Data Analysis of Covid 19 in Indonesia
Art
2022-12-24
Mengakses API covid.go.id
library(httr)## Warning: package 'httr' was built under R version 4.2.2set_config(config(ssl_verifypeer = 0L))
resp <- GET("https://storage.googleapis.com/dqlab-dataset/update.json")
# Status Code
status_code(resp)## [1] 200# Status Code - 2
identical(resp$status_code, status_code(resp))## [1] TRUE# Header API
headers(resp)## $`x-guploader-uploadid`
## [1] "ADPycduPUGCTwtpfQrAu_ApGlgQ88QsGLkUIPEeenGRe-86RAYLlJ5MdxiLaGFFij7VYe8TeZOfKMUlb8gEGO4ex-Avx4llMVQdj"
##
## $`x-goog-generation`
## [1] "1654513959565478"
##
## $`x-goog-metageneration`
## [1] "1"
##
## $`x-goog-stored-content-encoding`
## [1] "identity"
##
## $`x-goog-stored-content-length`
## [1] "311897"
##
## $`x-goog-hash`
## [1] "crc32c=GMMqEA=="
##
## $`x-goog-hash`
## [1] "md5=8aR/820+lfYyWNlv5bLUOQ=="
##
## $`x-goog-storage-class`
## [1] "STANDARD"
##
## $`accept-ranges`
## [1] "bytes"
##
## $`content-length`
## [1] "311897"
##
## $server
## [1] "UploadServer"
##
## $date
## [1] "Sat, 24 Dec 2022 06:00:16 GMT"
##
## $expires
## [1] "Sat, 24 Dec 2022 07:00:16 GMT"
##
## $`cache-control`
## [1] "public, max-age=3600"
##
## $`last-modified`
## [1] "Mon, 06 Jun 2022 11:12:39 GMT"
##
## $etag
## [1] "\"f1a47ff36d3e95f63258d96fe5b2d439\""
##
## $`content-type`
## [1] "application/json"
##
## $age
## [1] "0"
##
## $`alt-svc`
## [1] "h3=\":443\"; ma=2592000,h3-29=\":443\"; ma=2592000,h3-Q050=\":443\"; ma=2592000,h3-Q046=\":443\"; ma=2592000,h3-Q043=\":443\"; ma=2592000,quic=\":443\"; ma=2592000; v=\"46,43\""
##
## attr(,"class")
## [1] "insensitive" "list"Extracting the contents of the Response
cov_id_raw <- content(resp, as = "parsed", simplifyVector = TRUE)Extracting the contents of the Response - Pt 2
length(cov_id_raw)## [1] 2names(cov_id_raw)## [1] "data" "update"cov_id_update <- cov_id_raw$updateData Analysis
lapply(cov_id_update, names)## $penambahan
## [1] "jumlah_positif" "jumlah_meninggal" "jumlah_sembuh" "jumlah_dirawat"
## [5] "tanggal" "created"
##
## $harian
## [1] "key_as_string" "key" "doc_count"
## [4] "jumlah_meninggal" "jumlah_sembuh" "jumlah_positif"
## [7] "jumlah_dirawat" "jumlah_positif_kum" "jumlah_sembuh_kum"
## [10] "jumlah_meninggal_kum" "jumlah_dirawat_kum"
##
## $total
## [1] "jumlah_positif" "jumlah_dirawat" "jumlah_sembuh" "jumlah_meninggal"cov_id_update$penambahan$tanggal## [1] "2022-05-14"cov_id_update$penambahan$jumlah_sembuh## [1] 416cov_id_update$penambahan$jumlah_meninggal## [1] 5cov_id_update$total$jumlah_positif## [1] 6050519cov_id_update$total$jumlah_meninggal## [1] 156453What about Covid in West Java?
library(httr)
set_config(config(ssl_verifypeer = 0L))
resp_jabar <- GET("https://storage.googleapis.com/dqlab-dataset/prov_detail_JAWA_BARAT.json")
cov_jabar_raw <- content(resp_jabar, as = "parsed", simplifyVector = TRUE)
names(cov_jabar_raw)## [1] "last_date" "provinsi" "kasus_total"
## [4] "kasus_tanpa_tgl" "kasus_dengan_tgl" "meninggal_persen"
## [7] "meninggal_tanpa_tgl" "meninggal_dengan_tgl" "sembuh_persen"
## [10] "sembuh_tanpa_tgl" "sembuh_dengan_tgl" "list_perkembangan"
## [13] "data"cov_jabar_raw$kasus_total## [1] 1105134cov_jabar_raw$meninggal_persen## [1] 1.425619cov_jabar_raw$sembuh_persen## [1] 98.28238• What is the total number of COVID-19 cases in West Java? • What is the percentage of deaths from COVID-19 in West Java? • What is the percentage of the cure rate from COVID-19 in West Java?
