Seeking clarification on setting custom holiday prior scale

*EDIT: The questions I have are specifically about [this line](https://facebook.github.io/prophet/docs/seasonality,_holiday_effects,_and_regressors.html#modeling-holidays-and-special-events) in the docs. _You can also include a column prior_scale to set the prior scale separately for each holiday, as described below._

**prior_scale syntax**
Assuming I have a holidays dataframe as shown in the docs with an additional holiday flag called 'christmas', is the following an appropriate way to set different prior_scales?
```
holidays['prior_scale'] = 0.1
holidays.loc[holidays['holiday'] == 'christmas', 'prior_scale'] = 10
```
**intended effect**
The snippet from my fitted forecast below shows a consistent underestimation of the holiday effect for christmas.

Assuming the above syntax is correct, I have tried increasing the prior_scale to increase the flexibility of the 'christmas' holiday fit in hopes it will approach the actual. However, I have tried some reasonable priors (0.5, 1, 10) as well as 1000 and noticed no difference in the final effect.

Any insight would be appreciated here. Thank you.

Begin with the linked Prophet documentation section on modeling holidays and special events, then trace the documented per-holiday prior_scale behavior relevant to the shown holidays dataframe. Done means establishing whether the syntax and expected effect are correct and recording any needed clarification in that documentation.

Written by the indexing model from the issue text.