@@ -4232,7 +4232,55 @@ def as_matrix(self, columns=None):
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@property
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def values (self ):
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- """Numpy representation of NDFrame
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+ """
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+ Return a Numpy representation of the DataFrame.
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+
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+ Only the values in the DataFrame will be returned, the axes labels
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+ will be removed.
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+
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+ Returns
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+ -------
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+ numpy.ndarray
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+ The values of the DataFrame.
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+
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+ Examples
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+ --------
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+ A DataFrame where all columns are the same type (e.g., int64) results
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+ in an array of the same type.
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+
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+ >>> df = pd.DataFrame({'age': [ 3, 29],
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+ ... 'height': [94, 170],
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+ ... 'weight': [31, 115]})
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+ >>> df
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+ age height weight
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+ 0 3 94 31
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+ 1 29 170 115
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+ >>> df.dtypes
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+ age int64
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+ height int64
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+ weight int64
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+ dtype: object
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+ >>> df.values
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+ array([[ 3, 94, 31],
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+ [ 29, 170, 115]], dtype=int64)
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+
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+ A DataFrame with mixed type columns(e.g., str/object, int64, float32)
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+ results in an ndarray of the broadest type that accommodates these
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+ mixed types (e.g., object).
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+
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+ >>> df2 = pd.DataFrame([('parrot', 24.0, 'second'),
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+ ... ('lion', 80.5, 1),
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+ ... ('monkey', np.nan, None)],
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+ ... columns=('name', 'max_speed', 'rank'))
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+ >>> df2.dtypes
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+ name object
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+ max_speed float64
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+ rank object
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+ dtype: object
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+ >>> df2.values
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+ array([['parrot', 24.0, 'second'],
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+ ['lion', 80.5, 1],
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+ ['monkey', nan, None]], dtype=object)
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Notes
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-----
@@ -4243,8 +4291,13 @@ def values(self):
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e.g. If the dtypes are float16 and float32, dtype will be upcast to
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float32. If dtypes are int32 and uint8, dtype will be upcast to
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- int32. By numpy.find_common_type convention, mixing int64 and uint64
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- will result in a flot64 dtype.
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+ int32. By :func:`numpy.find_common_type` convention, mixing int64
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+ and uint64 will result in a float64 dtype.
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+
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+ See Also
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+ --------
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+ pandas.DataFrame.index : Retrievie the index labels
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+ pandas.DataFrame.columns : Retrieving the column names
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"""
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self ._consolidate_inplace ()
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return self ._data .as_array (transpose = self ._AXIS_REVERSED )
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