coalesce

In [1]:

# https://dplyr.tidyverse.org/reference/coalesce.html
%run nb_helpers.py

from datar.all import *

nb_header(coalesce)

# https://dplyr.tidyverse.org/reference/coalesce.html %run nb_helpers.py from datar.all import * nb_header(coalesce)

Try this notebook on binder.

★ coalesce

¶

Replace missing values with the first non-missing value¶

The original API:
https://dplyr.tidyverse.org/reference/coalesce.html

Args:¶

  x: A vector
  *replace: Values to replace missing values with.

Returns:¶

  An array of values

In [2]:

df = tibble(x=[5,4,3,NA,2,NA,1,NA])
df >> mutate(y=coalesce(f.x, 0)) >> pull(f.y)

df = tibble(x=[5,4,3,NA,2,NA,1,NA]) df >> mutate(y=coalesce(f.x, 0)) >> pull(f.y)

Out[2]:

0    5.0
1    4.0
2    3.0
3    0.0
4    2.0
5    0.0
6    1.0
7    0.0
Name: y, dtype: float64

In [3]:

df = tibble(
    y=[1,2,NA,NA,5],
    z=[NA,NA,3,4,5]
)
df >> mutate(m=coalesce(f.y, f.z)) >> pull(f.m)

df = tibble( y=[1,2,NA,NA,5], z=[NA,NA,3,4,5] ) df >> mutate(m=coalesce(f.y, f.z)) >> pull(f.m)

Out[3]:

0    1.0
1    2.0
2    3.0
3    4.0
4    5.0
Name: m, dtype: float64