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# Making Sure that only numbers are parsed through Data Frame def _contains_nan(a, nan_policy='propagate', use_summation=True): if not isinstance(a, np.ndarray): use_summation = False # some array_likes ignore nans (e.g. pandas) policies = ['propagate', 'raise', 'omit'] if nan_policy not in policies: raise ValueError("nan_policy must be one of {%s}" % ', '.join("'%s'" % s for s in policies)) def _isconst(x): y = x[~np.isnan(x)] if y.size == 0: return np.array([True]) else: return (y[0] == y).all(keepdims=True) def _quiet_nanmean(x): y = x[~np.isnan(x)] if y.size == 0: return np.array([np.nan]) else: return np.mean(y, keepdims=True) def _quiet_nanstd(x, ddof=0): y = x[~np.isnan(x)] if y.size == 0: return np.array([np.nan]) else: return np.std(y, keepdims=True, ddof=ddof) def _first(arr, axis): return np.take_along_axis(arr, np.array(0, ndmin=arr.ndim), axis) print("Function Generated to Handle NaN cases\n")
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