文档建议反馈控制台
首页
学习
活动
专区
圈层
工具
MCP广场
文章/答案/技术大牛
发布
首页
学习
活动
专区
圈层
工具
MCP广场
返回腾讯云官网
社区首页 >问答首页 >使用Python从csv文件中的两个日期时间列中仅减去时间(分钟)

问使用Python从csv文件中的两个日期时间列中仅减去时间(分钟)
EN

Stack Overflow用户
提问于 2022-10-16 07:39:30
回答 1查看 25关注 0票数 0

下面是我在数据集中遇到的问题：

检查从“111-建筑物火灾”事件登录到计算机辅助调度系统和第一个单元到达现场之间所需的分钟数的分布情况。这个分布的第三个四分位数是什么。注意:分钟数可以是小数(即，不要圆圆)。

列包括日期和时间。我只想使用时间，这样我就可以从两行中减去它并得到分布。下面是我的当前代码：

代码语言：javascript
运行
复制
time_of_issuance = dataset.loc[dataset['INCIDENT_TYPE_DESC'] == '111 - Building fire', 'INCIDENT_DATE_TIME']
time_of_creation = dataset.loc[dataset['INCIDENT_TYPE_DESC'] == '111 - Building fire', 'ARRIVAL_DATE_TIME']

print(time_of_issuance)
print(time_of_creation)

下面是上面片段的输出：

代码语言：javascript
运行
复制
91         01/01/2013 12:58:10 AM
199        01/01/2013 02:22:56 AM
440        01/01/2013 06:20:49 AM
492        01/01/2013 07:59:48 AM
569        01/01/2013 09:47:27 AM
                    ...          
1735758    11/01/2016 03:54:41 PM
1735841    11/01/2016 04:48:49 PM
1736021    11/01/2016 07:05:58 PM
1736100    11/01/2016 08:36:32 PM
1736286    11/02/2016 12:32:51 AM
Name: INCIDENT_DATE_TIME, Length: 10379, dtype: object
91         01/01/2013 01:00:50 AM
199        01/01/2013 02:25:23 AM
440        01/01/2013 06:26:13 AM
492        01/01/2013 08:03:33 AM
569        01/01/2013 09:49:25 AM
                    ...          
1735758    11/01/2016 03:56:52 PM
1735841    11/01/2016 04:54:09 PM
1736021    11/01/2016 07:10:00 PM
1736100    11/01/2016 08:38:33 PM
1736286    11/02/2016 12:37:23 AM
Name: ARRIVAL_DATE_TIME, Length: 10379, dtype: object

