Pandas "diff()" with string

Question

How can I flag a row in a dataframe every time a column change its string value?

Ex:

Input

ColumnA   ColumnB 1            Blue 2            Blue 3            Red 4            Red 5            Yellow   #  diff won't work here with strings....  only works in numerical values dataframe['changed'] = dataframe['ColumnB'].diff()           ColumnA   ColumnB      changed 1            Blue         0 2            Blue         0 3            Red          1 4            Red          0 5            Yellow       1 

Answer 1

Use .shift and compare:

dataframe['changed'] = dataframe['ColumnB'] == dataframe['ColumnB'].shift(1).fillna(dataframe['ColumnB']) 

Answer 2

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