typespecs.frame module#

typespecs.frame.collapse(frame: DataFrame, conflict: Mapping[str, Literal['override', 'update'] | Callable[[Any, Any], Any]] | Literal['override', 'update'] | Callable[[Any, Any], Any] = 'override', /) → DataFrame[source]#

Collapse given DataFrame by resolving conflicts between rows.

Parameters:

  • frame – DataFrame to collapse.

  • conflict – Resolution strategy for conflicts between rows. Either a single resolution or a mapping of column names to resolutions is accepted. As built-in resolutions, "override" (new value overrides old value; default behavior) and "update" (new mapping updates old mapping) are supported. A function that takes old and new values and returns resolved value can also be accepted as a custom resolution.

Returns:

Collapsed DataFrame.

typespecs.frame.concat(frames: Iterable[DataFrame], /) → DataFrame[source]#

Concatenate DataFrames row-wise with missing values filled with <NA>.

Parameters:

frames – DataFrames to concatenate.

Returns:

Concatenated DataFrame.

typespecs.frame.fillna(frame: DataFrame, value: Mapping[str, ~typing.Any] | ~typing.Any=<NA>, /) → DataFrame[source]#

Fill pandas <NA> in given DataFrame with given value.

Parameters:

  • frame – DataFrame to fill.

  • value – Default value for each column. Either a single value or a mapping of column names to values is accepted. If the specified columns are not present in frame, each column filled with the specified value will be added.

Returns:

Filled DataFrame.

typespecs.frame.isna(frame: DataFrame, /) → DataFrame[source]#

Detect missing values (<NA> only) in given DataFrame.

Parameters:

frame – DataFrame to check.

Returns:

Boolean DataFrame indicating missing values (<NA> only).

typespecs.frame.no_silent_downcasting() → AbstractContextManager[None][source]#

Context manager to avoid silent downcasting for pandas < 3.

typespecs.frame.replace(frame: DataFrame, old: Any, new: Any, /, on: Any | None = None) → DataFrame[source]#

Replace old value with new value in given DataFrame.

Parameters:

  • frame – DataFrame to replace.

  • old – Old value to replace.

  • new – New value to replace with.

  • on – Optional data type to restrict replacement on.

Returns:

Replaced DataFrame.