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python - 用于移动 python Pandas 的数据框

转载 作者：行者123 更新时间：2023-12-04 08:07:32 24 4
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我有一个 df 时间。我想要做的是创建另一列并将其设置为Shift。
每天早上 7 点到晚上 7 点是白类，晚上 7 点到早上 7 点是夜类。
例如:2/11:如果时间 btw 2/11 7 AM 到 2/11 7 PM 是 2-11 天和 2/11 7 PM 至 2/12 7 AM 是 2/11 晚上。
为了首先创建“Day-Shift”列，我创建了“Date”，然后创建了“Date-Shift”列。
但问题是我的代码正确分类了每天的“白类”(早上 7 点到晚上 7 点)，但未能正确分类“夜类”。请检查突出显示的行。
例如:第 21 行:其 Day-Shift 值应为“01-07 Night”而不是“01-08 Night”
enter image description here
我的代码:

df2["Date"]=df2['Time'].astype(str).str[:10]
df2["Shift"] = pd.to_datetime(df2['Time'],unit='s').apply(lambda x: "Day" if x.hour >= 7 and x.hour <= 18 else "Night")
df2['Date']=df2['Date'].astype(str)
df2['Date'] = df2['Date'].str[5:]
df2["Day-Shift"]=df2["Date"]+" "+df2["Shift"]
df2.head(2)
示例 df: 
{'Time': {17: Timestamp('2021-01-07 23:11:53'),
  18: Timestamp('2021-01-07 23:11:53'),
  19: Timestamp('2021-01-07 23:29:13'),
  20: Timestamp('2021-01-07 23:29:13'),
  21: Timestamp('2021-01-08 00:12:23'),
  22: Timestamp('2021-01-08 00:12:23'),
  23: Timestamp('2021-01-08 00:19:43'),
  24: Timestamp('2021-01-08 00:19:43'),
  25: Timestamp('2021-01-08 00:58:13'),
  26: Timestamp('2021-01-08 00:58:13'),
  27: Timestamp('2021-01-08 01:24:13'),
  28: Timestamp('2021-01-08 01:24:13'),
  29: Timestamp('2021-01-08 06:31:09'),
  30: Timestamp('2021-01-08 06:31:09'),
  31: Timestamp('2021-01-08 06:54:39'),
  32: Timestamp('2021-01-08 06:54:39'),
  33: Timestamp('2021-01-08 06:54:49'),
  34: Timestamp('2021-01-08 07:00:00'),
  35: Timestamp('2021-01-08 07:16:29'),
  36: Timestamp('2021-01-08 07:17:59'),
  37: Timestamp('2021-01-08 07:17:59'),
  38: Timestamp('2021-01-08 07:28:39'),
  39: Timestamp('2021-01-08 07:28:39'),
  40: Timestamp('2021-01-08 07:48:59'),
  41: Timestamp('2021-01-08 07:48:59'),
  42: Timestamp('2021-01-08 10:04:59'),
  43: Timestamp('2021-01-08 10:07:59'),
  44: Timestamp('2021-01-08 12:19:49'),
  45: Timestamp('2021-01-08 12:19:49'),
  46: Timestamp('2021-01-08 12:24:09'),
  47: Timestamp('2021-01-08 12:24:09'),
  48: Timestamp('2021-01-08 18:19:05'),
  49: Timestamp('2021-01-08 18:19:05')},
 'Date': {17: '01-07',
  18: '01-07',
  19: '01-07',
  20: '01-07',
  21: '01-08',
  22: '01-08',
  23: '01-08',
  24: '01-08',
  25: '01-08',
  26: '01-08',
  27: '01-08',
  28: '01-08',
  29: '01-08',
  30: '01-08',
  31: '01-08',
  32: '01-08',
  33: '01-08',
  34: '01-08',
  35: '01-08',
  36: '01-08',
  37: '01-08',
  38: '01-08',
  39: '01-08',
  40: '01-08',
  41: '01-08',
  42: '01-08',
  43: '01-08',
  44: '01-08',
  45: '01-08',
  46: '01-08',
  47: '01-08',
  48: '01-08',
  49: '01-08'},
 'Shift': {17: 'Night',
  18: 'Night',
  19: 'Night',
  20: 'Night',
  21: 'Night',
  22: 'Night',
  23: 'Night',
  24: 'Night',
  25: 'Night',
  26: 'Night',
  27: 'Night',
  28: 'Night',
  29: 'Night',
  30: 'Night',
  31: 'Night',
  32: 'Night',
  33: 'Night',
  34: 'Day',
  35: 'Day',
  36: 'Day',
  37: 'Day',
  38: 'Day',
  39: 'Day',
  40: 'Day',
  41: 'Day',
  42: 'Day',
  43: 'Day',
  44: 'Day',
  45: 'Day',
  46: 'Day',
  47: 'Day',
  48: 'Day',
  49: 'Day'},
 'Day-Shift': {17: '01-07 Night',
  18: '01-07 Night',
  19: '01-07 Night',
  20: '01-07 Night',
  21: '01-08 Night',
  22: '01-08 Night',
  23: '01-08 Night',
  24: '01-08 Night',
  25: '01-08 Night',
  26: '01-08 Night',
  27: '01-08 Night',
  28: '01-08 Night',
  29: '01-08 Night',
  30: '01-08 Night',
  31: '01-08 Night',
  32: '01-08 Night',
  33: '01-08 Night',
  34: '01-08 Day',
  35: '01-08 Day',
  36: '01-08 Day',
  37: '01-08 Day',
  38: '01-08 Day',
  39: '01-08 Day',
  40: '01-08 Day',
  41: '01-08 Day',
  42: '01-08 Day',
  43: '01-08 Day',
  44: '01-08 Day',
  45: '01-08 Day',
  46: '01-08 Day',
  47: '01-08 Day',
  48: '01-08 Day',
  49: '01-08 Day'}}

