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()

Exécutez d’abord la reproduction fournie avec pandas et Plotly, puis suivez le chemin de PeriodIndex jusqu’à la sérialisation JSON et comparez-le aux index de dates et de chaînes pris en charge. Le travail est terminé lorsque l’exemple se rend sans nécessiter astype(str) et que le comportement de PeriodIndex est couvert par un test.