pandas select row if value in another column changs

Question

Let's say I have a large data set that follows a similar structure:

where the id repeats multiple times. I would like to select any id where the value in column b changed with the desired output as such:

How might I be able to achieve that via pandas?

Please NEVER post dataframes as images, only as text and ideally as Python code to create the df, as in my answer below. Other useful tips here: https://stackoverflow.com/questions/20109391/how-to-make-good-reproducible-pandas-examples — piterbarg, Feb 24 '22 at 23:48

score 0 · Answer 1 · answered Feb 24 '22 at 23:47

It is not entirely clear what you are asking for. You say

I would like to select any id where the value in column b changed

but 'changed' from what?

Perhaps the following can be helpful -- it will show you all unique ColumnB strings for each id

Using a sample df:

df = pd.DataFrame({'id':[1,1,1,2,2,2,2], 'colb':['a','a','b','c','d','c','c']})

we use groupby and unique:

df.groupby('id')['colb'].unique().explode().to_frame()

output:


    colb
id  
1   a
1   b
2   c
2   d

so for id=1 we have a and b as unique phrases, and for id=2 we have c and d

1 Answers1