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# Set Operations
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Mathematical set operations for combining and comparing data frames using standard set theory operations.
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## Capabilities
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### Set Operation Functions
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```python { .api }
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def union(*frames) -> Frame:
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    """
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    Union of data frames (all unique rows from all frames).
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    Parameters:
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    - *frames: Frame objects to combine
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    Returns:
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    Frame with all unique rows from input frames
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    """
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def intersect(*frames) -> Frame:
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    """
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    Intersection of data frames (rows common to all frames).
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    Parameters:
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    - *frames: Frame objects to intersect
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    Returns:
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    Frame with rows present in all input frames
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    """
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def setdiff(frame1, frame2) -> Frame:
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    """
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    Set difference (rows in frame1 but not in frame2).
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    Parameters:
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    - frame1: First Frame
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    - frame2: Second Frame
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    Returns:
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    Frame with rows in frame1 that are not in frame2
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    """
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def symdiff(frame1, frame2) -> Frame:
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    """
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    Symmetric difference (rows in either frame but not both).
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    Parameters:
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    - frame1: First Frame
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    - frame2: Second Frame
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    Returns:
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    Frame with rows in either frame but not in both
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    """
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```
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## Examples
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```python
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import datatable as dt
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# Create sample frames
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A = dt.Frame({'x': [1, 2, 3], 'y': ['a', 'b', 'c']})
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B = dt.Frame({'x': [2, 3, 4], 'y': ['b', 'c', 'd']})
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C = dt.Frame({'x': [3, 4, 5], 'y': ['c', 'd', 'e']})
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# Union - all unique rows
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union_AB = dt.union(A, B)
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union_ABC = dt.union(A, B, C)
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# Intersection - common rows
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intersect_AB = dt.intersect(A, B)
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intersect_ABC = dt.intersect(A, B, C)
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# Set difference
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diff_AB = dt.setdiff(A, B)  # Rows in A but not B
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diff_BA = dt.setdiff(B, A)  # Rows in B but not A
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# Symmetric difference
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symdiff_AB = dt.symdiff(A, B)  # Rows in A or B but not both
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```