filter-na2

2023

eda

string

Published

May 14, 2023

Aufgabe

Filtern Sie alle Zeilen mit fehlende Werte im Datensatz penguins!

Lösung

Setup

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.3     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.0
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

d_path <- "https://vincentarelbundock.github.io/Rdatasets/csv/palmerpenguins/penguins.csv"
d <- read_csv(d_path)

Rows: 344 Columns: 9
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): species, island, sex
dbl (6): rownames, bill_length_mm, bill_depth_mm, flipper_length_mm, body_ma...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

nrow(d)

[1] 344

Weg 1

d %>% 
  filter(!complete.cases(.)) %>% 
  nrow()

[1] 11

Weg 2

d %>% 
  filter(if_any(everything(), ~ is.na(.))) %>% 
  nrow()

[1] 11

Categories:

2023
eda
na
string