Get full of information
# Seeing the Development of Covid in West Java
cov_jabar <- cov_jabar_raw$list_perkembangan
# see type of data
str(cov_jabar)## 'data.frame': 785 obs. of 9 variables:
## $ tanggal : num 1.58e+12 1.58e+12 1.58e+12 1.58e+12 1.58e+12 ...
## $ KASUS : int 1 1 1 1 0 0 0 0 0 1 ...
## $ MENINGGAL : int 1 0 0 0 0 0 0 0 1 0 ...
## $ SEMBUH : int 0 0 0 0 0 0 0 0 0 0 ...
## $ DIRAWAT_OR_ISOLASI : int 0 1 1 1 0 0 0 0 -1 1 ...
## $ AKUMULASI_KASUS : int 1 2 3 4 4 4 4 4 4 5 ...
## $ AKUMULASI_SEMBUH : int 0 0 0 0 0 0 0 0 0 0 ...
## $ AKUMULASI_MENINGGAL : int 1 1 1 1 1 1 1 1 2 2 ...
## $ AKUMULASI_DIRAWAT_OR_ISOLASI: int 0 1 2 3 3 3 3 3 2 3 ...# Show a couple of data
head(cov_jabar)## tanggal KASUS MENINGGAL SEMBUH DIRAWAT_OR_ISOLASI AKUMULASI_KASUS
## 1 1.583194e+12 1 1 0 0 1
## 2 1.583280e+12 1 0 0 1 2
## 3 1.583366e+12 1 0 0 1 3
## 4 1.583453e+12 1 0 0 1 4
## 5 1.583539e+12 0 0 0 0 4
## 6 1.583626e+12 0 0 0 0 4
## AKUMULASI_SEMBUH AKUMULASI_MENINGGAL AKUMULASI_DIRAWAT_OR_ISOLASI
## 1 0 1 0
## 2 0 1 1
## 3 0 1 2
## 4 0 1 3
## 5 0 1 3
## 6 0 1 3The Data
#set libraray yang dibutuhkan
library(dplyr)## Warning: package 'dplyr' was built under R version 4.2.2##
## 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#membuat variabel dataset baru
new_cov_jabar <-
cov_jabar %>%
#menghapus kolom
select(-contains("DIRAWAT_OR_ISOLASI")) %>%
select(-starts_with("AKUMULASI")) %>%
#mengubah nama kolom
rename(
kasus_baru = KASUS,
meninggal = MENINGGAL,
sembuh = SEMBUH
) %>%
#memperbaiki data kolom tanggal
mutate(
tanggal = as.POSIXct(tanggal / 1000, origin = "1970-01-01"),
tanggal = as.Date(tanggal)
)
#melihat tipe data
str(new_cov_jabar) ## 'data.frame': 785 obs. of 4 variables:
## $ tanggal : Date, format: "2020-03-03" "2020-03-04" ...
## $ kasus_baru: int 1 1 1 1 0 0 0 0 0 1 ...
## $ meninggal : int 1 0 0 0 0 0 0 0 1 0 ...
## $ sembuh : int 0 0 0 0 0 0 0 0 0 0 ...View the Graph
#set library yang dibutuhkan
library(ggplot2)## Warning: package 'ggplot2' was built under R version 4.2.2#membuat bar chart
library(hrbrthemes)## Warning: package 'hrbrthemes' was built under R version 4.2.2## NOTE: Either Arial Narrow or Roboto Condensed fonts are required to use these themes.## Please use hrbrthemes::import_roboto_condensed() to install Roboto Condensed and## if Arial Narrow is not on your system, please see https://bit.ly/arialnarrowggplot(data = new_cov_jabar, aes(x = tanggal, y = kasus_baru)) +
geom_col()
View the Graph - Pt 2
#set library yang dibutuhkan
library(ggplot2)
library(hrbrthemes)
#membuat bar chart modifikasi
ggplot(new_cov_jabar, aes(tanggal, kasus_baru)) +
geom_col(fill = "salmon") +
labs(
x = NULL,
y = "Jumlah kasus",
title = "Kasus Harian Positif COVID-19 di Jawa Barat",
subtitle = "Terjadi pelonjakan kasus di awal bulan Juli akibat klaster Secapa AD Bandung",
caption = "Sumber data: covid.19.go.id"
) +
theme_ipsum(
base_size = 13,
plot_title_size = 21,
grid = "Y",
ticks = TRUE
) +
theme(plot.title.position = "plot")## Warning in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)): font family not
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## The graph of recovered cases
library(ggplot2)
library(hrbrthemes)
#membuat bar chart kasus sembuh
ggplot(new_cov_jabar, aes(tanggal, sembuh)) +
geom_col(fill = "olivedrab2") +
labs(
x = NULL,
y = "Jumlah kasus",
title = "Kasus Harian Sembuh Dari COVID-19 di Jawa Barat",
caption = "Sumber data: covid.19.go.id"
) +
theme_ipsum(
base_size = 13,
plot_title_size = 21,
grid = "Y",
ticks = TRUE
) +
theme(plot.title.position = "plot")## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
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The graph of death cases
library(ggplot2)
library(hrbrthemes)
ggplot(new_cov_jabar, aes(tanggal, meninggal)) +
geom_col(fill = "darkslategray4") +
labs(
x = NULL,
y = "Jumlah kasus",
title = "Kasus Harian Meninggal Akibat COVID-19 di Jawa Barat",
caption = "Sumber data: covid.19.go.id"
) +
theme_ipsum(
base_size = 13,
plot_title_size = 21,
grid = "Y",
ticks = TRUE
) +
theme(plot.title.position = "plot")## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
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Is this week better?