最佳答案

您可以从 Time 中减去一天如果小时不太像 7在 Series.mask ，然后创建 Shift通过比较 Series.between 中的小时数并通过 numpy.where 设置值最后用 Series.dt.strftime 连接列对于提取日期和月份:

df['Date'] = (df['Time'].mask(df['Time'].dt.hour.lt(7), 
                              df['Time'] - pd.offsets.DateOffset(days=1)))

df["Shift"] = np.where(df['Time'].dt.hour.between(7, 18), 'Day','Night')

df["Day-Shift"] = df["Date"].dt.strftime('%m-%d') + " " + df["Shift"]
print (df)
                  Time                Date  Shift    Day-Shift
17 2021-01-07 23:11:53 2021-01-07 23:11:53  Night  01-07 Night
18 2021-01-07 23:11:53 2021-01-07 23:11:53  Night  01-07 Night
19 2021-01-07 23:29:13 2021-01-07 23:29:13  Night  01-07 Night
20 2021-01-07 23:29:13 2021-01-07 23:29:13  Night  01-07 Night
21 2021-01-08 00:12:23 2021-01-07 00:12:23  Night  01-07 Night
22 2021-01-08 00:12:23 2021-01-07 00:12:23  Night  01-07 Night
23 2021-01-08 00:19:43 2021-01-07 00:19:43  Night  01-07 Night
24 2021-01-08 00:19:43 2021-01-07 00:19:43  Night  01-07 Night
25 2021-01-08 00:58:13 2021-01-07 00:58:13  Night  01-07 Night
26 2021-01-08 00:58:13 2021-01-07 00:58:13  Night  01-07 Night
27 2021-01-08 01:24:13 2021-01-07 01:24:13  Night  01-07 Night
28 2021-01-08 01:24:13 2021-01-07 01:24:13  Night  01-07 Night
29 2021-01-08 06:31:09 2021-01-07 06:31:09  Night  01-07 Night
30 2021-01-08 06:31:09 2021-01-07 06:31:09  Night  01-07 Night
31 2021-01-08 06:54:39 2021-01-07 06:54:39  Night  01-07 Night
32 2021-01-08 06:54:39 2021-01-07 06:54:39  Night  01-07 Night
33 2021-01-08 06:54:49 2021-01-07 06:54:49  Night  01-07 Night
34 2021-01-08 07:00:00 2021-01-08 07:00:00    Day    01-08 Day
35 2021-01-08 07:16:29 2021-01-08 07:16:29    Day    01-08 Day
36 2021-01-08 07:17:59 2021-01-08 07:17:59    Day    01-08 Day
37 2021-01-08 07:17:59 2021-01-08 07:17:59    Day    01-08 Day
38 2021-01-08 07:28:39 2021-01-08 07:28:39    Day    01-08 Day
39 2021-01-08 07:28:39 2021-01-08 07:28:39    Day    01-08 Day
40 2021-01-08 07:48:59 2021-01-08 07:48:59    Day    01-08 Day
41 2021-01-08 07:48:59 2021-01-08 07:48:59    Day    01-08 Day
42 2021-01-08 10:04:59 2021-01-08 10:04:59    Day    01-08 Day
43 2021-01-08 10:07:59 2021-01-08 10:07:59    Day    01-08 Day
44 2021-01-08 12:19:49 2021-01-08 12:19:49    Day    01-08 Day
45 2021-01-08 12:19:49 2021-01-08 12:19:49    Day    01-08 Day
46 2021-01-08 12:24:09 2021-01-08 12:24:09    Day    01-08 Day
47 2021-01-08 12:24:09 2021-01-08 12:24:09    Day    01-08 Day
48 2021-01-08 18:19:05 2021-01-08 18:19:05    Day    01-08 Day
49 2021-01-08 18:19:05 2021-01-08 18:19:05    Day    01-08 Day

关于python - 用于移动 python Pandas 的数据框，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/66149355/

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