将日期时间对象按小时排序到Pandas数据框，然后使用Matplotlib可视化为直方图

我需要按小时将观看者分类为直方图.我有一些使用Matplotlib进行操作的经验，但是我找不到按小时对日期进行排序最实用的方法.

I need to sort viewers by hour to a histogram. I have some experience using Matplotlib to do that, but I can't find out what is the most pragmatic way to sort the dates by hour.

首先，我从JSON文件中读取数据，然后将两种相关的数据类型存储在pandas Dataframe中，如下所示:

First I read the data from a JSON file, then store the two relevant datatypes in a pandas Dataframe, like this:

data = pd.read_json('data/data.json')

session_duration = pd.to_datetime(data.session_duration, unit='s').dt.time
time = pd.to_datetime(data.time, format='%H:%M:%S').dt.time

viewers = []

for x, y in zip(time, session_duration):
    viewers.append({str(x):str(y)})

源文件看起来像这样，而忽略了不相关的部分.

The source file looks like this, leaving out the irrelevant parts.

{
    "time": "00:00:09",
    "session_duration": 91
},
{
    "time": "00:00:16",
    "session_duration": 29
},
{
    "time": "00:00:33",
    "session_duration": 102
},
{
    "time": "00:00:35",
    "session_duration": 203
}

请注意，session_duration以秒为单位.

Note that the session_duration is in seconds.

我必须区分两种类型的观众:

I have to distinguish two types of viewers:

• 在视频流上花费了< = 1分钟的人
• 在流中花费> = 1分钟的人

为此，我这样做:

import datetime
for element in viewers:
    for time, session_duration in element.items():
        if datetime.strptime(session_duration, '%H:%M:%S').time() >= datetime.strptime('00:01:00', '%H:%M:%S').time():
            viewers_more_than_1min.append(element)
        else:
            viewers_less_than_1min.append(element)

结果，我将值存储在这样的字典中:{session_duration:time} 其中键是会话结束的时间流，而值是观看时间.

As a result I have my values in a dictionary like this: {session_duration:time} Where the key is the time when the session ended the stream and the value is the time spent watching.

[{'00:00:09': '00:01:31'},
 {'00:00:16': '00:00:29'},
 {'00:00:33': '00:01:42'},
 {'00:00:35': '00:03:23'},
 {'00:00:36': '00:00:32'},
 {'00:00:37': '00:04:47'},
 {'00:00:47': '00:00:42'},
 {'00:00:53': '00:00:44'},
 {'00:00:56': '00:00:28'},
 {'00:00:58': '00:01:17'},
 {'00:01:04': '00:01:16'},
 {'00:01:09': '00:00:46'},
 {'00:01:29': '00:01:07'},
 {'00:01:31': '00:01:02'},
 {'00:01:32': '00:01:01'},
 {'00:01:32': '00:00:36'},
 {'00:01:37': '00:03:03'},
 {'00:01:49': '00:00:57'},
 {'00:02:01': '00:02:15'},
 {'00:02:18': '00:01:16'}]

作为最后一步，我希望创建一个带有Matplotlib的直方图，该直方图表示每小时从上述两种查看器类型获得的每个观看者人数.我认为它会像这样:

As a final step I wish to create a histogram withMatplotlib representing the viewercount for each our from the two viewertypes mentioned above per hour. I assume it would go something like this:

import matplotlib.pyplot as plt
import datetime as dt
hours = [(dt.time(i).strftime('%H:00')) for i in range(24)]
plt.xlabel('Hour')
plt.ylabel('Viewer count')
plt.bar(hours, sorted_viewcount_byhour)