tabsdata.tableframe.selectors.string#

string(*, include_categorical: bool = False) SelectorProxy[source]#

Select all columns of string or categorical data type.

Parameters:

include_categorical – If True, also include categorical columns in the selection.

Example

>>> import tabsdata.tableframe as td_tf
>>>
>>> tf = td_tf.TableFrame({
...     "Name": ["Anna", "Ben", "Cara", "Dean", "Ella", "Finn", "Gina", "Hugo"],
...     "Country": ["US", "UK", "FR", "DE", "IT", "ES", "NL", "SE"],
...     "Score": [90.5, 82.0, 88.5, 91.0, 85.5, 89.0, 87.5, 90.0]
... })

Original: ┌────────┬─────────┬───────┐ │ Name ┆ Country ┆ Score │ │ — ┆ — ┆ — │ │ str ┆ str ┆ f64 │ ╞════════╪═════════╪═══════╡ │ “Anna” ┆ “US” ┆ 90.5 │ │ “Ben” ┆ “UK” ┆ 82.0 │ │ “Cara” ┆ “FR” ┆ 88.5 │ │ “Dean” ┆ “DE” ┆ 91.0 │ │ “Ella” ┆ “IT” ┆ 85.5 │ │ “Finn” ┆ “ES” ┆ 89.0 │ │ “Gina” ┆ “NL” ┆ 87.5 │ │ “Hugo” ┆ “SE” ┆ 90.0 │ └────────┴─────────┴───────┘

>>> tf.select(td_tf.selectors.string())

Selected: ┌────────┬─────────┐ │ Name ┆ Country │ │ — ┆ — │ │ str ┆ str │ ╞════════╪═════════╡ │ “Anna” ┆ “US” │ │ “Ben” ┆ “UK” │ │ “Cara” ┆ “FR” │ │ “Dean” ┆ “DE” │ │ “Ella” ┆ “IT” │ │ “Finn” ┆ “ES” │ │ “Gina” ┆ “NL” │ │ “Hugo” ┆ “SE” │ └────────┴─────────┘