What is the fastest way to select rows that contain a value in a Pandas dataframe?

You can testing the speed

boolfilter=(np.char.find(df.values.ravel().astype(str),'b')!=-1).reshape(df.shape).any(1)
boolfilter
array([False,  True,  True])
newdf=df[boolfilter]

One trivial possibility is to disable regex:

res = df[df.apply(lambda r: r.str.contains('b', case=False, regex=False).any(), axis=1)] 

Another way using a list comprehension:

res = df[[any('b' in x.lower() for x in row) for row in df.values)]]