Data Explorer: Add preliminary customizable float formatting options for data values, summary stats

[wesm]

Partly addresses #2339 and #3210, and #3314. Adds a format_options parameter in the get_data_values and get_column_profiles backend methods to allow customized formatting of large, small, and medium-sized numbers. If the value threshold is above or below limits implied by the parameters, scientific notation is used. We've talked about dynamically trimming zero padding from the end of numbers (e.g. if all the floats displayed are integral, then we can trim the trailing zeros off all of them), but this will be a frontend-only change that can be done after.

e.g. with

df2 = pd.DataFrame(
    {
        "a": [
            0,
            1.0,
            1.01,
            1.012,
            0.0123,
            0.01234,
            0.0001,
            0.00000001,
            9999.123,
            9999.999,
            9999999,
            10000000,
            -10000000,
        ]
    }
)

[jthomasmock]

I think this is a good first step! Do you see a path forward for decimal alignment?

For example here is what RStudio does, still not necessarily ideal, but aligns everything:

[wesm]

Here's with slightly different settings in the front end:

[jthomasmock]

And just for comparison, here's a nice display in Sheets:

Ideally, I think we want to be careful to not over display sigfigs on decimal when there are very large numbers

[wesm]

Ideally, I think we want to be careful to not over display sigfigs on decimal when there are very large numbers

Right. I think there are two things to do as next steps:

• Decide on the default number of digits to use for formatting out of the box. If we want to make this "smart" on a per column basis, we'll have to add a formatting "sniffer" method that can make a guess based on a sample of the data (e.g. the first 1000 rows), but that's extra development work

• Trim zeros dynamically on the front end (I'll create an issue)

I'll go ahead and merge this since nothing here is set in stone.