
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else:
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return sum(ray.get(self._map_partitions(lambda df: df.count(
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axis=axis, level=level, numeric_only=numeric_only
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))._df))
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def cov(self, min_periods=None):
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raise NotImplementedError("Not Yet implemented.")
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@ -784,7 +851,9 @@ class DataFrame(object):
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raise NotImplementedError("Not Yet implemented.")
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def round(self, decimals=0, *args, **kwargs):
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raise NotImplementedError("Not Yet implemented.")
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return self._map_partitions(lambda df: df.round(decimals=decimals,
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*args,
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**kwargs))
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def rpow(self, other, axis='columns', level=None, fill_value=None):
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raise NotImplementedError("Not Yet implemented.")
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@ -1008,7 +1077,17 @@ class DataFrame(object):
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raise NotImplementedError("Not Yet implemented.")
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def __getitem__(self, key):
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raise NotImplementedError("Not Yet implemented.")
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"""Get the column specified by key for this DataFrame.
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Args:
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key : The column name.
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Returns:
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A Pandas Series representing the value fo the column.
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"""
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result_column_chunks = self._map_partitions(
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lambda df: df.__getitem__(key))
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return to_pandas(result_column_chunks)
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def __setitem__(self, key, value):
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raise NotImplementedError("Not Yet implemented.")
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@ -1056,16 +1135,44 @@ class DataFrame(object):
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raise NotImplementedError("Not Yet implemented.")
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def __delitem__(self, key):
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raise NotImplementedError("Not Yet implemented.")
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"""Delete an item by key. `del a[key]` for example.
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Operation happnes in place.
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Args:
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key: key to delete
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"""
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def del_helper(df):
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df.__delitem__(key)
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return df
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self._df = self._map_partitions(del_helper)._df
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self.columns = self.columns.drop(key)
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def __finalize__(self, other, method=None, **kwargs):
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raise NotImplementedError("Not Yet implemented.")
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def __copy__(self, deep=True):
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raise NotImplementedError("Not Yet implemented.")
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"""Make a copy using Ray.DataFrame.copy method
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Args:
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deep: Boolean, deep copy or not.
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Currently we do not support deep copy.
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Returns:
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A Ray DataFrame object.
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"""
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return self.copy(deep=deep)
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def __deepcopy__(self, memo=None):
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raise NotImplementedError("Not Yet implemented.")
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"""Make a -deep- copy using Ray.DataFrame.copy method
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This is equivalent to copy(deep=True).
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Args:
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memo: No effect. Just to comply with Pandas API.
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Returns:
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A Ray DataFrame object.
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"""
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return self.copy(deep=True)
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def __and__(self, other):
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raise NotImplementedError("Not Yet implemented.")
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@ -1266,7 +1373,7 @@ def from_pandas(df, npartitions=None, chunksize=None, sort=True):
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def to_pandas(df):
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"""Converts a Ray DataFrame to a pandas DataFrame.
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"""Converts a Ray DataFrame to a pandas DataFrame/Series.
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Args:
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df (ray.DataFrame): The Ray DataFrame to convert.
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@ -46,7 +46,8 @@ def test_values(ray_df, pandas_df):
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@pytest.fixture
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def test_axes(ray_df, pandas_df):
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assert(np.array_equal(ray_df.axes, pandas_df.axes))
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for ray_axis, pd_axis in zip(ray_df.axes, pandas_df.axes):
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assert (np.array_equal(ray_axis, pd_axis))
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@pytest.fixture
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@ -113,7 +114,8 @@ def create_test_dataframe():
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df = pd.DataFrame({'col1': [0, 1, 2, 3],
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'col2': [4, 5, 6, 7],
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'col3': [8, 9, 10, 11],
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'col4': [12, 13, 14, 15]})
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'col4': [12, 13, 14, 15],
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'col5': [0, 0, 0, 0]})
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return rdf.from_pandas(df, 2)
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@ -124,8 +126,8 @@ def test_int_dataframe():
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pandas_df = pd.DataFrame({'col1': [0, 1, 2, 3],
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'col2': [4, 5, 6, 7],
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'col3': [8, 9, 10, 11],
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'col4': [12, 13, 14, 15]})
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'col4': [12, 13, 14, 15],
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'col5': [0, 0, 0, 0]})
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ray_df = rdf.from_pandas(pandas_df, 2)
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testfuncs = [lambda x: x + 1,
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@ -153,6 +155,16 @@ def test_int_dataframe():
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test_abs(ray_df, pandas_df)
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test_keys(ray_df, pandas_df)
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test_transpose(ray_df, pandas_df)
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test_round(ray_df, pandas_df)
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test_all(ray_df, pandas_df)
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test_any(ray_df, pandas_df)
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test___getitem__(ray_df, pandas_df)
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test___delitem__(ray_df, pandas_df)
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test___copy__(ray_df, pandas_df)
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test___deepcopy__(ray_df, pandas_df)
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test_bool(ray_df, pandas_df)
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test_count(ray_df, pandas_df)
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def test_float_dataframe():
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@ -160,7 +172,8 @@ def test_float_dataframe():
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pandas_df = pd.DataFrame({'col1': [0.0, 1.0, 2.0, 3.0],
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'col2': [4.0, 5.0, 6.0, 7.0],
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'col3': [8.0, 9.0, 10.0, 11.0],
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'col4': [12.0, 13.0, 14.0, 15.0]})
