Similar to #799 but on y-axis and https://github.com/pandas-dev/pandas/issues/16953
import pandas as pd
from pandas.compat import StringIO
import plotly
import plotly.graph_objs as go
dat = """c1,c2,c3
1000,2000,1500
9000,8000,1600"""
df = pd.read_csv(StringIO(dat))
df = df.apply(lambda x: pd.to_timedelta(x, unit='ms'))
print(df)
print(df.dtypes)
print(df.index)
trace1 = go.Bar(
x=df.index,
y=df.c1,
name='c1'
)
trace2 = go.Bar(
x=df.index,
y=df.c2,
name='c2'
)
trace3 = go.Bar(
x=df.index,
y=df.c3,
name='c3'
)
data = [trace1, trace2, trace3]
layout = go.Layout(
barmode='group'
)
plotly.offline.plot({
"data": data,
"layout": layout
})
displays

y-axis values are not correctly displayed
A workaround is to do:
for col in df.columns:
df[col] = df[col] + pd.to_datetime('1970/01/01')

but it will be nice if plotly.py could handle timedelta64 on y-axis
Is there any progress regarding this, I really need to use timedelta64 on Y-axis?
Most helpful comment
Is there any progress regarding this, I really need to use timedelta64 on Y-axis?