Pandas “diff()” with string

I get better performance with ne instead of using the actual != comparison:

df['changed'] = df['ColumnB'].ne(df['ColumnB'].shift().bfill()).astype(int)

Timings

Using the following setup to produce a larger dataframe:

df = pd.concat([df]*10**5, ignore_index=True) 

I get the following timings:

%timeit df['ColumnB'].ne(df['ColumnB'].shift().bfill()).astype(int)
10 loops, best of 3: 38.1 ms per loop

%timeit (df.ColumnB != df.ColumnB.shift()).astype(int)
10 loops, best of 3: 77.7 ms per loop

%timeit df['ColumnB'] == df['ColumnB'].shift(1).fillna(df['ColumnB'])
10 loops, best of 3: 99.6 ms per loop

%timeit (df.ColumnB.ne(df.ColumnB.shift())).astype(int)
10 loops, best of 3: 19.3 ms per loop