熊猫:比较数据框架的列，并根据条件添加一个新的列&值

Question

我有一个数据框架，

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']}] 

由此产生的数据框架应该是，

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

"op_df“必须以以下条件为基础，

“value

• Condition”条件1:检查“详细信息”列中是否存在“类”和"sec“，如果存在，则添加一个名为"subjects”的新列及其各自的2:如果"details“列中不存在"class”和"sec“，则检查”类“是否匹配，如果匹配，则在”条件1“和条件2中添加一个名为"subjects”的新列及其各自的值
• ，在"subjects“列中添加默认值为0,0。

Answer 1

如果需要的话，解决方案首先由next和iter两种条件匹配值来添加默认值[0, 0]，如果没有匹配的话：

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