Nhập môn viết hàm trong R
Richie Cotton
Data Evangelist at DataCamp
mean có 3 đối số
x: Vector số hoặc ngày-giờ.trim: Tỉ lệ phần tử ở mỗi đầu bị loại trước khi tính.na.rm: Loại NA trước khi tính.Truyền đối số theo vị trí
mean(numbers, 0.1, TRUE)
Truyền đối số theo tên
mean(na.rm = TRUE, trim = 0.1, x = numbers)
Đối số thường dùng theo vị trí, đối số hiếm theo tên
mean(numbers, trim = 0.1, na.rm = TRUE)
library(readr)
test_scores_geography_raw <- read_csv("test_scores_geography.csv")
library(dplyr)
test_scores_geography_clean <- test_scores_geography_raw %>%
select(person_id, first_name, last_name, test_date, score)
library(readr)
test_scores_geography_raw <- read_csv("test_scores_geography.csv")
library(dplyr)
test_scores_geography_clean <- test_scores_geography_raw %>%
select(person_id, first_name, last_name, test_date, score)
library(readr)
test_scores_geography_raw <- read_csv("test_scores_geography.csv")
library(dplyr)
test_scores_geography_clean <- test_scores_geography_raw %>%
select(person_id, first_name, last_name, test_date, score)
library(readr)
test_scores_geography_raw <- read_csv("test_scores_geography.csv")
library(dplyr)
test_scores_geography_clean <- test_scores_geography_raw %>%
select(person_id, first_name, last_name, test_date, score)
library(readr)
test_scores_geography_raw <- read_csv("test_scores_geography.csv")
library(dplyr)
test_scores_geography_clean <- test_scores_geography_raw %>%
select(person_id, first_name, last_name, test_date, score)
library(readr)
test_scores_geography_raw <- read_csv("test_scores_geography.csv")
library(dplyr)
test_scores_geography_clean <- test_scores_geography_raw %>%
select(person_id, first_name, last_name, test_date, score)
library(readr)
test_scores_english_raw <- read_csv("test_scores_english.csv")
library(dplyr)
test_scores_english_clean <- test_scores_english_raw %>%
select(person_id, first_name, last_name, test_date, score)
library(readr)
test_scores_art_raw <- read_csv("test_scores_art.csv")
library(dplyr)
test_scores_art_clean <- test_scores_art_raw %>%
select(person_id, first_name, last_name, test_date, score)
library(readr)
test_scores_spanish_raw <- read_csv("test_scores_spanish.csv")
library(dplyr)
test_scores_spanish_clean <- test_scores_spanish_raw %>%
select(person_id, first_name, last_name, test_date, score)
library(readr)
test_scores_geography_raw <- read_csv("test_scores_geography.csv")
library(dplyr)
library(lubridate)
test_scores_geography_clean <- test_scores_geography_raw %>%
select(person_id, first_name, last_name, test_date, score) %>%
mutate(test_date = mdy(test_date))
library(readr)
test_scores_english_raw <- read_csv("test_scores_english.csv")
library(dplyr)
library(lubridate)
test_scores_english_clean <- test_scores_english_raw %>%
select(person_id, first_name, last_name, test_date, score) %>%
mutate(test_date = mdy(test_date))
library(readr)
test_scores_art_raw <- read_csv("test_scores_art.csv")
library(dplyr)
library(lubridate)
test_scores_art_clean <- test_scores_art_raw %>%
select(person_id, first_name, last_name, test_date, score) %>%
mutate(test_date = mdy(test_date))
library(readr)
test_scores_spanish_raw <- read_csv("test_scores_spanish.csv")
library(dplyr)
library(lubridate)
test_scores_spanish_clean <- test_scores_spanish_raw %>%
select(person_id, first_name, last_name, test_date, score) %>%
mutate(test_date = mdy(test_date))
library(readr)
test_scores_geography_raw <- read_csv("test_scores_geography.csv")
library(dplyr)
library(lubridate)
test_scores_geography_clean <- test_scores_geography_raw %>%
select(person_id, first_name, last_name, test_date, score) %>%
mutate(test_date = mdy(test_date)) %>%
filter(!is.na(score))
library(readr)
test_scores_english_raw <- read_csv("test_scores_english.csv")
library(dplyr)
library(lubridate)
test_scores_english_clean <- test_scores_english_raw %>%
select(person_id, first_name, last_name, test_date, score) %>%
mutate(test_date = mdy(test_date)) %>%
filter(!is.na(score))
library(readr)
test_scores_art_raw <- read_csv("test_scores_art.csv")
library(dplyr)
library(lubridate)
test_scores_art_clean <- test_scores_art_raw %>%
select(person_id, first_name, last_name, test_date, score) %>%
mutate(test_date = mdy(test_date)) %>%
filter(is.na(score))
library(readr)
test_scores_spanish_raw <- read_csv("test_scores_spanish.csv")
library(dplyr)
library(lubridate)
test_scores_spanish_clean <- test_scores_spanish_raw %>%
select(person_id, first_name, last_name, test_date, score) %>%
mutate(test_date = mdy(test_date)) %>%
filter(!is.na(score))
Hàm loại bỏ lặp lại trong mã, từ đó
Hàm cũng hỗ trợ tái sử dụng và chia sẻ mã.
Nhập môn viết hàm trong R