spotify_confidence/analysis/frequentist/confidence_computers/t_test_computer.py [27:40]:
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def point_estimate(df: DataFrame, **kwargs: Dict[str, str]) -> float:
    numerator = kwargs[NUMERATOR]
    denominator = kwargs[DENOMINATOR]
    if (df[denominator] == 0).any():
        raise ValueError("""Can't compute point estimate: denominator is 0""")
    return df[numerator] / df[denominator]


def variance(df: DataFrame, **kwargs: Dict[str, str]) -> float:
    numerator = kwargs[NUMERATOR]
    denominator = kwargs[DENOMINATOR]
    numerator_sumsq = kwargs[NUMERATOR_SUM_OF_SQUARES]
    binary = df[numerator_sumsq] == df[numerator]
    if binary.all():
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spotify_confidence/analysis/frequentist/confidence_computers/z_test_computer.py [56:69]:
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def point_estimate(df: DataFrame, **kwargs: Dict[str, str]) -> float:
    numerator = kwargs[NUMERATOR]
    denominator = kwargs[DENOMINATOR]
    if (df[denominator] == 0).any():
        raise ValueError("""Can't compute point estimate: denominator is 0""")
    return df[numerator] / df[denominator]


def variance(df: DataFrame, **kwargs: Dict[str, str]) -> float:
    numerator = kwargs[NUMERATOR]
    denominator = kwargs[DENOMINATOR]
    numerator_sumsq = kwargs[NUMERATOR_SUM_OF_SQUARES]
    binary = df[numerator_sumsq] == df[numerator]
    if binary.all():
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