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df = read.csv2("D:\\TAM DAN NON-ORTHO\\11. Non Ortho_ORAL HEATHY SURVEY FORM\\11.3 GINGIVAL INDEX (GI)\\11.3 GINGIVAL INDEX (GI).csv")
library(lessR)
## Warning: package 'lessR' was built under R version 4.5.2
## 
## lessR 4.5                            feedback: gerbing@pdx.edu 
## --------------------------------------------------------------
## > d <- Read("")  Read data file, many formats available, e.g., Excel
##   d is the default data frame, data= in analysis routines optional
## 
## Many examples of reading, writing, and manipulating data, graphics,
## testing means and proportions, regression, factor analysis,
## customization, forecasting, and aggregation to pivot tables.
##   Enter: browseVignettes("lessR")
## 
## View lessR updates, now including modern time series forecasting
##   and many, new Plotly interactive visualizations output. Most
##   visualization functions are now reorganized to three functions:
##      Chart(): type="bar", "pie", "radar", "bubble", "treemap", "icicle"
##      X(): type="histogram", "density", "vbs" and more
##      XY(): type="scatter" for a scatterplot, or "contour", "smooth"
##    Most previous function calls still work, such as:
##      BarChart(), Histogram, and Plot().
##   Enter: news(package="lessR"), or ?Chart, ?X, or ?XY
## There is also Flows() for Sankey flow diagrams, see ?Flows
## 
## Interactive data analysis for constructing visualizations.
##   Enter: interact()
library(labelled)
## Warning: package 'labelled' was built under R version 4.5.3
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:lessR':
## 
##     order_by, recode, rename
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(writexl)
## Warning: package 'writexl' was built under R version 4.5.3
# 1. MÃ HÓA GINGIVAL INDEX VÀ GHI ĐÈ LÊN BẢNG GỐC (df)
df <- df %>%
  mutate(
    # Loại trừ STT, ID và áp dụng mã hóa cho tất cả các cột mặt răng còn lại
    across(
      -c(STT, ID),
      ~ factor(., 
               levels = c(0, 1, 2, 3, 88, 99), 
               labels = c("Normal gingival", 
                          "Mild inflammation; slight erythema; minimal superficial alterations. No bleeding", 
                          "Moderate inflammation; erythema; bleeding on probing", 
                          "Severe inflammation; severe erythema and swelling; tendency to spontaneous bleeding; possible ulceration", 
                          "Not recorded", 
                          "Missing tooth"))
    )
  )

# 2. GẮN NHÃN MÔ TẢ (LABELS) HOÀN TOÀN TỰ ĐỘNG
# Bước 2.1: Lấy danh sách tên tất cả các biến (trừ STT và ID)
gingival_vars <- setdiff(names(df), c("STT", "ID"))

# Bước 2.2: Tự động dịch các hậu tố viết tắt thành tên mặt răng đầy đủ
nhan_gingival <- gingival_vars %>%
  gsub("_Disto", " Distal Surface", .) %>%
  gsub("_Buc", " Buccal Surface", .) %>%
  gsub("_Mesio", " Mesial Surface", .) %>%
  gsub("_Lin", " Lingual Surface", .) %>%
  paste("Gingival Index Tooth", .) # Thêm cụm từ nhận diện vào phía trước để phân biệt với Plaque Index

# Bước 2.3: Gán danh sách nhãn vừa tạo vào bảng df
names(nhan_gingival) <- gingival_vars
var_label(df) <- as.list(nhan_gingival)
# Tạo một bảng copy tạm thời để đổi tên tiêu đề
df_export <- df %>%
  # Lệnh này biến toàn bộ các "Nhãn dài" thành tên cột thực sự
  setNames(var_label(., unlist = TRUE))

# Sau đó xuất cái bảng tạm này ra Excel
write_xlsx(df_export, "D:\\TAM DAN - NON ORTHO (NEW)\\11.3\\11.3 GINGIVAL INDEX (GI).xlsx")