pyspark.pandas.DataFrame.xs¶
- 
DataFrame.xs(key: Union[Any, Tuple[Any, …]], axis: Union[int, str] = 0, level: Optional[int] = None) → Union[DataFrame, Series][source]¶
- Return cross-section from the DataFrame. - This method takes a key argument to select data at a particular level of a MultiIndex. - Parameters
- keylabel or tuple of label
- Label contained in the index, or partially in a MultiIndex. 
- axis0 or ‘index’, default 0
- Axis to retrieve cross-section on. currently only support 0 or ‘index’ 
- levelobject, defaults to first n levels (n=1 or len(key))
- In case of a key partially contained in a MultiIndex, indicate which levels are used. Levels can be referred by label or position. 
 
- Returns
- DataFrame or Series
- Cross-section from the original DataFrame corresponding to the selected index levels. 
 
 - See also - DataFrame.loc
- Access a group of rows and columns by label(s) or a boolean array. 
- DataFrame.iloc
- Purely integer-location based indexing for selection by position. 
 - Examples - >>> d = {'num_legs': [4, 4, 2, 2], ... 'num_wings': [0, 0, 2, 2], ... 'class': ['mammal', 'mammal', 'mammal', 'bird'], ... 'animal': ['cat', 'dog', 'bat', 'penguin'], ... 'locomotion': ['walks', 'walks', 'flies', 'walks']} >>> df = ps.DataFrame(data=d) >>> df = df.set_index(['class', 'animal', 'locomotion']) >>> df num_legs num_wings class animal locomotion mammal cat walks 4 0 dog walks 4 0 bat flies 2 2 bird penguin walks 2 2 - Get values at specified index - >>> df.xs('mammal') num_legs num_wings animal locomotion cat walks 4 0 dog walks 4 0 bat flies 2 2 - Get values at several indexes - >>> df.xs(('mammal', 'dog')) num_legs num_wings locomotion walks 4 0 - >>> df.xs(('mammal', 'dog', 'walks')) num_legs 4 num_wings 0 Name: (mammal, dog, walks), dtype: int64 - Get values at specified index and level - >>> df.xs('cat', level=1) num_legs num_wings class locomotion mammal walks 4 0