Tugas Visualisasi Data Individu
Farid Yafi Suwandi
2024-03-05
Read Data
Membaca data dari data Susenas KOR
library(readr)
Data_KOR <- read.csv("C:/Users/anggr/Downloads/2023 Maret JABAR - SUSENAS KOR Rumah Tangga.csv")
head(Data_KOR)## X URUT PSU SSU WI1 WI2 R101 R102 R105 NUINFORT R1701 R1702 R1703
## 1 0 500001 12448 123442 12435 123427 32 7 2 2 5 5 5
## 2 1 500002 31373 311039 31360 311024 32 72 1 1 1 1 1
## 3 2 500003 12092 119908 12079 119893 32 6 2 2 5 5 5
## 4 3 500004 31135 308689 31122 308674 32 72 1 2 5 5 5
## 5 4 500005 33988 336798 33975 336783 32 77 1 1 5 5 5
## 6 5 500006 34062 337531 34049 337516 32 77 1 1 5 5 5
## R1704 R1705 R1706 R1707 R1708 NUINFORT1 R1801 R1802 R1803 R1804 R1805 R1806
## 1 5 5 5 5 5 2 1 1 5 110 5 2
## 2 5 5 5 5 5 1 1 1 1 35 5 3
## 3 5 5 5 5 5 2 1 1 1 96 5 2
## 4 5 5 5 5 5 2 2 1 1 300 5 2
## 5 5 5 5 5 5 1 1 3 0 84 1 2
## 6 5 5 5 5 5 1 1 1 1 300 1 2
## R1807 R1808 R1809A R1809B R1809C R1809D R1809E R1810A R1810B R1811A R1811B
## 1 1 4 2 1 1 98 7 4 2 2 998
## 2 1 6 1 1 4 0 0 4 2 1 0
## 3 1 2 1 1 1 20 7 5 1 1 0
## 4 1 2 1 1 1 98 7 2 0 2 10
## 5 1 2 1 1 1 98 7 1 0 1 0
## 6 1 2 1 1 1 98 7 1 0 1 0
## R1812 R1813A R1813B R1813C R1813D R1813E R1814A R1814B R1815A R1815B R1815C
## 1 5 5 5 5 5 5 4 2 1 1 1
## 2 5 5 5 5 5 5 4 2 1 1 1
## 3 5 5 5 5 5 5 5 1 1 1 5
## 4 5 5 5 5 5 5 5 2 1 1 1
## 5 5 5 5 5 5 5 4 2 1 1 1
## 6 5 5 5 5 5 5 3 0 1 1 1
## R1816 R1816B1 R1816B2 R1816B3 R1817 R1901A R1901B R1901C R1901D R1901E R1901F
## 1 1 1 0 0 4 1 5 5 5 5 5
## 2 1 1 0 0 4 5 5 5 5 5 5
## 3 1 1 1 0 4 5 5 5 5 5 5
## 4 1 2 0 0 4 1 5 5 5 5 5
## 5 1 1 0 0 2 5 5 5 5 5 5
## 6 1 3 0 0 3 5 5 5 5 5 5
## R1901G R1901H R1901I R1901J R2001A R2001B R2001C R2001D R2001E R2001F R2001G
## 1 5 5 5 5 5 1 5 5 5 1 5
## 2 5 5 5 5 5 5 5 5 5 5 5
## 3 5 5 5 5 5 1 5 5 5 5 5
## 4 5 5 5 5 5 1 5 5 5 5 5
## 5 5 5 5 5 1 1 5 5 5 1 5
## 6 5 5 5 5 1 1 1 1 1 1 1
## R2001H R2001I R2001J R2001K R2001L R2001M R2002_A R2002_B R2002_C R2002_D
## 1 5 5 5 5 5 1 A
## 2 5 5 5 5 5 1 A
## 3 1 5 5 5 5 1 A
## 4 1 5 5 5 5 1 A
## 5 1 1 1 1 1 5
## 6 1 1 5 1 1 1 A
## R2101A R2101B R2101C R2201A2 R2201A3 R2201B2 R2201B3 R2201C2 R2201C3 R2201D2
## 1 2 0 2 1 1 5 0 5 0 5
## 2 1 2 0 5 0 5 0 5 0 5
## 3 1 1 0 5 0 5 0 5 0 5
## 4 1 1 0 5 0 5 0 5 0 5
## 5 1 2 0 5 0 5 0 5 0 1
## 6 4 0 0 5 0 5 0 5 0 5
## R2201D3 R2201E2 R2201E3 R2201F2 R2201F3 R2202 R2203 R2204A R2204B R2204C_A
## 1 0 5 0 5 0 2 1 1 4 A
## 2 0 5 0 5 0 1 5 0 0
## 3 0 5 0 5 0 5 5 