根据时间python查找最大值和下降行

发布于 2025-02-07 12:58:01 字数 1274 浏览 4 评论 0原文

我试图根据电台列和有效列的小时找到REC的最大值。我没有可行的代码，因为我一直在尝试这种情况，而且还没有发现工作解决方案。

框

电台	合作	与
数据	是	正在
我	这	的

	02-23 08:07:00	0.1
1V4	2022-02-23 08:51:00	0.6
BTV	2022-02-23 07:52:00	0.1
BTV	2022-02-23	07
:54:54: 00	: 54 23 07:59:00	0.3
BTV	2022-02-23 08:02:00	0.0
BTV	2022-02-23 08:16:00	0.0
BTV	08:29:00	0.3

2022-02-23 看起来像

站	有效	爆炸
1V4	2022-02-23 07:58:00	0.4
1V4	2022-02-23 08:51:00	0.6
BTV	2022-02-23 07:59:00	0.3 0.3
BTV	20222-202-23 08:29 ：00	0.3

原文

I am trying to find the maximum value of precip based on the station column and the hour of the valid column. I have no workable code as I've been trying this forever and have found no even close to working solution.

Here is the dataframe I am working with

station	valid	precip
1V4	2022-02-23 07:54:00	0.2
1V4	2022-02-23 07:55:00	0.2
1V4	2022-02-23 07:58:00	0.4
1V4	2022-02-23 08:07:00	0.1
1V4	2022-02-23 08:51:00	0.6
BTV	2022-02-23 07:52:00	0.1
BTV	2022-02-23 07:54:00	0.2
BTV	2022-02-23 07:59:00	0.3
BTV	2022-02-23 08:02:00	0.0
BTV	2022-02-23 08:16:00	0.0
BTV	2022-02-23 08:29:00	0.3

This is what I want it to look like

station	valid	precip
1V4	2022-02-23 07:58:00	0.4
1V4	2022-02-23 08:51:00	0.6
BTV	2022-02-23 07:59:00	0.3
BTV	2022-02-23 08:29:00	0.3

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可是我不能没有你 2025-02-14 12:58:01

您需要按车站和小时分组，并获取idxmax，然后切片：

df['valid'] = pd.to_datetime(df['valid'])

df.loc[df.groupby(['station', df['valid'].dt.hour])['precip'].idxmax()]

输出：

   station               valid  precip
2      1V4 2022-02-23 07:58:00     0.4
4      1V4 2022-02-23 08:51:00     0.6
7      BTV 2022-02-23 07:59:00     0.3
10     BTV 2022-02-23 08:29:00     0.3

You need to group by station and hour and get the idxmax, then slice:

df['valid'] = pd.to_datetime(df['valid'])

df.loc[df.groupby(['station', df['valid'].dt.hour])['precip'].idxmax()]

output:

   station               valid  precip
2      1V4 2022-02-23 07:58:00     0.4
4      1V4 2022-02-23 08:51:00     0.6
7      BTV 2022-02-23 07:59:00     0.3
10     BTV 2022-02-23 08:29:00     0.3

回复收藏 0 原文

極樂鬼 2025-02-14 12:58:01

这将使您能够按小时和车站进行分组

df1['Hour'] = pd.to_datetime(df['valid'], infer_datetime_format=True).dt.hour
df1['precip_max'] = df1.groupby(['station', 'Hour'])['precip'].transform('max')
df1.loc[df['precip'] == df['precip_max']]

This will allow you to group by the hour and the station

df1['Hour'] = pd.to_datetime(df['valid'], infer_datetime_format=True).dt.hour
df1['precip_max'] = df1.groupby(['station', 'Hour'])['precip'].transform('max')
df1.loc[df['precip'] == df['precip_max']]

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~没有更多了~