将包含三元组数据表 转为以某一维度的特征数据为列表头的csv - 数据转格式化处理

##############################
#统计特征SB下XX数据有几个，并保存


#适用于
#featureA   featureB  featureC
#SDF          345        TA
#SDF          976        TB
#KKj           3         TA
#KKj           43        TB


#想转为
#featureA   TA       TB
#SDF        345      976
#KKj        43        3
##############################

import pandas as pd
df=pd.read_csv('指定数据的文件名',encoding='utf8')

featureC=list(set(list(df['featureC'])))
print(featureC)

featureA_list = ['数据划分列表']

list_basic_featureC=featureC.copy()


head_str=[]

dic_basic_id={}

dic_use_id={}

for i in list_basic_featureC:
    strs_id ="可以自定义名称" +str(i)
    head_str.append(strs_id)
    dic_basic_id[i]=strs_id
    dic_use_id[i]=0



head_str.append('featureA')
Lists_tot = [head_str]
print(Lists_tot)

return_lists = featureC.copy()

for k in range(0,len(featureA_list)):
    Ts = return_lists.copy()
    Tdic = dic_use_id.copy()

    dfs=df[(df['brand']==featureA_list[k])]
    if not dfs.empty :
        #逐行遍历dataFrame
        for r,i in dfs.iterrows():
            featureB = i['featureB']
            featureC=i['featureC']
            Tdic[featureC]=featureB
        print(Tdic)
    for m in range(0,len(Ts)):
        Ts[m] = Tdic[return_lists[m]]

    Ts.append(featureA_list[k])

    Lists_tot.append(Ts)


print(Lists_tot)


import pandas as pd

dft = pd.DataFrame(Lists_tot[1:], columns=Lists_tot[0])
print(dft)
print("1")
dft.to_csv('输出文件结果', encoding='utf8', index=False)
print("~end~")