Count appearances of a value until it changes to another value

Question

I have the following DataFrame:

df = pd.DataFrame([10, 10, 23, 23, 9, 9, 9, 10, 10, 10, 10, 12], columns=[\'values\'])

I want to calculate

Answer 1

Using crosstab

df['key']=df['values'].diff().ne(0).cumsum()
pd.crosstab(df['key'],df['values'])
Out[353]: 
values  9   10  12  23
key                   
1        0   2   0   0
2        0   0   0   2
3        3   0   0   0
4        0   4   0   0
5        0   0   1   0

Slightly modify the result above

pd.crosstab(df['key'],df['values']).stack().loc[lambda x:x.ne(0)]
Out[355]: 
key  values
1    10        2
2    23        2
3    9         3
4    10        4
5    12        1
dtype: int64

---

Base on python groupby

from itertools import groupby

[ (k,len(list(g))) for k,g in groupby(df['values'].tolist())]
Out[366]: [(10, 2), (23, 2), (9, 3), (10, 4), (12, 1)]