使用cumsum查找独特的章节

Question

我有这样一个数据帧：

df = pd.DataFrame()

  text      secFlag  
0  book     1 
1  headings 1 
2  chapter  1 
3  one      1
4  page     0 
5  one      0
6  text     0
7  chapter   1 
8  two       1 
9  page     0 
10  two      0
11  text     0 
12  page      0
13  three     0
10  text      0
11  chapter   1 
12  three     1
13  something  0

我想找到累计和，这样我就可以通过一个运行的索引号来标记属于特定章节的所有页面

**Desired output**


  text      secFlag  chapter
0  book     1       1
1  headings 1       1
2  chapter  1       2
3  one      1       2
4  page     0       2
5  one      0       2
6  text     0       2
7  chapter   1      3
8  two       1      3
9  page     0      3
10  two      0     3
11  text     0      3
12  page      0     3
13  three     0     3
10  text      0     3
11  chapter   1      4
12  three     1     4
13  something  0     4

这就是我所尝试的：

df['chapter'] = ((df['secFlag'].shift(-1) == 1)).cumsum()

但是，这并没有给出所需的输出，因为一旦节标志中的值为1，它就会递增。注意，多个单词是文本的一部分，章节标题通常有多个单词

你能建议一个简单的方法来完成这件事吗？ 谢谢

Answer 1

如果需要由secFlag中的第一个1标记，则解决方案是：

df['chapter'] = ((df['secFlag'] == 1) & (df['secFlag'] != df['secFlag'].shift())).cumsum()
print (df)
         text  secFlag  chapter
0        book        1        1
1    headings        1        1
2     chapter        1        1
3         one        1        1
4        page        0        1
5         one        0        1
6        text        0        1
7     chapter        1        2
8         two        1        2
9        page        0        2
10        two        0        2
11       text        0        2
12       page        0        2
13      three        0        2
10       text        0        2
11    chapter        1        3
12      three        1        3
13  something        0        3

详细信息：

a = (df['secFlag'] == 1)
b = (df['secFlag'] != df['secFlag'].shift())
c = a & b
d = c.cumsum()

print (pd.concat([df,a,b,c,d], 
                 axis=1, 
                 keys=('orig','==1','!=shifted','chained by &','cumsum')))
         orig             ==1 !=shifted chained by &  cumsum
         text secFlag secFlag   secFlag      secFlag secFlag
0        book       1    True      True         True       1
1    headings       1    True     False        False       1
2     chapter       1    True     False        False       1
3         one       1    True     False        False       1
4        page       0   False      True        False       1
5         one       0   False     False        False       1
6        text       0   False     False        False       1
7     chapter       1    True      True         True       2
8         two       1    True     False        False       2
9        page       0   False      True        False       2
10        two       0   False     False        False       2
11       text       0   False     False        False       2
12       page       0   False     False        False       2
13      three       0   False     False        False       2
10       text       0   False     False        False       2
11    chapter       1    True      True         True       3
12      three       1    True     False        False       3
13  something       0   False      True        False       3