@@ -241,17 +241,47 @@ class DataFrame(NDFrame):
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Column labels to use for resulting frame. Will default to
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np.arange(n) if no column labels are provided
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dtype : dtype, default None
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- Data type to force, otherwise infer
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+ Data type to force. Only a single dtype is allowed. If None, infer
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copy : boolean, default False
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Copy data from inputs. Only affects DataFrame / 2d ndarray input
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Examples
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--------
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- >>> d = {'col1': ts1, 'col2': ts2}
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- >>> df = DataFrame(data=d, index=index)
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- >>> df2 = DataFrame(np.random.randn(10, 5))
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- >>> df3 = DataFrame(np.random.randn(10, 5),
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- ... columns=['a', 'b', 'c', 'd', 'e'])
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+ Constructing DataFrame from a dictionary.
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+
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+ >>> d = {'col1': [1, 2], 'col2': [3, 4]}
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+ >>> df = pd.DataFrame(data=d)
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+ >>> df
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+ col1 col2
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+ 0 1 3
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+ 1 2 4
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+
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+ Notice that the inferred dtype is int64.
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+
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+ >>> df.dtypes
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+ col1 int64
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+ col2 int64
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+ dtype: object
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+
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+ To enforce a single dtype:
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+
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+ >>> df = pd.DataFrame(data=d, dtype=np.int8)
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+ >>> df.dtypes
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+ col1 int8
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+ col2 int8
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+ dtype: object
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+
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+ Constructing DataFrame from numpy ndarray:
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+
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+ >>> df2 = pd.DataFrame(np.random.randint(low=0, high=10, size=(5, 5)),
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+ ... columns=['a', 'b', 'c', 'd', 'e'])
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+ >>> df2
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+ a b c d e
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+ 0 2 8 8 3 4
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+ 1 4 2 9 0 9
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+ 2 1 0 7 8 0
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+ 3 5 1 7 1 3
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+ 4 6 0 2 4 2
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See also
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--------
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