Plot DataFrame with TimedeltaIndex (x-axis)

Hello,

Plotly.py doesn't display x axis well when using a TimedeltaIndex

import pandas as pd
from pandas.compat import StringIO
import plotly
from plotly.graph_objs import Scatter, Layout

dat = """millis;ax;ay;az
544;-5.65;-0.39;7.45
550;-4.79;-0.59;7.26
556;-4.79;-1.33;6.79
562;-0.63;-1.33;9.53
579;-4.63;0.16;7.96
599;-5.45;0.35;7.34
618;-5.18;1.88;3.77
637;-6.12;-2.00;9.92
658;-3.80;0.51;9.02
677;-4.35;0.04;9.53
697;-3.88;0.71;8.79
717;-4.86;-0.43;8.83
741;-4.16;-1.06;8.79
756;-3.57;0.31;7.92
777;-2.71;2.79;8.32
796;-2.43;5.53;10.55
816;-2.75;3.30;8.67
835;-2.12;2.47;7.85
856;-2.04;2.63;7.85
875;-2.31;2.31;8.04
894;-2.00;3.37;8.12
922;0.86;7.69;9.65
942;-1.45;5.26;8.75
961;-1.96;4.35;8.04
985;-1.80;3.77;8.36
1001;-1.61;3.10;8.55"""

df = pd.read_csv(StringIO(dat), sep=';')
df['millis'] = pd.to_timedelta(df['millis'], unit='ms')
df = df.set_index('millis')

df.index = df.index + pd.Timestamp("1970/01/01")

print(df)
print(df.dtypes)
print(df.index)

plotly.offline.plot({
"data": [
    Scatter(x=df.index, y=df['ax'])
],
"layout": Layout(
    title="DataFrame with %s" % str(type(df.index))
)
})

When using TimedeltaIndex I get

x-axis have odd values starting with P0D 0H0M0.

but when using a DatetimeIndex I get

It will be great if Plotly.py could handle TimedeltaIndex without hassle.

Kind regards

Start with the provided pandas TimedeltaIndex reproduction and trace Plotly.py's conversion of index values into x-axis data. Confirm the behavior against the shown DatetimeIndex output; done means a TimedeltaIndex renders readable x-axis values without requiring the caller to convert it manually.