If you are using the package for the first time, you will first have to install it.
# install.packages("survival")
# install.packages("openxlsx") If you have already downloaded this package in the current version of R, you will only have to load the package.
library(survival)
library(openxlsx)Load a data set from a package.
You can use the double colon symbol (:), to return the pbc object from the package survival. We store this data set to an object with the name pbc.
pbc <- survival::pbcList all your R objects
ls()## [1] "a" "A" "Age" "age_time" "age_time_sex"
## [6] "AgeCat" "ar" "ar1" "b" "B"
## [11] "basedat" "birthwt" "C" "cal_sd" "cal_var"
## [16] "Columns_com" "cSum" "dat" "dat1" "dat2"
## [21] "dat3" "dat4" "dataset1" "dataset2" "datlist"
## [26] "decimals" "demos" "DerivativeFunction" "des" "DF"
## [31] "df_test" "df1_test" "df2_test" "dice" "die"
## [36] "dt" "dt_events" "esoph" "exdat" "fam_lm"
## [41] "files" "fm1" "fm2" "fmla1" "fmla2"
## [46] "fmla3" "fmla4" "fmla5" "FUdat" "fun1"
## [51] "Fun1" "fun2" "fun3" "fun4" "fun4_correct"
## [56] "fun5" "fun5b" "fun6" "fun7" "Function2"
## [61] "google.trends1" "h" "heart" "hi" "hint"
## [66] "html_files" "htmlfiles" "i" "img" "j"
## [71] "k" "labdat" "let" "list_pbc" "list_test"
## [76] "list1" "list2" "lung" "M" "marks"
## [81] "mat" "Mat" "mat_test" "mdat" "mdat_all"
## [86] "mdat_x" "mdat_y" "mdat3" "means" "MHtest"
## [91] "mod" "mod_chol" "mod_chol2" "mod_lm" "mod_sub"
## [96] "mod1" "mod1b" "mod1c" "mod2" "mod2a"
## [101] "mod2b" "mod2c" "mod3" "my_list" "mylist"
## [106] "myList" "MyList" "mysummary" "N" "newData"
## [111] "newList" "nrj" "number" "otherlist" "out"
## [116] "output" "p" "p_adj_BH" "p_adj_Bonf" "p4"
## [121] "padj" "patient" "pbc" "pbc_chol_na" "pbc_female_bili"
## [126] "pbc_male_bili" "pbc_males" "pbc_out_bili" "pbc_sub" "pbcLong"
## [131] "pbcseq" "pbcseq.idNEW2" "pbcseq.idNEW3" "pbcseqWide" "pdfs"
## [136] "plot_summary" "plotdat" "practicals" "props" "pv"
## [141] "pval1" "pval2" "pval3" "pvals" "res"
## [146] "res1" "res2" "res3" "results" "retinopathy"
## [151] "Rfiles" "Rmd_files" "Rmdfiles" "scalar_test" "sex"
## [156] "Sex" "shinyFiles" "slides" "smod_chol" "smod1"
## [161] "smod1c" "smod2" "static" "std_num" "stratum"
## [166] "subset_data" "summary_categorical" "summary_continuous" "summary_df" "summary_list"
## [171] "summary_lm" "survey" "tab" "tab1" "test_lm"
## [176] "test_logit" "test_probit" "testdat" "testres" "textdat"
## [181] "Treatment" "ttest1" "ttest2" "vec" "vec_test"
## [186] "vec1" "vec1_test" "vec2" "vec2_test" "vec3"
## [191] "vec4" "weight" "Weight" "write_Demos_md" "write_Practicals_md"
## [196] "write_Slides_md" "wtest" "x" "X" "x1"
## [201] "x2" "xnew" "xvec" "xxx" "y"
## [206] "Y" "y1" "y2" "z"Take care: first you need to set your working directory (Rstudio: Session -> Set Working Directory -> Choose Directory…). Otherwise you do not know where your R workspace is saved.
You can also the function setwd(...) to set the working directory
getwd()## [1] "C:/Users/erler/Documents/Work/Projects/Teaching/BST02/Demos/Basic use of R"dt <- pbc[1:6, c("id", "sex", "bili", "chol")]
p <- 1
#save(dt, p, file = "data.RData")
#saveRDS(dt, file = "data1.RData")#load("data.RData")
#readRDS("data1.RData")#write.csv(dt, "mydata.csv")
#write.table(dt, "mydata.txt", sep="\t")
#write.xlsx(dt, "mydata.xlsx")