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'col4': [12.0, 13.0, 14.0, 15.0],
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'col5': [0.0, 0.0, 0.0, 0.0]})
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ray_df = rdf.from_pandas(pandas_df, 2)
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@ -189,6 +202,16 @@ def test_float_dataframe():
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test_abs(ray_df, pandas_df)
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test_keys(ray_df, pandas_df)
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test_transpose(ray_df, pandas_df)
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test_round(ray_df, pandas_df)
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test_all(ray_df, pandas_df)
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test_any(ray_df, pandas_df)
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test___getitem__(ray_df, pandas_df)
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test___delitem__(ray_df, pandas_df)
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test___copy__(ray_df, pandas_df)
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test___deepcopy__(ray_df, pandas_df)
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test_bool(ray_df, pandas_df)
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test_count(ray_df, pandas_df)
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def test_add():
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@ -219,18 +242,16 @@ def test_align():
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ray_df.align(None)
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def test_all():
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ray_df = create_test_dataframe()
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with pytest.raises(NotImplementedError):
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ray_df.all()
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@pytest.fixture
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def test_all(ray_df, pd_df):
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assert pd_df.all().equals(ray_df.all())
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assert pd_df.all(axis=1).equals(ray_df.all(axis=1))
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def test_any():
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ray_df = create_test_dataframe()
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with pytest.raises(NotImplementedError):
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ray_df.any()
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@pytest.fixture
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def test_any(ray_df, pd_df):
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assert pd_df.any().equals(ray_df.any())
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assert pd_df.any(axis=1).equals(ray_df.any(axis=1))
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def test_append():
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@ -307,14 +328,19 @@ def test_bfill():
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ray_df = create_test_dataframe()
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with pytest.raises(NotImplementedError):
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ray_df.bfill()
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ray_df.between_time(None, None)
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def test_bool():
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ray_df = create_test_dataframe()
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with pytest.raises(NotImplementedError):
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@pytest.fixture
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def test_bool(ray_df, pd_df):
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with pytest.raises(ValueError):
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ray_df.bool()
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pd_df.bool()
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single_bool_pd_df = pd.DataFrame([True])
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single_bool_ray_df = rdf.from_pandas(single_bool_pd_df, 1)
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assert single_bool_pd_df.bool() == single_bool_ray_df.bool()
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def test_boxplot():
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@ -394,11 +420,10 @@ def test_corrwith():
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ray_df.corrwith(None)
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def test_count():
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ray_df = create_test_dataframe()
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with pytest.raises(NotImplementedError):
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ray_df.count()
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@pytest.fixture
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def test_count(ray_df, pd_df):
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assert ray_df.count().equals(pd_df.count())
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assert ray_df.count(axis=1).equals(pd_df.count(axis=1))
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def test_cov():
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@ -1100,11 +1125,10 @@ def test_rolling():
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ray_df.rolling(None)
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def test_round():
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ray_df = create_test_dataframe()
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with pytest.raises(NotImplementedError):
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ray_df.round()
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@pytest.fixture
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def test_round(ray_df, pd_df):
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assert ray_df_equals_pandas(ray_df.round(), pd_df.round())
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assert ray_df_equals_pandas(ray_df.round(1), pd_df.round(1))
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def test_rpow():
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@ -1520,11 +1544,13 @@ def test_xs():
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ray_df.xs(None)
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def test___getitem__():
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ray_df = create_test_dataframe()
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@pytest.fixture
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def test___getitem__(ray_df, pd_df):
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ray_col = ray_df.__getitem__('col1')
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assert isinstance(ray_col, pd.Series)
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with pytest.raises(NotImplementedError):
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ray_df.__getitem__(None)
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pd_col = pd_df['col1']
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assert pd_col.equals(ray_col)
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def test___setitem__():
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@ -1639,11 +1665,13 @@ def test___setstate__():
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ray_df.__setstate__(None)
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def test___delitem__():
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ray_df = create_test_dataframe()
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with pytest.raises(NotImplementedError):
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ray_df.__delitem__(None)
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@pytest.fixture
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def test___delitem__(ray_df, pd_df):
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ray_df = ray_df.copy()
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pd_df = pd_df.copy()
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ray_df.__delitem__('col1')
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pd_df.__delitem__('col1')
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ray_df_equals_pandas(ray_df, pd_df)
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def test___finalize__():
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@ -1653,18 +1681,16 @@ def test___finalize__():
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ray_df.__finalize__(None)
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def test___copy__():
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ray_df = create_test_dataframe()
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with pytest.raises(NotImplementedError):
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ray_df.__copy__()
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@pytest.fixture
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def test___copy__(ray_df, pd_df):
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ray_df_copy, pd_df_copy = ray_df.__copy__(), pd_df.__copy__()
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assert ray_df_equals_pandas(ray_df_copy, pd_df_copy)
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def test___deepcopy__():
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ray_df = create_test_dataframe()
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with pytest.raises(NotImplementedError):
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ray_df.__deepcopy__()
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@pytest.fixture
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def test___deepcopy__(ray_df, pd_df):
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ray_df_copy, pd_df_copy = ray_df.__deepcopy__(), pd_df.__deepcopy__()
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assert ray_df_equals_pandas(ray_df_copy, pd_df_copy)
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def test_blocks():
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