Pandas：比较数据框的列并根据条件添加新列和值

Question

我有一个数据框，

ip_df:
     name class    sec    details
0    tom  I        a      [{'class':'I','sec':'a','subjects':['numbers','ethics']},{'class':'I','sec':'b','subjects':['numbers','moral-science']},{'class':'I','sec':'c','subjects':['moral-science','ethics']},{'class':'I','subjects':['numbers','ethics1']}]
1    sam  I        d      [{'class':'I','sec':'a','subjects':['numbers','ethics']},{'class':'I','sec':'b','subjects':['numbers','moral-science']},{'class':'I','sec':'c','subjects':['moral-science','ethics']},{'class':'I','subjects':['numbers','ethics1']}] 

并且结果数据框应该是，

op_df:
      name  class  sec   subjects
0     tom   I      a     ['numbers','ethics']
1     sam   I      d     ['numbers','ethics1']

“op_df”必须根据以下条件进行构图，

• 条件1：检查“details”列中是否存在“class”和“sec”，如果存在，则添加一个名为“subjects”的新列及其各自的值
• 条件2：如果“details”列中不存在“class”和“sec”，检查“class”是否匹配，如果匹配，则添加一个名为“subjects”的新列及其各自的值
• 如果条件1和条件2都不存在，则在“subjects”列中添加默认值[0,0]

Answer 1

解决方案是否需要两个条件的第一个匹配值，如果没有匹配，则使用next和iter技巧添加默认值[0, 0] ：

final = []
for a, b, c in zip(df['class'], df['sec'], df['details']):
    out = []
    for x in c:
        m1 = x['class'] == a 
        if m1 and x.get('sec') == b:
            out.append(x['subjects'])
        elif m1 and 'sec' not in list(x.keys()):
            out.append(x['subjects'])
    final.append(next(iter(out), [0,0]))

df['subjects'] =  final