0 0
## 4 0 5 0 5 0 5 5 0 0
## 5 1 5 0 5 0 5 5 0 0
## 6 0 5 0 5 0 5 5 0 0
## R2204C_B R2204C_C R2204C_D R2204C_E R2204C_F R2204C_G R2205A R2206A R2207
## 1 NA 5 5 1
## 2 NA 5 5 1
## 3 NA 5 5 1
## 4 NA 5 5 5
## 5 NA 5 5 5
## 6 NA 5 5 5
## R2208A2 R2208B2 R2208BI2 R2208C2 R2208D2 R2208EIB2 R2208EIIB2 R2208EIT2
## 1 5 0 0 0 0 0 0 0
## 2 5 0 0 0 0 0 0 0
## 3 5 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0
## R2208EIIT2 R2208EK2 R2208ENU2 R2208EIL2 R2208EIIL2 R2208ES2 R2208F2 R2208G2
## 1 0 0 0 0 0 0
## 2 0 0 0 0 0 0
## 3 0 0 0 0 0 0
## 4 0 0 0 0 0 0
## 5 0 0 0 0 0 0
## 6 0 0 0 0 0 0
## R2208H2 R2208A3 R2208B3 R2208BI3 R2208C3 R2208D3 R2208EIB3 R2208EIIB3
## 1 0 5 0 0 0 0 0 0
## 2 0 5 0 0 0 0 0 0
## 3 0 5 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0
## R2208EIT3 R2208EIIT3 R2208EK3 R2208ENU3 R2208EIL3 R2208EIIL3 R2208ES3 R2208F3
## 1 0 0 0 0 0 0
## 2 0 0 0 0 0 0
## 3 0 0 0 0 0 0
## 4 0 0 0 0 0 0
## 5 0 0 0 0 0 0
## 6 0 0 0 0 0 0
## R2208G3 R2208H3 R2208A4 R2208B4 R2208BI4 R2208C4 R2208D4 R2208EIB4 R2208EIIB4
## 1 0 0 1 1 600000 3 1 200000 17
## 2 0 0 5 0 0 0 0 0 0
## 3 0 0 1 1 400000 2 1 240000 20
## 4 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0
## R2208EIT4 R2208EIIT4 R2208EK4 R2208ENU4 R2208EIL4 R2208EIIL4 R2208ES4
## 1 40000 16 DAGING AYAM 59 70000 2 KG
## 2 0 0 0 0 0
## 3 60000 36 KENTANG 13 100000 5 KG
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
## R2208F4 R2208G4 R2208H4 R2208A5 R2208B5 R2208BI5 R2208C5 R2208D5 R2208EIB5
## 1 1 1 1 5 0 0 0 0 0
## 2 0 0 0 1 1 600000 3 1 110000
## 3 1 5 1 5 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0
## R2208EIIB5 R2208EIT5 R2208EIIT5 R2208EK5 R2208ENU5 R2208EIL5
## 1 0 0 0 0 0
## 2 10 26000 16 DAGING AYAM RAS 59 32000
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
## R2208EIIL5 R2208ES5 R2208F5 R2208G5 R2208H5 R2209A R2209B R2209C R2210A
## 1 0 0 0 0 5 5 5 5
## 2 1 KG 1 1 1 1 5 5 5
## 3 0 0 0 0 1 5 5 5
## 4 0 0 0 0 5 5 5 5
## 5 0 0 0 0 5 5 5 1
## 6 0 0 0 0 5 5 5 5
## R2210B1 R2210B2 R2210B3 R2210B4 R2210B5 R2211A R2211A1 R2211A2 R2211A3
## 1 5 5 5 5 5 1 600000 0 0
## 2 5 5 5 5 5 5 0 0 0
## 3 5 5 5 5 5 5 0 0 0
## 4 5 5 5 5 5 5 0 0 0
## 5 5 5 5 5 5 5 0 0 0
## 6 5 5 5 5 5 5 0 0 0
## R2211A4 R2211A5 R2211B R2211B1 R301 R302 R303 R304 R305 FWT
## 1 0 0 5 0 4 0 4 3 1 454.889101
## 2 0 0 5 0 2 0 2 2 0 172.376821
## 3 0 0 5 0 3 0 3 3 1 241.578661
## 4 0 0 5 0 7 1 6 5 1 93.673563
## 5 0 0 5 0 3 0 3 3 1 122.217556
## 6 0 0 5 0 2 0 2 2 0 7.638085Membuka Library
Membuka semua library yang diperlukan
