Align y-axis scales for plots with more than one mark type

When plotting two different mark types on the same plot, the y-axis aren't guaranteed to be the same scale, even by setting the y_min / y_max consistently. One way to do this would be to introduce another parameter to control major tick interval.

Here's some example code:

```py
q.page['timeseries'] = ui.plot_card(box = ui.box('timeseries', height = '1000px'),
title = 'My Title',
data = ts_plot_data,
plot = ui.plot([
ui.mark(type='path', x_scale='time', x='=date', y='=picks', color='=label', y_min=0, y_max = np.max(plot_data["upper_bound"]), color_range="#3399FF #FF9966", y_title="Picks", y_nice=True),
ui.mark(type='area', x_scale='time', x='=date', y0='=lower_bound', y='=upper_bound', y_min=0, y_max = np.max(plot_data["upper_bound"]), y_nice = True)])
)
```

And the result:


in `ggplot2`, this is controlled explicitly with [sec_axis](https://ggplot2.tidyverse.org/reference/sec_axis.html). Ideally, if both marks are plotting the same quantity (or at least in the same units as each other), a secondary axis may not necessary. Here's another example using ggplot: https://www.r-graph-gallery.com/line-chart-dual-Y-axis-ggplot2.html

Start with the Python plotting API demonstrated in the issue, especially ui.plot and ui.mark handling for path and area marks. Reproduce the example with shared y_min and y_max, then determine how major tick intervals or secondary-axis behavior should be specified. Done means multiple mark types plotting the same quantity use aligned y-axis scales, with the intended behavior covered by tests.

Written by the indexing model from the issue text.