datar 0.4.0

Port of dplyr and other related R packages in python, using pipda.

datar

Port of dplyr and other related R packages in python, using pipda.

Documentation | Reference Maps | Notebook Examples | API | Blog

Unlike other similar packages in python that just mimic the piping syntax, datar follows the API designs from the original packages as much as possible, and is tested thoroughly with the cases from the original packages. So that minimal effort is needed for those who are familar with those R packages to transition to python.

Installtion

pip install -U datar

datar requires python 3.7.1+ and is backended by pandas (1.2+).

Example usage

from datar import f
from datar.dplyr import mutate, filter, if_else
from datar.tibble import tibble
# or
# from datar.all import f, mutate, filter, if_else, tibble

df = tibble(
    x=range(4),
    y=['zero', 'one', 'two', 'three']
)
df >> mutate(z=f.x)
"""# output
        x        y       z
  <int64> <object> <int64>
0       0     zero       0
1       1      one       1
2       2      two       2
3       3    three       3
"""

df >> mutate(z=if_else(f.x>1, 1, 0))
"""# output:
        x        y       z
  <int64> <object> <int64>
0       0     zero       0
1       1      one       0
2       2      two       1
3       3    three       1
"""

df >> filter(f.x>1)
"""# output:
        x        y
  <int64> <object>
0       2      two
1       3    three
"""

df >> mutate(z=if_else(f.x>1, 1, 0)) >> filter(f.z==1)
"""# output:
        x        y       z
  <int64> <object> <int64>
0       2      two       1
1       3    three       1
"""

# works with plotnine
# example grabbed from https://github.com/has2k1/plydata
import numpy
from datar.base import sin, pi
from plotnine import ggplot, aes, geom_line, theme_classic

df = tibble(x=numpy.linspace(0, 2*pi, 500))
(df >>
  mutate(y=sin(f.x), sign=if_else(f.y>=0, "positive", "negative")) >>
  ggplot(aes(x='x', y='y')) +
  theme_classic() +
  geom_line(aes(color='sign'), size=1.2))

# easy to integrate with other libraries
# for example: klib
import klib
from pipda import register_verb
from datar.datasets import iris
from datar.dplyr import pull

dist_plot = register_verb(func=klib.dist_plot)
iris >> pull(f.Sepal_Length) >> dist_plot()