Ticdat

* `clone_` functions added to `TicDatFactory` and `PanDatFactory` to support the following schema manipulations via cloning.
* Adding a table. (Removing a table has been available for a while with the `table_restrictions` argument of the vanilla `clone`.
* Adding a column.
* Removing a column.
* Renaming a column.
* `duplicates_ticdat_init` flag available to better manage the duplicate rows when initializing `TicDat` objects. (151)
* munging speed improvement for infinity io flag (131)
* `-r` command line support for Roundoff. 159
* Enframe support removed.
* `-e` command line argument now used for something else.
* `dat_restricted` `sln_restricted` removed from `ticdat`. (These are super-easy to re-create manually is anyone needs them for backwards compatibility).
* Fixed empty-string bug when checking a `datetime` data type. (162)
* `tooltips` added to `TicDatFactory`, `PanDatFactory` for better schema documentation. (156)
* `-e` command line argument now supports creation of data integrity errors report. (164).
* `TicDatFactory` and `PanDatFactory` now consistent in terms of always json-dumping an empty list for an empty table.
* `get_row_predicates` added to `TicDatFactory`, `PanDatFactory` to allow easier programmatic assessment of current row predicates.
* `remove_parameter` added to `TicDatFactory`, `PanDatFactory`.
* `TicDatFactory` now allows default values for primary key fields.

* `TicDatFactory` and `PanDatFactory` now share the same default JSON format. List-of-lists is succinct and human readable.
* `add_implied_foreign_keys` added to `TicDatFactory` (which now longer creates implied foreign keys by default).
* `PanDat.__init__` uses defaults to handle missing columns.
* In general, more robust initialization of `TicDat`, `PanDat` from `pandas.DataFrame`.
* `TicDatFactory`/`PanDatFactory` `clone` made safer
* Minor bug fix re: string munging when writing parameters table.

Following summarizes all the changes since the 0.2.20 Release.

- Fixing a slow data load problem for `TicDatFactory` and Excel files. Should have been fixed with 0.2.19.6 but I overlooked Excel.
- Performance improvement for Excel reading with `PanDatFactory`
- Uses `openpyxl` for reading .xlsx files (latest `xlrd` no longer works for this).
- This includes some work to prune trailing all-empty rows, which were previously auto-pruned by the `xlrd` code.
- Ancient branches with example code finally got merged in.
- Fixed a minor bug re: setting up PG schemas.
- Fixed a minor bug re: initialing `PanDat` objects with empty lists for the named arguments.
- Made the csv example data a little more challenging to import.
- better `clone` functionality (easier to customize a clone to a slightly different schema)
- fixed deployment problem for sparse Pythons
- minor bug fix in examples
- minor bug fix re: `PanDatFactory` and long Excel sheet names
- Progress tracking for pd pg uploading.

* better `clone` functionality (easier to customize a clone to a slightly different schema)
* fixed deployment problem for sparse Pythons
* minor bug fix in examples
* minor bug fix re: `PanDatFactory` and long Excel sheet names
* Progress tracking for pd pg uploading.

Not putting this release on PyPi. Making it available to anyone who will benefit.

- Fixed a minor bug re: setting up PG schemas.
- Fixed a minor bug re: initialing `PanDat` objects with empty lists for the named arguments.
- Made the csv example data a little more challenging to import.

Not putting this release on PyPi. Making it available to anyone who will benefit.

- Performance improvement for Excel reading with `PanDatFactory`
- Uses `openpyxl` for reading .xlsx files (latest `xlrd` no longer works for this).
- This includes some work to prune trailing all-empty rows, which were previously auto-pruned by the `xlrd` code.
- Ancient branches with example code finally got merged in.