Python 如何从pandas数据帧生成Django模型

我有一个包含3300多行的csv文件，描述了数据库结构。我正在使用pandas.read_csv（）进行解析。 下面是我的文件的一个小示例（第一行是标题）：

要创建用户界面，我更喜欢Django及其方便的ORM

目前，我面临着从DataFrame生成Django模型的问题，我已经可以选择了。 有什么方法可以轻松做到这一点吗？我不想重新发明轮子

"Variable / Field Name","Form Name","Section Header","Field Type","Field Label","Choices, Calculations, OR Slider Labels","Field Note","Text Validation Type OR Show Slider Number","Text Validation Min","Text Validation Max",Identifier?,"Branching Logic (Show field only if...)","Required Field?","Custom Alignment","Question Number (surveys only)","Matrix Group Name","Matrix Ranking?"
participant_id,participant_information,,text,"Participant ID",,,,,,y,,,,,,
dob,participant_information,,text,"Date of birth",,,date_dmy,,,y,,y,,,,
pi_completeness,participant_information,,dropdown,"Record Completeness","1,1 Complete | 2,2 Incomplete - followup (specify) | 3,3 Incomplete - no followup (specify) | 4,4 Declined (specify) | 5,5 No data - missed window | 6,6 No data - child (specify) | 7,7 No data - parent (specify) | 8,8 No data - equipment (specify) | 9,9 No data - experimenter (specify) | 10,10 No data - other (specify) | 11,11 NA - pilot | 12,12 NA - other (specify)",,,,,,,,,,,