Python 从日期列创建月份列（但是日期列不包含月份信息）

我有这样一个数据，想创建一个名为“Month”的列

+---------+------------------+------+------+
| Name    | Task             | Team | Date |
+---------+------------------+------+------+
| John    | Market study     | A    | 1    |
+---------+------------------+------+------+
| Michael | Customer service | B    | 1    |
+---------+------------------+------+------+
| Joanna  | Accounting       | C    | 1    |
+---------+------------------+------+------+
| John    | Accounting       | B    | 2    |
+---------+------------------+------+------+
| Michael | Customer service | A    | 2    |
+---------+------------------+------+------+
| Joanna  | Market study     | C    | 2    |
+---------+------------------+------+------+
| John    | Customer service | C    | 1    |
+---------+------------------+------+------+
| Michael | Market study     | A    | 1    |
+---------+------------------+------+------+
| Joanna  | Customer service | B    | 1    |
+---------+------------------+------+------+
| John    | Market study     | A    | 2    |
+---------+------------------+------+------+
| Michael | Customer service | B    | 2    |
+---------+------------------+------+------+
| Joanna  | Accounting       | C    | 2    |
+---------+------------------+------+------+

所以基本上，我有日期信息，但日期不包含它所属的月份。但是，我知道如果是第一次，那么它将属于第1个月，如果是第二次，那么它将属于第2个月。例如，日期1出现3次，然后被日期2打断。所以前3次属于第1个月，接下来3次属于第2个月。因此，我希望我的结果如下：

+---------+------------------+------+------+---------+
| Name    | Task             | Team | Date | Month   |
+---------+------------------+------+------+---------+
| John    | Market study     | A    | 1    | Month 1 |
+---------+------------------+------+------+---------+
| Michael | Customer service | B    | 1    | Month 1 |
+---------+------------------+------+------+---------+
| Joanna  | Accounting       | C    | 1    | Month 1 |
+---------+------------------+------+------+---------+
| John    | Accounting       | B    | 2    | Month 1 |
+---------+------------------+------+------+---------+
| Michael | Customer service | A    | 2    | Month 1 |
+---------+------------------+------+------+---------+
| Joanna  | Market study     | C    | 2    | Month 1 |
+---------+------------------+------+------+---------+
| John    | Customer service | C    | 1    | Month 2 |
+---------+------------------+------+------+---------+
| Michael | Market study     | A    | 1    | Month 2 |
+---------+------------------+------+------+---------+
| Joanna  | Customer service | B    | 1    | Month 2 |
+---------+------------------+------+------+---------+
| John    | Market study     | A    | 2    | Month 2 |
+---------+------------------+------+------+---------+
| Michael | Customer service | B    | 2    | Month 2 |
+---------+------------------+------+------+---------+
| Joanna  | Accounting       | C    | 2    | Month 2 |
+---------+------------------+------+------+---------+

除了使用一些循环之外，我没有任何想法。

---

谢谢大家。

如果我正确理解了问题，您可以执行以下操作：创建掩码

s

，将每个连续值分成单独的组。从

s

，为每组的每个值创建掩码

s1

。Groupby

s1

和

Date

并执行

cumcount

和

map

以创建所需的输出：

s = df.Date.ne(df.Date.shift()).cumsum()
s1 = df.Date.groupby(s).cumcount()

df['Month'] = df.groupby([s1, 'Date']).Name.cumcount().add(1).map(lambda x: 'Month '+str(x))

Out[897]:
       Name              Task Team  Date    Month
0      John      Market-study    A     1  Month 1
1   Michael  Customer-service    B     1  Month 1
2    Joanna        Accounting    C     1  Month 1
3      John        Accounting    B     2  Month 1
4   Michael  Customer-service    A     2  Month 1
5    Joanna      Market-study    C     2  Month 1
6      John  Customer-service    C     1  Month 2
7   Michael      Market-study    A     1  Month 2
8    Joanna  Customer-service    B     1  Month 2
9      John      Market-study    A     2  Month 2
10  Michael  Customer-service    B     2  Month 2
11   Joanna        Accounting    C     2  Month 2

---

如果第一次发生什么？对不起，我找不到模式。如果日期是第一次出现（在date列中，您可以看到date 1，2。但是date 1出现了3次，然后被date 2打断，然后date 1再次出现，然后date 2再次出现。这意味着date 1第一次出现时，它属于month 1，第二次出现时，它属于month 2。对不起，我仍然不太清楚，当日期和名称重复时，然后是month sh应该是2？例如，日期1出现3次，然后被日期2打断，也出现3次。这意味着日期1在前3次出现中属于月份1，下一次出现时，它属于月份2。我真的不知道如何说得更清楚，英语不是我的第一语言，这不是一个容易问的问题。这取决于人们如何回答对于您的结果，我建议查看pd.where（or.np）和np.select

df.Date

相当于

df['Date']