从字典内的字符串数组中删除nan

Here is a simple way to do what you're asking:

test_dict = {key: np.array([v for v in values if v is not np.nan]) for key, values in sdg_keywords_dict.items()}

Output:

{'test1': array(['a', 'b', 'c', 'd', 'e', 'f', 'g '], dtype=object)}

Note that if your values were numeric, you could use np.isnan() for vectorized boolean indexing like this:

sdg_keywords_dict = {'test1': np.array([1,2,3,4,5,6,np.nan,7])}
test_dict = {key: values[~np.isnan(values)] for key, values in sdg_keywords_dict.items()}

Input: {'test1': array([ 1., 2., 3., 4., 5., 6., nan, 7.])}

Output: {'test1': array([1., 2., 3., 4., 5., 6., 7.])}

However, the presence of elements of type str in your array means that np.isnan() will raise an exception:

TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''