How can i get the top smallest and top highest value for each row in pandas?

[mahmoudr899]

I have data that I have sorted, below is a sample of the data:

Output:
    missing_values	count
    0		                51
    3		                1
    12		                12
    13		                1
    15		                1
    16		                1
    21		                1
    35		                2
    36		                3
    40		                1

I have the following code:

# Get the vount of each missing value
missing_value_count = missing_values.iloc[:, 0:1].value_counts().to_frame()
missing_value_count.sort_index(inplace=True)

missing_value_count.to_csv('question.csv')
        
missing_value_count.agg(lambda s: pd.Series([*s.nlargest().index, *s.nsmallest().index],
                           ['missing_values']),
                           axis='columns')

When I run the code I get the following error:

Output:
missing_value_count.agg(lambda s: pd.Series([*s.nlargest().index, *s.nsmallest().index],
                           ['missing_values']),
                           axis='columns')
    Traceback (most recent call last):

      Cell In[29], line 1
    missing_value_count.agg(lambda s: pd.Series([*s.nlargest().index, *s.nsmallest().index],

      File D:\Users\Mahmoud\anaconda3\Lib\site-packages\pandas\core\frame.py:9196 in aggregate
    result = op.agg()

      File D:\Users\Mahmoud\anaconda3\Lib\site-packages\pandas\core\apply.py:699 in agg
    result = self.obj.apply(self.orig_f, axis, args=self.args, **self.kwargs)

      File D:\Users\Mahmoud\anaconda3\Lib\site-packages\pandas\core\frame.py:9423 in apply
    return op.apply().__finalize__(self, method="apply")

      File D:\Users\Mahmoud\anaconda3\Lib\site-packages\pandas\core\apply.py:678 in apply
    return self.apply_standard()

      File D:\Users\Mahmoud\anaconda3\Lib\site-packages\pandas\core\apply.py:798 in apply_standard
    results, res_index = self.apply_series_generator()

      File D:\Users\Mahmoud\anaconda3\Lib\site-packages\pandas\core\apply.py:814 in apply_series_generator
    results[i] = self.f(v)

      Cell In[29], line 1 in <lambda>
    missing_value_count.agg(lambda s: pd.Series([*s.nlargest().index, *s.nsmallest().index],

      File D:\Users\Mahmoud\anaconda3\Lib\site-packages\pandas\core\series.py:500 in __init__
    com.require_length_match(data, index)

      File D:\Users\Mahmoud\anaconda3\Lib\site-packages\pandas\core\common.py:576 in require_length_match
    raise ValueError(

    ValueError: Length of values (2) does not match length of index (1)

I want to return the lowest value in missing_values with the highest values in count. So in the above data the result will be

Output:
    missing_values      count
    0                          51

How can I modify this part of the code to get the result I want?

missing_value_count.agg(lambda s: pd.Series([*s.nlargest().index, *s.nsmallest().index],
                           ['missing_values']),
                           axis='columns')