TypeError: "value" parameter must be a scalar, dict or Series, but you passed a "Index"

df = df['Consequence Number'].fillna("CLS" + df.index.astype(str))

I did try the above solution along with iterating rows

 for index in priority_cls.iterrows():
     if priority_cls['Consequence Number'].isna() == True:
        priority_cls['Consequence Number'] = 'CLS00'+ str(priority_cls['ConsequenceNumber'].isnull().sum())

The error is as follows:

TypeError: "value" parameter must be a scalar, dict or Series, but you passed a "Index"

Convert your Index to_series:

df['Consequence Number'].fillna("CLS" + df.index.to_series().astype(str))

Example:

df = pd.DataFrame({'Consequence Number': ['A', 'B', pd.NA, pd.NA]})

df['out'] = (df['Consequence Number']
             .fillna("CLS" + df.index.to_series().astype(str))
            )

Output:

  Consequence Number   out
0                  A     A
1                  B     B
2               <NA>  CLS2
3               <NA>  CLS3