Tabeline 0.4.0

The main feature of this release is the addition of null support. It also adds Python 3.12 support, which necessitated changing the bounds of dependencies.

• Add Python 3.12 support
  • Upgrade to pyarrow 14 (first version with Python 3.12 support) for export to Arrow
  • Upgrade to Pandas 2 (2.1 is the first version with Python 3.12 support) for Pandas export
  • Upgrade to Polars 0.19
  • Put <3.13 ceiling on Python support. This was needed because NumPy 1.26 (the first version with Python 3.12 support) put a ceiling on its Python support, and in Poetry, this ceiling is viral.
• Add support for nulls
  • Add DataType enum and apply to Arrays
  • Added is_null function
  • Made all functions propagate nulls effectively
• Fixed a bug in the NumPy export of Arrays

Tabeline 0.3.2

One big feature and one small feature:

• DataFrame indexing thourgh df[rows, columns]
  • If int, str, returns a Python scalar
  • If columns is a str, return a tabeline.Array which is basically an array
  • If rows is an int, return a tabeline.Record which is basically a dictionary
  • If both request multiple items, return a new tabeline.DataFrame
• DataFrame.to_dict(self) returns a dict[str, Array]

Tabeline 0.3.1

This adds a handful of functions that can be used in expressions:

• Casting functions
  • to_boolean(x): Convert x from a boolean, a float, or an integer, to a boolean
  • to_integer(x): Convert x from a boolean, a float, or an integer to an integer or parse a string as an integer
  • to_float(x): Convert x from a boolean, a float, or an integer to a float or parse a string as a float
  • to_string(x): Deparse x to a string
• is_finite(x): True if x value is a floating point finite number
• same(x): One value of x if all values of x are the same, otherwise error

Duplicate columns in various operations are now properly detected and given a nice error message.

Tabeline 0.3.0

This adds a handful of functions to expressions:

• arcsin, arccos, arctan
• interp
• if_else

This also adds concatenate_rows and concatenate_columns as Python functions that take multiple DataFrames and do what you expect.

Tabeline 0.2.0

This release makes two major changes to Tabeline:

• group was renamed to group_by to be more consistent with the surrounding ecosystem.
  • group was kept as an alias for backwards compatibility
• DataTable was renamed to DataFrame to be more consistent with the surrounding ecosystem
  • DataTable was kept as an alias for backwards compatibility

In addition, there were some minor changes:

• The required version of Polars was advanced from 0.13 to 0.17.
• Support for Python 3.11 was added.
• A Contributing page was added to the documentation website

Tabeline 0.1.1

This provides minor fixes to broken package metadata. There is no change in the behavior of the installed package.

Tabline 0.1.0

The initial release of Tabeline, a dplyr-inspired data table and data grammar library, wrapping Polars as its computational engine:

• DataTable class
  • Multiple levels of grouping
• Conversions
  • from_polars, to_polars
  • from_pandas, to_pandas
  • read_csv, write_csv
• Basic verbs
  • select, deselect, rename
  • filter, slice0, slice1, distinct, unique
  • group, ungroup
  • summarize
  • spread, gather
  • inner_join, outer_join, left_join
• Expression operations
  • +, -, *, /, %, **
  • abs, sqrt, log, log2, log10, exp, pow, sin, cos, tan, floor, ceil
  • is_nan
  • std, var, max, min, sum, mean, median, quantile, trapz
  • any, all
  • first, last
• Documentation website