SOMADataFrame

SOMADataFrame is a multi-column table that must contain a column called soma_joinid of type int64, which contains a unique value for each row and is intended to act as a join key for other objects, such as SOMASparseNDArray. (lifecycle: experimental)

Super classes

tiledbsoma::TileDBObject -> tiledbsoma::TileDBArray -> tiledbsoma::SOMAArrayBase -> SOMADataFrame

Methods

Public methods

• SOMADataFrame$create()

• SOMADataFrame$write()

• SOMADataFrame$read()

• SOMADataFrame$update()

• SOMADataFrame$clone()

Inherited methods

• tiledbsoma::TileDBObject$class()
• tiledbsoma::TileDBObject$exists()
• tiledbsoma::TileDBObject$initialize()
• tiledbsoma::TileDBObject$is_open()
• tiledbsoma::TileDBObject$mode()
• tiledbsoma::TileDBObject$reopen()
• tiledbsoma::TileDBArray$attributes()
• tiledbsoma::TileDBArray$attrnames()
• tiledbsoma::TileDBArray$close()
• tiledbsoma::TileDBArray$colnames()
• tiledbsoma::TileDBArray$dimensions()
• tiledbsoma::TileDBArray$dimnames()
• tiledbsoma::TileDBArray$fragment_count()
• tiledbsoma::TileDBArray$get_metadata()
• tiledbsoma::TileDBArray$index_column_names()
• tiledbsoma::TileDBArray$ndim()
• tiledbsoma::TileDBArray$non_empty_domain()
• tiledbsoma::TileDBArray$open()
• tiledbsoma::TileDBArray$print()
• tiledbsoma::TileDBArray$schema()
• tiledbsoma::TileDBArray$set_metadata()
• tiledbsoma::TileDBArray$shape()
• tiledbsoma::TileDBArray$tiledb_array()
• tiledbsoma::TileDBArray$tiledb_schema()
• tiledbsoma::TileDBArray$used_shape()

---

Method create()

Create (lifecycle: experimental)

Usage

SOMADataFrame$create(
  schema,
  index_column_names = c("soma_joinid"),
  platform_config = NULL,
  internal_use_only = NULL
)

Arguments

schema

an arrow::schema.

index_column_names

A vector of column names to use as user-defined index columns. All named columns must exist in the schema, and at least one index column name is required.

platform_config

A platform configuration object

internal_use_only

Character value to signal this is a 'permitted' call, as create() is considered internal and should not be called directly.

---

Method write()

Write (lifecycle: experimental)

Usage

SOMADataFrame$write(values)

Arguments

values

An arrow::Table or arrow::RecordBatch containing all columns, including any index columns. The schema for values must match the schema for the SOMADataFrame.

---

Method read()

Read (lifecycle: experimental) Read a user-defined subset of data, addressed by the dataframe indexing column, and optionally filtered.

Usage

SOMADataFrame$read(
  coords = NULL,
  column_names = NULL,
  value_filter = NULL,
  result_order = "auto",
  iterated = FALSE,
  log_level = "auto"
)

Arguments

coords

Optional named list of indices specifying the rows to read; each (named) list element corresponds to a dimension of the same name.

column_names

Optional character vector of column names to return.

value_filter

Optional string containing a logical expression that is used to filter the returned values. See tiledb::parse_query_condition for more information.

result_order

Optional order of read results. This can be one of either "ROW_MAJOR, "COL_MAJOR", or "auto"` (default).

iterated

Option boolean indicated whether data is read in call (when FALSE, the default value) or in several iterated steps.

log_level

Optional logging level with default value of "warn".

Returns

arrow::Table or TableReadIter

---

Method update()

Update (lifecycle: experimental)

Usage

SOMADataFrame$update(values, row_index_name = NULL)

Arguments

values

A data.frame, arrow::Table, or arrow::RecordBatch.

row_index_name

An optional scalar character. If provided, and if the values argument is a data.frame with row names, then the row names will be extracted and added as a new column to the data.frame prior to performing the update. The name of this new column will be set to the value specified by row_index_name.

Details

Update the existing SOMADataFrame to add or remove columns based on the input:

• columns present in the current the SOMADataFrame but absent from the new values will be dropped

• columns absent in current SOMADataFrame but present in the new values will be added

• any columns present in both will be left alone, with the exception that if values has a different type for the column, the entire update will fail because attribute types cannot be changed.

Furthermore, values must contain the same number of rows as the current SOMADataFrame.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

SOMADataFrame$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.