我需要在列中出现某个值以与时间戳匹配（pandas dataframe＆amp; csv-file）
我有一个带有列roomid的CSV文件（称为“ Cameradata”），时间（还有更多的列，但不需要它们）。
我想在一天中使用某个会议室内的事件数量（“ 14094020”（“ 14094020”）。幸运的是，CSV文件仅由“时间”专栏中一天的时间戳组成。一个问题是时间戳在DateTime-Format％H：％m：％s中，我想在发生的小时（07：00-18：00）之前对出现进行分类。
目的是将出现与时间戳的时间链接在一起 - 为了让我绘制一个带有（x =“ Timestamps（hourly）”的barplot，y =“ y =”一个数据框/系列，将某个会议室绘制为一小时 。
使用
了
y = cameradata.set_index('Time').resample('H')
cameradata['MeetingRoomID'].value_counts()[14094020]
被 我不知道如何以语法友好的方式连接它
，但
。揭示了最多的ID，所以我认为我对
的帮助表示感谢！
您 是我所说的geetsroomid。 出于某种原因，“时间”列将其转换为DateTime时添加了一个化妆的年份和一个月。我转换为DateTime：Kameradata ['tid'] = pd.to_dateTime（kameradata ['tid']，格式=（'％h：％m：％s'））
I have a csv-file (called "cameradata") with columns MeetingRoomID, and Time (There are more columns, but they should not be needed).
I would like to get the number of occurrences a certain MeetingRoomID ("14094020", from the column "MeetingRoomID") is used during one day. The csv-file luckily only consist of timestamps from one day in the "Time" column. One problem is that the timestamps are in the datetime-format %H:%M:%S and I want to categorize the occurrences by the hour it occured (between 07:00-18:00).
The goal is to have the occurences linked to the hours of the timestamps - in order for me to plot a barplot with (x = "timestamps (hourly)" and y = "a dataframe/series that maps the certain MeetingRoomID with the hour it was used".
How can I get a function for my y-axis that understands that the value_count for ID 14094020 and the timestamps are connected?
So far I've come up with something like this:
y = cameradata.set_index('Time').resample('H')
cameradata['MeetingRoomID'].value_counts()[14094020]
My code seems to work if I divide it, but I do not know how to connect it in a syntax-friendly way.
Clarification:
The code: cameradata['MeetingRoomID'].value_counts().idxmax() revealed the ID with the most occurrences, so I think I'm onto something there.
Grateful for your help!
This is how the print of the Dataframe looks like, 'Tid' is time and 'MätplatsID' is what I called MeetingRoomID.
For some reason the "Time" column has added a made-up year and month next to it when I converted it to datetime. I converted in to datetime by: kameradata['Tid'] = pd.to_datetime(kameradata['Tid'], format=('%H:%M:%S'))
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