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

The function groupby in itertools can help you, for str:

>>> string = 'aabbaacc'
>>> for char, freq in groupby('aabbaacc'):
>>>     print(char, len(list(freq)), sep=':', end='\n')
[out]:
    a:2
    b:2
    a:2
    c:2

This function also works for list:

>>> df = pd.DataFrame([10, 10, 23, 23, 9, 9, 9, 10, 10, 10, 10, 12], columns=['values'])
>>> for char, freq in groupby(df['values'].tolist()):
>>>     print(char, len(list(freq)), sep=':', end='\n')
[out]:
    10:2
    23:2
     9:3
    10:4
    12:1

Note: for df, you always use this way like df['values'] to take 'values' column, because DataFrame have a attribute values