Python PatsyError:数据参数之间的行数不匹配

我知道以前有人问过这个问题，但我找不到适合我具体情况的情况

我有以下代码：

list_of_responses =['Respiratory','GI_System','Systemic_Other','EXP_TEST_COVMEN_PUI_MISC','MED_ALERT_CPR_SHOCK_SEPSIS','Lymph_Node_Neck','Ear','Mouth_Sores','Eye','Cough','Nasal_Congestion','SOB_WOB_Hyp_Desat','PNA','Abdominal_Pain','Nausea','Vomiting','Diarrhea','Rash','Fever','Weak_Fatigue','Bodyaches','Dizziness','Fussy','Poor_PO_Dehydration','Tachycardia','COVID_Exposure','COVID_Test','COVID_PUI','CP','ST','HA','Wheezing_Asthma','Loss_Taste_Smell']


for cc in list_of_responses:
        reg_model = smf.logit("Covid_pos ~  cc + C(RACE_GROUP_N, Treatment(0)) + C(Age_Group_N, Treatment(0)) + C(Insurance_Type_Group, Treatment(0))",
            data = df_merged2).fit()
        reg_model_odds = pd.DataFrame(np.exp(reg_model.params), columns= ['OR'])
        reg_model_odds['z-value']= reg_model.pvalues
        reg_model_odds[['2.5%', '97.5%']] = np.exp(reg_model.conf_int())
        reg_model_odds['OR'] = round(reg_model_odds['OR'], 2)
        reg_model_odds['2.5%'] = round(reg_model_odds['2.5%'], 2)
        reg_model_odds['97.5%'] = round(reg_model_odds['97.5%'], 2)
        reg_model_odds["OR 95% CI"]= reg_model_odds['OR'].map(str)+' ('+reg_model_odds['2.5%'].map(str)+', '+reg_model_odds['97.5%'].map(str)+')'
        reg_model_oddsOR=reg_model_odds["OR 95% CI"]
        reg_model_oddsOR

运行此代码时，出现以下错误：

PatsyError: Number of rows mismatch between data argument and cc (5253 versus 1)
    Covid_pos ~  cc + C(RACE_GROUP_N, Treatment(0)) + C(Age_Group_N, Treatment(0)) + C(Insurance_Type_Group, Treatment(0))
                 ^^

我在以前的文章中看到，这可能是由于列的格式和公式，但我认为我的列似乎格式正确，公式是正确的。我不太确定我会错在哪里

这就是我的数据的样子：

ID   RACE_GROUP_N Age_Group_N... Covid_pos  Asymptomatic  Fever  Cough ...
0     1               0            1             0        1      0
1     0               2            0             0        0      1
2     3               3            1             1        0      0
3     2               1            1             0        1      0
4     3               2            0             1        0      0
5     0               4            1             0        1      0