def _is_corr_matrix()

in python-package/lets_plot/bistro/corr.py [0:0]

• 30 lines of code
• 17 McCabe index (conditional complexity)

def _is_corr_matrix(data: Any):
    if is_pandas_data_frame(data):
        if data.shape[0] != data.shape[1]:
            return False

        if not (all(col_type == 'float64' for col_type in data.dtypes)):
            return False

        for column in data:
            import math
            if not all(math.isnan(v) or (1.0 >= v >= -1.0) for v in data[column]):
                return False

        return True

    elif isinstance(data, dict):
        m = len(data.keys())
        for column in data.values():
            if not isinstance(column, (list, tuple)):
                return False

            if len(column) != m:
                return False

            import math
            for v in column:
                if not isinstance(v, float):
                    return False

                if math.isnan(v):
                    return True

                if 1.0 >= v >= -1.0:
                    return True

                return False

            return True
    else:
        return False