extract data with special value

Question

I have a dataset like:

df = pd.DataFrame({'scientist':["Wendelaar Bonga"," Sjoerd E.", "Grätzel"," Michael", "Willett", "Walter C.",
                             "Kessler", "Ronald C.", "Witten, Edward", "Wang, Zhong Lin"],
               'SubjectField': ["Biomedical Engineering", "Inorganic & Nuclear Chemistry",
                                "Organic Chemistry", "Biomedical Engineering", "Developmental Biology",
                                "Mechanical Engineering & Transports", "Biomedical Engineering", "Microbiology",
                                "Cardiovascular System & Hematology", "Biomedical Engineering"]})

I want to count the number of scientists in each subject field and extract subject fields that have more than 2 scientists. this is my code to count the number of scientists

 number_of_scientists_in_fields=data.groupby(['SubjectField'])['scientist'].count()

how can I extract subject fields that have more than 2 scientists?

Answer 1

Use value_counts, as follows:

fields = df.value_counts('SubjectField').to_frame('count')
res = fields[fields['count'] > 2]
print(res)

Output

                        count
SubjectField                 
Biomedical Engineering      4