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

首先執行提供的 Python 重現程式，並將 timedelta64 y 軸值與轉譯後的圖表進行比較。追蹤 pandas timedelta 值如何傳入 Plotly 的 bar trace，並將完成標準定義為此範例中的 y 軸值能正確顯示。