pandas 绘制Timedelta系列的图，在选定时间带有垂直线 [英] Pandas graphing a Timedelta series, with vertical lines at selected time

问题描述

我有一个与此非常相似的问题:熊猫绘制时间序列图，在选定日期有垂直线，但是该解决方案不适用于Timedelta.

I got a very similar question to this one : Pandas graphing a timeseries, with vertical lines at selected dates but the solution doesn't works with Timedelta.

考虑这个系列:

In:
avg_hr.head()

Out:
00:00:00     69.000000
00:00:01     93.750000
00:00:02     93.125000
00:00:03     92.900000
00:00:04     93.222222
00:00:05     93.222222
...
Name: bpm, Length: 253, dtype: float64

我可以这样选择本系列中的元素:

I can select element in this series like this:

In:
avg_hr[pd.Timedelta(seconds=3)]

Out:
92.9

我可以生成如下图:

In:
avg_hr.plot()

但是，我不能像这样用TimeDelta绘制垂直线:

But, I can't plot vertical lines with TimeDelta like this:

In:
plt.axvline(x=pd.Timedelta(seconds=110), color='r', linestyle='dashed', linewidth=2)

Out:
TypeError: Cannot compare type 'Timedelta' with type 'float64'

但是，如果我使用float或int，则垂直线会出现在位置0.

Though, if I use a float or int, the vertical lines appear at position 0.

In:
plt.axvline(x=110, color='r', linestyle='dashed', linewidth=2)

如何使用此timedelta索引绘制垂直线?

How can I plot vertical lines using this timedelta index?

即使我直接使用x轴上使用的键，也会遇到相同的错误:

Even if I use directly the keys used on x-axis, I got the same error:

In:
for key in avg_hr.keys():
    ax.axvline(x=key, color='r', linestyle='dashed', linewidth=2)

Out:
TypeError: Cannot compare type 'Timedelta' with type 'float64'

推荐答案

我发现即使我以秒为单位工作，并且轴标签以秒为单位显示时间，实际上也以纳秒为单位！

I figured out that even if I work in seconds, and that the axis label show the time in second, it's in fact in nanoseconds!

从文档熊猫时间增量:

Pandas使用64位表示纳秒级的Timedeltas 整数

Pandas represents Timedeltas in nanosecond resolution using 64 bit integers

因此，在我的问题示例中，当我调用此命令时，垂直线不在位置0处，而是实际上在110纳秒的位置(在此标度下非常接近0):

So, in the example of my question, when I called this, the vertical line was not at position 0, but in fact at position 110 nanoseconds (so very close to 0 with this scale):

plt.axvline(x=110, color='r', linestyle='dashed', linewidth=2)

解决方案只是将您的x值转换为十亿分之一秒:

The solution is simply to convert your x value in nanoseconds:

x_ns = pd.Timedelta(seconds=110) / pd.Timedelta(1,'ns') #Seconds to nanoseconds
plt.axvline(x=x_ns, color='r', linestyle='dashed', linewidth=2)

当我尝试更改xlim时发现了这一点，然后发现一切都缩放到了纳秒.因此，需要将相同的转换应用于xlim.

I found this when I tried to change the xlim, then I saw that everything was scale to nanoseconds. So, the same conversion needed to be applied to xlim.

ax1.set_xlim([0, 110])

结果(具有多条垂直线)

完成于:

#Add verticals lines for specific event
plt.axvline(x=pd.Timedelta(seconds=120) / pd.Timedelta(1,'ns'), color='r', linestyle='dashed', linewidth=2)
plt.axvline(x=pd.Timedelta(seconds=185) / pd.Timedelta(1, 'ns'), color='r', linestyle='dashed', linewidth=2)
plt.axvline(x=pd.Timedelta(seconds=210) / pd.Timedelta(1, 'ns'), color='r', linestyle='dashed', linewidth=2)
plt.axvline(x=pd.Timedelta(seconds=225) / pd.Timedelta(1, 'ns'), color='r', linestyle='dashed', linewidth=2)

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