Publications by Lilis Indra Purnama
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Nomor 1 library(readxl) library(ggplot2) Nomor1 <- read_xlsx("D:/Cooliah/Semester 4/Analisis Eksplorasi Data/UAS/Data2.xlsx", sheet = 1) Nomor1 ## # A tibble: 50 × 3 ## Participant `Daily Sleep Duration (in hours)` `Productivity Score` ## <dbl> <dbl> <dbl> ## 1 1 ...
4800 sym R (39871 sym/107 pcs) 10 img
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library(readxl) df <- read_excel("D:/Cooliah/Semester 4/Analisis Eksplorasi Data/Pertemuan 3/Data.xlsx", sheet="Sheet2") df ## # A tibble: 136 × 2 ## TPT Waktu ## <chr> <chr> ## 1 5.97 Februari 2022 ## 2 5.47 Februari 2022 ## 3 6.17 Februari 2022 ## 4 4.40 Februari 2022 ## 5 4.70 Februari 2022 ## 6 4.74...
32 sym R (7207 sym/24 pcs) 5 img
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data(mtcars) head(mtcars) ## mpg cyl disp hp drat wt qsec vs am gear carb ## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 ## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 ## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 ## Hornet 4 Drive 21.4 6 ...
19 sym R (3222 sym/13 pcs) 3 img
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library(ggplot2) library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ lubridate 1.9.3 ✔ tibble 3.2.1 ## ✔ purrr 1.0.2 �...
1000 sym R (526057 sym/30 pcs) 4 img
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IMPORT DATA library(ggplot2) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union d1 <- read.csv2("D:/Cooliah/Semester 4/Visualisasi Data/2023 Maret JABAR - SUSENA...
3547 sym R (5417 sym/14 pcs) 6 img
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Nama : Lilis Indra Purnama Sari NIM : G1401221014 library(readxl) Data <- read_excel("D:/Cooliah/Semester 4/Perancangan Percobaan/Pertemuan 6/Data Tugas Kuliah.xlsx") Data ## # A tibble: 45 × 4 ## Kelompok Varietas Nitrogen Respon ## <dbl> <chr> <chr> <chr> ## 1 1 V1 N1 14.9 ## 2 1 V1 N2 ...
1274 sym R (1433 sym/10 pcs)
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data <- read.csv("C:/Users/ASUS/Downloads/data liver.csv", sep=";") y<-data$Y x1<-data$X1 x2<-data$X2 x3<-data$X3 x4<-data$X4 x5<-data$X5 x6<-data$X6 data<-data.frame(cbind(y,x1,x2,x3,x4,x5,x6)) head(data) ## y x1 x2 x3 x4 x5 x6 ## 1 158.76 16.36 8.90 3.47 6.02 57.42 1.11 ## 2 197.19 26.68 21.22 3.53 12.07 61....
5230 sym 3 img
KUIS UAS MANDAREL
Global Education Data ini menyajikan perspektif global mengenai pendidikan, serta memberikan beragam wawasan penting mengenai sistem pendidikan di seluruh dunia. csv <- read.csv("C:/Users/ASUS/Downloads/GlobalEducation.csv", sep = ","); csv ## Countries.and.areas Latitude Longitude ## 1 Afghanistan 33.93...
1518 sym 2 img
Praktikum 13 Mandarel
Mengetahui hubungan antara tingkat kejahatan di beberapa negara bagian Amerika Serikat Data diperoleh dari data set yang ada di R head (USArrests) ## Murder Assault UrbanPop Rape ## Alabama 13.2 236 58 21.2 ## Alaska 10.0 263 48 44.5 ## Arizona 8.1 294 80 31.0 ## Arkansas 8.8 1...
423 sym 2 img