n_distinct

In [1]:

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

from datar.all import sample, n_distinct

nb_header(sample, n_distinct, book='n_distinct')

# https://dplyr.tidyverse.org/reference/n_distinct.html %run nb_helpers.py from datar.all import sample, n_distinct nb_header(sample, n_distinct, book='n_distinct')

Try this notebook on binder.

★ sample

¶

Sample a vector¶

Args:¶

  x: a vector or scaler
  size: the size of the sample
  replace: whether to sample with replacement
  prob: the probabilities of sampling each element

Returns:¶

  The sampled vector

★ n_distinct

¶

Count the number of distinct values¶

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

Args:¶

  _data: A data frame
  na_rm: If True, remove missing values before counting.

Returns:¶

  The number of distinct values

In [2]:

x = sample(range(10), 1e5, replace=True)
len(x)

x = sample(range(10), 1e5, replace=True) len(x)

Out[2]:

100000

In [3]:

n_distinct(x)

n_distinct(x)

Out[3]:

10