library(tidyverse) ## Warning: package 'tidyverse' was built under R version 4.3.2## Warning: package 'lubridate' was built under R version 4.3.2## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.3 ✔ purrr 1.0.2
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.4.9000 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.0
## ── 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 errorslibrary(ggridges)## Warning: package 'ggridges' was built under R version 4.3.2library(GGally) ## Warning: package 'GGally' was built under R version 4.3.2## Registered S3 method overwritten by 'GGally':
## method from
## +.gg ggplot2library(treemap)## Warning: package 'treemap' was built under R version 4.3.2library(dplyr)
library(ggplot2)
library(forcats)data <- Data_KOR %>% mutate (R1802 = case_when(
R1802 == 1 ~ "milik sendiri",
R1802 == 2 ~ "kontrak/sewa",
R1802 == 3 ~ "bebas sewa",
R1802 == 4 ~ "dinas",
R1802 == 5 ~ "lainnya",
))Diagram Besaran
Bar Chart
data %>%
ggplot(aes(x = R1802)) +
geom_bar(fill = "purple") +
labs(title = "Kepemilikan Rumah", x = "Rumah", y = "Jumlah Pemilik") +
theme_classic() 
## Lolipop Chart
Data_KOR %>%
mutate(R1802 = case_when(
R1802 == 1 ~ "milik sendiri",
R1802 == 2 ~ "kontrak/sewa",
R1802 == 3 ~ "bebas sewa",
R1802 == 4 ~ "dinas",
R1802 == 5 ~ "lainnya"
))%>%
count(R1802) %>%
arrange(desc(n)) %>%
ggplot() +
geom_segment(aes(x = fct_reorder(as.factor(R1802), n), xend = fct_reorder(as.factor(R1802), n), y = 0, yend = n), color = "green") +
geom_point(aes(x = fct_reorder(as.factor(R1802), n), y = n), color = "red", size = 2) +
scale_y_continuous(expand = c(0, 0)) +
coord_flip() +
ggtitle("Kepemilikan Rumah") +
xlab("Kepemilikan") +
ylab("Jumlah Pemilik") +
theme_light() +
theme(plot.title = element_text(hjust = 0.5))
# Diagram Sebaran ## Read Data Membaca data dari data Susenas KP
library(readr)
Data_KP <- read.csv("C:/Users/anggr/Downloads/DataKP.csv")
head(Data_KP)## X URUT R101 R102 R105 R301 FOOD NONFOOD EXPEND KAPITA
