add support for Pandas Time spans as index col (PeriodIndex)

Hello,

I'd like to use the pandas PeriodIndex date format to work with and calculate things in a time series way.

The manual says that Plotly auto-sets the axis type to a date format when the corresponding data are either ISO-formatted date strings or if they're a date pandas column or datetime NumPy array. (https://plotly.com/python/time-series/)

So I guess, since a PeriodIndex isn't of the concept "date" but of the concept "Time spans", Plotl.ly isn't able to auto-set this axis type? The error I get is a TypeError: Object of type Period is not JSON serializable

I know I can solve this with converting to another format (#df.index = df.index.astype(str)), but it would be great to have a native solution inside plot.ly that can understand PeriodIndex.

Here is my example code:

import pandas as pd
import plotly.express as px


### READ IN DATA ###
d = {
    'one':
    pd.Series([1., 2.],
              index=[
                  'Jan/2020', 'Feb/2020', 
              ])
}

df = pd.DataFrame(d)

print(f'\n# this is what I get from my datasource\n')
print(df.index)
print(df)

### CONVERT DATA ###
idx = df.index
df.index = pd.to_datetime(idx, format="%b/%Y").to_period(freq='M')

print(f'\n# after conversion\n')
print(df.index)

df.index.name = 'Monat'
print(df)

df = df.sort_index()

###THIS FIXES IT, BUT :/ ###
#df.index = df.index.astype(str)

fig = px.line(df, x=df.index, y=('one'), title='Testplot')
fig.show()

先运行提供的 pandas 和 Plotly 复现代码，然后跟踪 PeriodIndex 如何进入 JSON 序列化流程，并将其与受支持的日期索引和字符串索引进行比较。完成标准是示例无需 astype(str) 即可渲染，并且 PeriodIndex 的行为有测试覆盖。