Pandas graphing a Timedelta series, with vertical lines at selected time

user_4079426 0
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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.

Consider this series:

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

I can select element in this series like this:

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

Out:
92.9

I can generate a graph like this:

In:
avg_hr.plot()

avg_hr.plot()

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'

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)

avg_hr.plot()

How can I plot vertical lines using this timedelta index?

EDIT:

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'
pandas timedelta matplotlib python
2 Answers

I have encountered a similar problem. The solution for the TimeDelta index I used was the total_seconds property which returns float in seconds. ("Total duration of timedelta in seconds (to ns precision)")

So,

plt.axvline(pd.Timedelta(seconds=120).total_seconds, color='r', linestyle='dashed', linewidth=2)

should do the trick.

user_35468940
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