Plotting DataFrame with timedelta64 (y-axis)

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

[jaladh-singhal]

Is there any progress regarding this, I really need to use timedelta64 on Y-axis?

[ThomasGl]

Hey, it’s a bit late to the party. But, I wrote a solution for this issue. You can have dash, including its iterative features working and a datetime format in any sense. This, includes the autorender to solve for many x_sample points, so that it won’t crash your axis.

Such is the following:

For the x_axis make absolutely sure that the format of your list is list[str] and they are consistent. ALSO, match the format in those strings in the tickformat of your list, the reference for time is standard as used in datetime objects, for future reference check: https://plotly.com/python/reference/layout/xaxis/#layout-xaxis-tickformat

e.g.:

mock_list = ["00:00:00", "00:00:01"]

mock_list to be the x values in a scatter plot for instance then adjust the axis as follows:

fig.update_xaxes( tickformat="%H:%M:%S")