在单个HH:MM:SS轴上绘制不同日期的数据 [英] plotting data for different days on a single HH:MM:SS axis

问题描述

DataFrame具有时间戳记的数据，我想在视觉上比较数据的每日时间演变.如果我groupby天并绘制图表；由于日期不同，它们显然在时间上水平偏移.

The DataFrame has timestamped data and I want to visually compare the daily temporal evolution of the data. If I groupby day and plot the graphs; they are obviously displaced horizontaly in time due to differences in their dates.

我想在仅时间轴上绘制日趋势的日期不可知图.为此，我采取了shift将数据恢复适当的天数的方法，如以下代码所示

I want to plot a date agnostic graph of the day wise trends on a time only axis. Towards that end I have resorted to shifting the data back by an appropriate number of days as demonstrated in the following code

import pandas as pd
import datetime
import matplotlib.pyplot as plt

index1 = pd.date_range('20141201', freq='H', periods=2)
index2 = pd.date_range('20141210', freq='2H', periods=4)
index3 = pd.date_range('20141220', freq='3H', periods=5)

index = index1.append([index2, index3])

df = pd.DataFrame(list(range(1, len(index)+1)), index=index, columns=['a'])

gbyday = df.groupby(df.index.day)

first_day = gbyday.keys.min() # convert all data to this day

plt.figure()
ax = plt.gca()
for n,g in gbyday:
    g.shift(-(n-first_day+1), 'D').plot(ax=ax, style='o-', label=str(n))

plt.show()

产生以下情节

>

问题:这是熊猫的做事方式吗?换句话说，如何才能更优雅地实现这一目标?

Question: Is this the pandas way of doing it? In other words how can I achieve this more elegantly?

推荐答案

您可以在分组后选择索引的hour属性，如下所示:

You can select the hour attribute of the index after grouping like this:

In [36]: fig, ax = plt.subplots()
In [35]: for label, s in gbyday:
   ....:     ax.plot(s.index.hour, s, 'o-', label=label)

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