ezyquant.creator.SETSignalCreator.rank#

static SETSignalCreator.rank(factor_df: DataFrame, quantity: float | None = None, method: Literal['average', 'min', 'max', 'first', 'dense'] = 'first', ascending: bool = True, pct: bool = False)#

Compute numerical data ranks (1 through quantity) along axis.

Parameters:

  • factor_df (pd.DataFrame) – Dataframe of numerical data.

  • quantity (Optional[float] = None) – Number/Percentile of symbols to filter, filter out symbol will replace with nan. Default is None, which means rank all symbol.

  • method (str = "first") –

    How to rank the group of records that have the same value (i.e. ties):

    • average: average rank of the group

    • min: lowest rank in the group

    • max: highest rank in the group

    • first: ranks assigned in order they appear in the array

    • dense: like ‘min’, but rank always increases by 1 between groups.

  • ascending (bool = True) – Whether or not the elements should be ranked in ascending order.

  • pct (bool = False) – Whether or not to display the returned rankings in percentile form.

Return type:

pd.DataFrame with data ranks as values.

Examples

>>> from ezyquant import SETSignalCreator
>>> df = pd.DataFrame(
...     [
...         [11.0, 12.0, 13.0],
...         [21.0, float("nan"), 23.0],
...         [31.0, 31.0, 31.0],
...     ]
... )
>>> SETSignalCreator.rank(df)
     0    1    2
0  1.0  2.0  3.0
1  1.0  NaN  2.0
2  1.0  1.0  1.0