Python 如何使用df.iterrows（）匹配同一列中的上一行值？

我正在尝试使用索引编号将前一行值与特定值匹配。 但我不知道如何实现这一点。 你能帮我怎么做吗

例如：

operator_type   Operator
    =            None
    =            AND
    =            None
    =            OR
    =            None
    =            None

我正在尝试的代码：

for index, row in df.iterrows():
       if row['Operator'] == None and row['operator_type'] == '=' and row['Operator'].(index-1).values != 'AND':
             print('alka')

错误：

File "imed_cons_new.py", line 68
    if row['and_or_not_oprtor'] == None and row['operator_type'] == '=' and row['and_or_not_oprtor'].(index-1).values != 'AND':
                                                                                                     ^
SyntaxError: invalid syntax

你应该试试“shift（）”

输出：

0 alka
4 alka
5 alka

---

您可以尝试矢量化解决方案：

np.where((df['operator'].isna()) & (df['operator'].shift() != 'AND') & (df['operator_type'] == '='))[0]

结果是：

pd.DataFrame({'type':'alka'}, 
             index=np.where((df['operator'].isna()) & (df['operator'].shift() != 'AND') & (df['operator_type'] == '='))[0])

OUT:
  type
0 alka
4 alka
5 alka

---

正如错误所说，这只是语法错误。有更好的方法来做你想做的事情，但现在只需做以下改变

   if row['Operator'] == None and row['operator_type'] == '=' and row['Operator'].(index-1).values != 'AND':

到

   if row['Operator'] == None and row['operator_type'] == '=' and row['Operator'].(index-1).values != 'AND':

   if row['Operator'] == None and row['operator_type'] == '=' and row['Operator'][index-1]  != 'AND':