python - Select rows containing certain values from pandas dataframe -

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i have pandas dataframe entries strings:

       b      c 1 apple  banana pear 2 pear   pear   apple 3 banana pear   pear 4 apple  apple  pear

etc. want select rows contain string, say, 'banana'. don't know column appear in each time. of course, can write loop , iterate on rows. there easier or faster way this?

with numpy, vectorized search many strings wish, -

def select_rows(df,search_strings):     unq,ids = np.unique(df,return_inverse=true)     unqids = np.searchsorted(unq,search_strings)     return df[((ids.reshape(df.shape) == unqids[:,none,none]).any(-1)).all(0)]

sample run -

in [393]: df out[393]:                b      c 0   apple  banana   pear 1    pear    pear  apple 2  banana    pear   pear 3   apple   apple   pear  in [394]: select_rows(df,['apple','banana']) out[394]:               b     c 0  apple  banana  pear  in [395]: select_rows(df,['apple','pear']) out[395]:               b      c 0  apple  banana   pear 1   pear    pear  apple 3  apple   apple   pear  in [396]: select_rows(df,['apple','banana','pear']) out[396]:               b     c 0  apple  banana  pear

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