我只想减去输出中所显示的两列之间的时间(以分钟为单位)。我怎样才能用Python做到这一点呢？我尝试过使用.dt.time，但它给我带来了一个错误。

在下面找到数据头：

代码语言：javascript
运行
复制
{'IM_INCIDENT_KEY': {0: 55672688,
  1: 55672692,
  2: 55672693,
  3: 55672695,
  4: 55672697,
  5: 55672698,
  6: 55672699,
  7: 55672700,
  8: 55672703,
  9: 55672705},
 'FIRE_BOX': {0: 2147,
  1: 818,
  2: 9656,
  3: 7412,
  4: 4019,
  5: 1328,
  6: 688,
  7: 9604,
  8: 2897,
  9: 2602},
 'INCIDENT_TYPE_DESC': {0: '300 - Rescue, EMS incident, other',
  1: '735A - Unwarranted alarm/defective condition of alarm system',
  2: '300 - Rescue, EMS incident, other',
  3: '412 - Gas leak (natural gas or LPG)',
  4: '735A - Unwarranted alarm/defective condition of alarm system',
  5: '735A - Unwarranted alarm/defective condition of alarm system',
  6: '353 - Removal of victim(s) from stalled elevator',
  7: '651 - Smoke scare, odor of smoke',
  8: '331 - Lock-in (if lock out , use 511 )',
  9: '710 - Malicious, mischievous false call, other'},
 'INCIDENT_DATE_TIME': {0: '01/01/2013 12:00:20 AM',
  1: '01/01/2013 12:00:37 AM',
  2: '01/01/2013 12:01:17 AM',
  3: '01/01/2013 12:02:32 AM',
  4: '01/01/2013 12:01:49 AM',
  5: '01/01/2013 12:02:45 AM',
  6: '01/01/2013 12:03:55 AM',
  7: '01/01/2013 12:04:03 AM',
  8: '01/01/2013 12:04:37 AM',
  9: '01/01/2013 12:05:10 AM'},
 'ARRIVAL_DATE_TIME': {0: '01/01/2013 12:14:23 AM',
  1: '01/01/2013 12:09:03 AM',
  2: '01/01/2013 12:04:55 AM',
  3: '01/01/2013 12:07:48 AM',
  4: '01/01/2013 12:06:27 AM',
  5: '01/01/2013 12:07:55 AM',
  6: '01/01/2013 12:13:10 AM',
  7: '01/01/2013 12:06:19 AM',
  8: '01/01/2013 12:11:02 AM',
  9: '01/01/2013 12:08:20 AM'},
 'UNITS_ONSCENE': {0: 1.0,
  1: 3.0,
  2: 1.0,
  3: 4.0,
  4: 6.0,
  5: 3.0,
  6: 1.0,
  7: 4.0,
  8: 1.0,
  9: 6.0},
 'LAST_UNIT_CLEARED_DATE_TIME': {0: '01/01/2013 12:20:06 AM',
  1: '01/01/2013 12:30:06 AM',
  2: '01/01/2013 12:15:18 AM',
  3: '01/01/2013 12:40:11 AM',
  4: '01/01/2013 12:24:56 AM',
  5: '01/01/2013 12:18:20 AM',
  6: '01/01/2013 12:30:33 AM',
  7: '01/01/2013 12:11:21 AM',
  8: '01/01/2013 12:23:29 AM',
  9: '01/01/2013 12:10:29 AM'},
 'HIGHEST_LEVEL_DESC': {0: '1 - More than initial alarm, less than Signal 7-5',
  1: '1 - More than initial alarm, less than Signal 7-5',
  2: '1 - More than initial alarm, less than Signal 7-5',
  3: '1 - More than initial alarm, less than Signal 7-5',
  4: '1 - More than initial alarm, less than Signal 7-5',
  5: '1 - More than initial alarm, less than Signal 7-5',
  6: '1 - More than initial alarm, less than Signal 7-5',
  7: '1 - More than initial alarm, less than Signal 7-5',
  8: '1 - More than initial alarm, less than Signal 7-5',
  9: '1 - More than initial alarm, less than Signal 7-5'},
 'TOTAL_INCIDENT_DURATION': {0: 1186.0,
  1: 1769.0,
  2: 841.0,
  3: 2259.0,
  4: 1387.0,
  5: 935.0,
  6: 1598.0,
  7: 438.0,
  8: 1132.0,
  9: 319.0},
 'ACTION_TAKEN1_DESC': {0: '00 - Action taken, other',
  1: '86 - Investigate',
  2: '00 - Action taken, other',
  3: '44 - Hazardous materials leak control & containment',
  4: '86 - Investigate',
  5: '86 - Investigate',
  6: '64 - Shut down system',
  7: '86 - Investigate',
  8: '70 - Assistance, other',
  9: '00 - Action taken, other'},
 'ACTION_TAKEN2_DESC': {0: nan,
  1: nan,
  2: nan,
  3: '64 - Shut down system',
  4: nan,
  5: nan,
  6: nan,
  7: nan,
  8: nan,
  9: nan},
 'ACTION_TAKEN3_DESC': {0: nan,
  1: nan,
  2: nan,
  3: '82 - Notify other agencies.',
  4: nan,
  5: nan,
  6: nan,
  7: nan,
  8: nan,
  9: nan},
 'PROPERTY_USE_DESC': {0: 'UUU - Undetermined',
  1: 'UUU - Undetermined',
  2: 'UUU - Undetermined',
  3: '429 - Multifamily dwelling',
  4: 'UUU - Undetermined',
  5: 'UUU - Undetermined',
  6: '429 - Multifamily dwelling',
  7: '960 - Street, other',
  8: '429 - Multifamily dwelling',
  9: 'UUU - Undetermined'},
 'STREET_HIGHWAY': {0: 'E 138 ST',
  1: 'W 46 ST',
  2: '116 ST',
  3: '43 ST',
  4: 'WYCKOFF AVE',
  5: 'HAMILTON AVE',
  6: 'AVEOFAMERICAS',
  7: '102 ST',
  8: 'BOYNTON AVE',
  9: '52 ST'},
 'ZIP_CODE': {0: 10454.0,
  1: 10036.0,
  2: 11418.0,
  3: 11103.0,
  4: 11385.0,
  5: 11215.0,
  6: 10001.0,
  7: 11418.0,
  8: 10472.0,
  9: 11219.0},
 'BOROUGH_DESC': {0: '2 - Bronx',
  1: '1 - Manhattan',
  2: '5 - Queens',
  3: '5 - Queens',
  4: '5 - Queens',
  5: '4 - Brooklyn',
  6: '1 - Manhattan',
  7: '5 - Queens',
  8: '2 - Bronx',
  9: '4 - Brooklyn'},
 'FLOOR': {0: nan,
  1: nan,
  2: nan,
  3: '1',
  4: nan,
  5: nan,
  6: '18',
  7: nan,
  8: nan,
  9: nan},
 'CO_DETECTOR_PRESENT_DESC': {0: nan,
  1: nan,
  2: nan,
  3: nan,
  4: nan,
  5: nan,
  6: nan,
  7: nan,
  8: nan,
  9: nan},
 'FIRE_ORIGIN_BELOW_GRADE_FLAG': {0: nan,
  1: nan,
  2: nan,
  3: nan,
  4: nan,
  5: nan,
  6: nan,
  7: nan,
  8: nan,
  9: nan},
 'STORY_FIRE_ORIGIN_COUNT': {0: nan,
  1: nan,
  2: nan,
  3: nan,
  4: nan,
  5: nan,
  6: nan,
  7: nan,
  8: nan,
  9: nan},
 'FIRE_SPREAD_DESC': {0: nan,
  1: nan,
  2: nan,
  3: nan,
  4: nan,
  5: nan,
  6: nan,
  7: nan,
  8: nan,
  9: nan},
 'DETECTOR_PRESENCE_DESC': {0: nan,
  1: nan,
  2: nan,
  3: nan,
  4: nan,
  5: nan,
  6: nan,
  7: nan,
  8: nan,
  9: nan},
 'AES_PRESENCE_DESC': {0: nan,
  1: nan,
  2: nan,
  3: nan,
  4: nan,
  5: nan,
  6: nan,
  7: nan,
  8: nan,
  9: nan},
 'STANDPIPE_SYS_PRESENT_FLAG': {0: nan,
  1: nan,
  2: nan,
  3: nan,
  4: nan,
  5: nan,
  6: nan,
  7: nan,
  8: nan,
  9: nan}}
python
pandas
EN

