Source code for pandas_ta.statistics.zscore

# -*- coding: utf-8 -*-
from pandas_ta.overlap import sma
from .stdev import stdev
from pandas_ta.utils import get_offset, verify_series


def zscore(close, length=None, std=None, offset=None, **kwargs):
    """Indicator: Z Score"""
    # Validate Arguments
    length = int(length) if length and length > 1 else 30
    std = float(std) if std and std > 1 else 1
    close = verify_series(close, length)
    offset = get_offset(offset)

    if close is None: return

    # Calculate Result
    std *= stdev(close=close, length=length, **kwargs)
    mean = sma(close=close, length=length, **kwargs)
    zscore = (close - mean) / std

    # Offset
    if offset != 0:
        zscore = zscore.shift(offset)

    # Handle fills
    if "fillna" in kwargs:
        zscore.fillna(kwargs["fillna"], inplace=True)
    if "fill_method" in kwargs:
        zscore.fillna(method=kwargs["fill_method"], inplace=True)

    # Name & Category
    zscore.name = f"ZS_{length}"
    zscore.category = "statistics"

    return zscore


zscore.__doc__ = \
"""Rolling Z Score

Sources:

Calculation:
    Default Inputs:
        length=30, std=1
    SMA = Simple Moving Average
    STDEV = Standard Deviation
    std = std * STDEV(close, length)
    mean = SMA(close, length)
    ZSCORE = (close - mean) / std

Args:
    close (pd.Series): Series of 'close's
    length (int): It's period. Default: 30
    std (float): It's period. Default: 1
    offset (int): How many periods to offset the result. Default: 0

Kwargs:
    fillna (value, optional): pd.DataFrame.fillna(value)
    fill_method (value, optional): Type of fill method

Returns:
    pd.Series: New feature generated.
"""