## 1 0 500001 32 7 2 4 2660400 2304033.3 4964433 1241108.3
## 2 1 500002 32 72 1 2 1108714 525166.7 1633881 816940.5
## 3 2 500003 32 6 2 3 2413886 1398333.3 3812219 1270739.7
## 4 3 500004 32 72 1 7 7770000 4313333.3 12083333 1726190.5
## 5 4 500005 32 77 1 3 4932557 46219750.0 51152307 17050769.0
## 6 5 500006 32 77 1 2 3272143 11400716.7 14672860 7336429.8
## KALORI_KAP PROTE_KAP LEMAK_KAP KARBO_KAP WERT WEIND PSU SSU
## 1 2365.173 67.13024 43.22239 352.9857 454.889101 1819.55641 12448 123442
## 2 2611.639 69.09189 30.11824 471.9977 172.376821 344.75364 31373 311039
## 3 2526.510 68.74262 58.51762 360.4562 241.578661 724.73598 12092 119908
## 4 3655.855 141.50262 119.46043 454.9395 93.673563 655.71494 31135 308689
## 5 2330.988 78.53335 53.14161 254.8461 122.217556 366.65267 33988 336798
## 6 2330.760 68.15351 60.91893 317.6763 7.638085 15.27617 34062 337531
## WI1 WI2
## 1 12435 123427
## 2 31360 311024
## 3 12079 119893
## 4 31122 308674
## 5 33975 336783
## 6 34049 337516Histogram Chart
ggplot(Data_KP)+
geom_histogram(aes(x=PROTE_KAP),fill="#FF7F00", color="black")+
labs(title="Histogram Sebaran Protein")+
xlab("Protein")+
ylab("Jumlah")+
xlim(0,350)## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_bar()`).
Diagram Density Plot
ggplot(Data_KP)+
geom_density(aes(x=KARBO_KAP,fill= "Karbohidrat" ),color="#FF7F00")+
labs(title="Density Plot Sebaran Karbohidrat")+
xlab("Karbohidrat")+
ylab("Jumlah")+
xlim(0,350)## Warning: Removed 9426 rows containing non-finite outside the scale range
## (`stat_density()`).
# Diagram Komposisi ## Diagram Pie Chart
Data_KOR <- Data_KOR %>%
mutate(R1802 = case_when(
R1802 == 1 ~ "milik sendiri",
R1802 == 2 ~ "kontrak/sewa",
R1802 == 3 ~ "bebas sewa",
R1802 == 4 ~ "dinas",
R1802 == 5 ~ "lainnya"
))
Data_KOR %>%
ggplot(aes(x = "", y = ..count.., fill = R1802)) +
geom_bar() +
coord_polar("y", start = 0) +
ggtitle("Kepemilikan Rumah") +
theme_void() +
theme(plot.title = element_text(hjust = 0.5),
legend.position = "right")## Warning: The dot-dot notation (`..count..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(count)` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
Diagram Treemap
library(readr)
Data_KOR <- read.csv("C:/Users/anggr/Downloads/2023 Maret JABAR - SUSENAS KOR Rumah Tangga.csv")
Data_KOR %>%
mutate(R1802 = case_when(
R1802 == 1 ~ "Milik sendiri",
R1802 == 2 ~ "Kontrak/sewa",
R1802 == 3 ~ "Bebas sewa",
R1802 == 4 ~ "Dinas",
R1802 == 5 ~ "Lainnya"
))%>%
mutate(R105 = case_when(
R105 == 1 ~ "Perkotaan",
R105 == 2 ~ "Perdesaan",
))%>%
treemap(Data_KOR,
index = c("R105", "R1802"),
vSize = "X",
draw = TRUE,
title = "Kepemilikan Rumah",
fontsize.labels = 12,
fontsize.title = 14,
align.labels = list(c("center", "center")),
palette = "RdYlBu",
border.col = "white",
border.lwds = 5,
aspRatio = 1
)