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I have a dataframe as follows:

 Company LT MT ST 0 XYZ A - - 1 XYZ A - B 2 XYZ - C B 3 ABC R - - 4 ABC R - B 5 DEF A B - 6 DEF A B B

what I want is to make a dataframe that can check whether company is duplicated or not and based on the duplication check for muliple columns LT, MT & ST. And if the values in these columns are repeatative than merge it onto single row entry for same company name. Output as follows:

 Company LT MT ST 0 XYZ A C B 1 ABC R - B 2 DEF A B B

I have tried with df.drop_duplicates() but it doesn't solve my problem.

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Use groupby and first with fillna

In [559]: (df.replace('-', np.nan) .groupby('Company', sort=False, as_index=False) .first() .fillna('-')) Out[559]: Company LT MT ST 0 XYZ A C B 1 ABC R - B 2 DEF A B B
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