Extracting values after a split to create a new column with a yes or no in Python

Hello, I am new to coding and am currently working on some data cleaning using Python and I am trying to break apart my data so that I can perform some better analysis. I currently have a few columns that contain multiple strings within one column. For example, one column is the comorbidities of a patient and some patients have multiple comorbidities within that one column. I am trying to split the data, which are strings, so that there is a new column with a simple yes/no or 1/0 for each patient. I am unable to post pictures so I recreated the tables.

Currently I have one column that has multiple strings contained within it. I split the column using:
df1 = pd.concat((df, df['comorbidities'].str.split(',', expand = True)), axis = 1, ignore_index = True)

The resulting dataframe looks like this:

After this, I am trying to take the split strings and create a new column that will contain either yes/no or 1/0. So that each sample will be able to tell me if they have this or not. Any suggestions as to how to do this? I have tried groupby on just one column, and on all the columns and it does not work. I can't share the actual data but I created a dummy dataset with an example and the output I want below.

For example, what I am trying to do is take hypertension and create a new column with the name hypertension, and a simple yes/no or 1/0 for each sampleID. Any suggestions would be greatly appreciated!

Use str.get_dummies combined with replace and join:

out = df.join(df['comorbidities'].str.get_dummies(', ')
                                 .replace({0: 'no', 1: 'yes'}))

Output:

  sampleID           comorbidities  CHD asthma diabetes hypertension
0      P01  hypertension, diabetes   no     no      yes          yes
1      P02  hypertension, diabetes   no     no      yes          yes
2      P03                diabetes   no     no      yes           no
3      P04             CHD, asthma  yes    yes       no           no
4      P05    asthma, hypertension   no    yes       no          yes