How to calculate conditional probability of values in dataframe pandas-python?

Question

I want to calculate conditional probabilites of ratings(\'A\',\'B\',\'C\') in ratings column.

    company     model    rating   type
0   ford       mustang          


        

Answer 1

first, convert into a pandas dataframe. by doing so, you can take advantage of pandas' groupby methods.

collection = {"company": ["ford", "chevy", "ford", "ford", "ford", "toyota"],
              "model": ["mustang", "camaro", "fiesta", "focus", "taurus", "camry"],
              "rating": ["A", "B", "C", "A", "B", "B"],
              "type": ["coupe", "coupe", "sedan", "sedan", "sedan", "sedan"]}

df = pd.DataFrame(collection)

then, groupby based on events (ie rating).

df_s = df.groupby('rating')['type'].value_counts() / df.groupby('rating')['type'].count()
df_f = df_s.reset_index(name='cpt')
df_f.head()  # your conditional probability table