Python Pandas DataFrame:基于其他列值的条件列

Question

问题描述:
我正在试着模拟一台机器，它的运行模式"如果"VALUE"在前3个时间步中大于或等于5 -这意味着&;value&;>= 5至少3分钟。运营模式&;保持"&;B"为下一个时间步骤，只要"VALUE"大于或等于5，并变成"A"在至少3个时间步之后-这意味着操作模式&;在接下来的3分钟内保持有效。3分钟后运行模式"a";如果"VALUE">

目标:
我需要一种使用python和pandas来识别"A"描述的操作模式的方法。和";B"(列:"statusA/& ")，根据列"VALUE"中的值状态"开启";和";down"(专栏:"VALUE<5—>down, VALUE>=5 ->知道;)。

必须考虑的条件如下:

• 中"A"one_answers";B">
• 中"B"如果至少3个"on">
• 一旦"B"发生，接下来的3个时间步必须是即使状态是"down"，也要保持"&;B"只要"继续";存在。

What I did try:
我尝试了多种方法，为案件申请了抗辩;和";知道;并尝试根据计数器值跟踪状态，但不幸的是它没有正常工作。

<表类> 时间价值VALUE<5——比;down/VALUE>=5—>statusA/Btbody><<tr>00到00:010到00:020到00:038在00:044到00:05开始52到00:061到00:072到00:081到00:085在00:096在00:100到00:1110在00:1210在00:1310在00:1411到B今日2到B00:161到B00:173到00:1811在00:1910在00:2010在00:2110在B00:2210在B00:2311在B00:2414在B00:2511在B

修改方案． 我编辑了我的解决方案，感谢亲爱的mozway提出的一个微妙的观点:

import pandas as pd
df2['status'] = df2['VALUE'].mask(df2['VALUE'].shift().rolling(3, min_periods=3).min() >= 5, 'B')
m1 = df2['status'].shift().eq('B')
m2 = df2['status'].shift(2).eq('B')

df2['status'] = (df2['status']
.mask(m1 | m2).fillna('B')
.astype(str)
.str.replace(r'd+', 'A'))
m5 = df2['status'].shift().eq('B')
m6 = df2['status'].shift(2).eq('B')
m3 = df2['status'].eq('A')
m4 = df2.iloc[:, 2].eq('on')
df2['status'] = df2['status'].mask((m5 & m3 & m4) | (m6 & m3 & m4)).fillna('B')

index  VALUE  ...                                 resulted statusA/B status
0       0      3  ...                                                  A      A
1       1      5  ...                                                  A      A
2       2      2  ...                                                  A      A
3       3      6  ...                                                  A      A
4       4      3  ...                                                  A      A
5       5      1  ...                                                  A      A
6       6      7  ...                                                  A      A
7       7      7  ...                                                  A      A
8       8      2  ...                                                  A      A
9       9      2  ...                                                  A      A
10     10      3  ...                                                  A      A
11     11      6  ...                                                  A      A
12     12      8  ...                                                  A      A
13     13      8  ...                                                  A      A
14     14      7  ...                                                  B      B
15     15      4  ...                                                  B      B
16     16      4  ...                                                  B      B
17     17      6  ...  A(expected is B because is "on" and at least 3...      B
18     18      6  ...  A(expected is B because is "on" and at least 3...      B
19     19      6  ...  A(expected is B because is "on" and at least 3...      B
20     20      7  ...                                                  B      B
21     21      2  ...                                                  B      B
22     22      9  ...                                                  B      B
23     23      8  ...  A(expected is B because "B" keeps a "B" for 3 ...      B
24     24      7  ...  A(expected is B because is "on" and at least 3...      B
25     25      2  ...                                                  B      B
26     26      4  ...  A(expected is B because "B" keeps a "B" for 3 ...      B
27     27      4  ...  A(expected is B because "B" keeps a "B" for 3 ...      B
28     28      1  ...  A(this true because it is down and the 3 time ...      A
29     29      4  ...                                                  A      A
[30 rows x 5 columns]