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I am doing Data-Wrangling in big data-set and there are many columns containing invalid values like Unspecified, 0 Unspecified and so on so, my goal is to replace them with NaN value so that I can easily decide which column is useless or which are not by their ratio of total NaN values respective total value rows. So, I am able to replace one value at a time and I want to do this all at a time as once

here is my code for replacing a value

for columns in cutmr_df.columns.values:
    cutmr_df[columns] = cutmr_df.replace('Unspecified', np.nan)

I even have tried this too but I am getting error

for columns in cutmr_df.columns.values:
    cutmr_df[columns] = cutmr_df.replace({columns: {'Unspecified': np.nan, '0 Unspecified': np.nan}})

#---------------------ERROR--------------------------#
Cannot compare types 'ndarray(dtype=int64)' and 'str'

So, How I should do this task

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