回答 1

Stack Overflow用户

发布于 2022-10-16 08:09:10

这并不能直接回答你的问题，因为我不认为你的方法很好。试试这个：

代码语言：javascript
运行
复制
delay = (
    dataset
    .query("INCIDENT_TYPE_DESC == '111 - Building fire'")
    .eval("ARRIVAL_DATE_TIME - INCIDENT_DATE_TIME")
    .divide(pd.Timedelta("1m"))
)

delay将是日志日期和到达时间之间分钟的pandas.Series，即表示一个分发。

例如，要找到第三个四分位数，请执行以下操作：

代码语言：javascript
运行
复制
delay.quantile(0.75)

编辑

您可能需要确保您的日期时间数据是pandas.Timestamp。执行此操作以进行转换，然后运行解决方案

代码语言：javascript
运行
复制
dataset["INCIDENT_DATE_TIME"] = dataset["INCIDENT_DATE_TIME"].apply(pd.to_datetime)
dataset["ARRIVAL_DATE_TIME"] = dataset["ARRIVAL_DATE_TIME"].apply(pd.to_datetime)

编辑2

对于较老的熊猫版本：

代码语言：javascript
运行
复制
df = dataset.query("INCIDENT_TYPE_DESC == '111 - Building fire'")
delay = df["ARRIVAL_DATE_TIME"] - df["INCIDENT_DATE_TIME"]
delay = delay/pd.Timedelta("1m")
票数 0
EN
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：

https://stackoverflow.com/questions/74085367

复制
相关文章

相似问题

领券

腾讯云开发者

扫码关注腾讯云开发者

扫码关注腾讯云开发者

领取腾讯云代金券

热门产品

热门推荐

更多推荐

Copyright © 2013 - 2025 Tencent Cloud. All Rights Reserved. 腾讯云 版权所有 

深圳市腾讯计算机系统有限公司 ICP备案/许可证号：粤B2-20090059 深公网安备号 44030502008569

腾讯云计算（北京）有限责任公司 京ICP证150476号 |  京ICP备11018762号 | 京公网安备号11010802020287

问题归档专栏文章快讯文章归档关键词归档开发者手册归档开发者手册 Section 归档