Import datar

Import submodule, verbs and functions from datar

You can import everything (all verbs and functions) from datar by:

from datar.all import *

which is not recommended. Instead, you can import individual verbs or functions by:

from datar.all import mutate

Attention

When you use from datar.all import *, you need to pay attention to the python builtin names that are covered by datar (will warn by default). For example, slice will be datar.dplyr.slice instead of builtins.slice. To refer to the builtin one, you need to:

import builtins

s = builtins.slice(None, 3, None) # [:3]

Or if you know the origin of the verb, you can also do:

from datar.dplyr import mutate

You can also keep the namespace:

from datar import dplyr

# df = tibble(x=1)
# then use it with the dplyr namespace:
df >> dplyr.mutate(y=2)

If you feel those namespaces are annoying, you can always use datar.all:

from datar.all import mutate

Import datasets from datar

Note

Dataset has to be imported individually. This means from datar.datasets import * won't work (you don't want all datasets to exhaust your memory).

You don't have to worry about other datasets to be imported and take up the memory when you import one. The dataset is only loaded into memory when you explictly import it individually.

See also datasets for details about available datasets.

About python reserved names to be masked by datar

Sometimes it will be confusing especially when python builtin functions are overriden by datar. There are a couple of datar (r-base, dplyr) functions with the same name as python builtin functions. For example: filter, which is a python builtin function, but also a dplyr function. You should use filter_ instead. By default, datar will raise an error when you try to import filter. You can set this option to True to allow this behavior.