library(dplyr)
library(lubridate)## Warning: package 'lubridate' was built under R version 4.2.2## Loading required package: timechange## Warning: package 'timechange' was built under R version 4.2.2##
## Attaching package: 'lubridate'## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, union#membuat variabel dataset
cov_jabar_pekanan <- new_cov_jabar %>%
count(
tahun = year(tanggal),
pekan_ke = week(tanggal),
wt = kasus_baru,
name = "jumlah"
)
#melakukan inspeksi data
glimpse(cov_jabar_pekanan)## Rows: 115
## Columns: 3
## $ tahun <dbl> 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2…
## $ pekan_ke <dbl> 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24…
## $ jumlah <int> 1, 3, 16, 41, 98, 149, 153, 155, 156, 284, 803, 175, 395, 203…Answering questions
#set library yang dibutuhkan
library(dplyr)
#membuat variabel dataset
cov_jabar_pekanan <-
cov_jabar_pekanan %>%
mutate(
jumlah_pekanlalu = dplyr::lag(jumlah, 1),
jumlah_pekanlalu = ifelse(is.na(jumlah_pekanlalu), 0, jumlah_pekanlalu),
lebih_baik = jumlah < jumlah_pekanlalu
)
#melakukan inspeksi data
glimpse(cov_jabar_pekanan)## Rows: 115
## Columns: 5
## $ tahun <dbl> 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020,…
## $ pekan_ke <dbl> 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22…
## $ jumlah <int> 1, 3, 16, 41, 98, 149, 153, 155, 156, 284, 803, 175, …
## $ jumlah_pekanlalu <dbl> 0, 1, 3, 16, 41, 98, 149, 153, 155, 156, 284, 803, 17…
## $ lebih_baik <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALS…Make out Bar Chart
library(dplyr)
cov_jabar_akumulasi <-
new_cov_jabar %>%
transmute(
tanggal,
akumulasi_aktif = cumsum(kasus_baru) - cumsum(sembuh) - cumsum(meninggal),
akumulasi_sembuh = cumsum(sembuh),
akumulasi_meninggal = cumsum(meninggal)
)
tail(cov_jabar_akumulasi)## tanggal akumulasi_aktif akumulasi_sembuh akumulasi_meninggal
## 780 2022-04-21 11628 1077361 15731
## 781 2022-04-22 10753 1078344 15735
## 782 2022-04-23 9882 1079297 15737
## 783 2022-04-24 8709 1080519 15748
## 784 2022-04-25 5428 1083851 15751
## 785 2022-04-26 3253 1086129 15752library(ggplot2)
library(hrbrthemes)
ggplot(cov_jabar_pekanan[cov_jabar_pekanan$tahun==2020,], aes(pekan_ke, jumlah, fill =lebih_baik)) +
geom_col(show.legend = FALSE) +
scale_x_continuous(breaks = 9:29, expand = c(0,0)) +
scale_fill_manual(values = c("TRUE" = "seagreen3", "FALSE" = "salmon")) +
labs(
x = NULL,
y = "Jumlah kasus",
title = "Kasus Pekanan Positif COVID-19 di Jawa Barat",
subtitle = "Kolom hijau menunjukan penambahan kasus baru lebih sedikit dibandingkan satu pekan sebelumnya",
caption = "Sumber data: covid.19.go.id"
) +
theme_ipsum(
base_size = 13,
plot_title_size = 21,
grid = "Y",
ticks = TRUE
) +
theme(plot.title.position = "plot")## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
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##Patterns and dynamics
library(dplyr)
cov_jabar_akumulasi <-
new_cov_jabar %>%
transmute(
tanggal,
akumulasi_aktif = cumsum(kasus_baru) - cumsum(sembuh) - cumsum(meninggal),
akumulasi_sembuh = cumsum(sembuh),
akumulasi_meninggal = cumsum(meninggal)
)
tail(cov_jabar_akumulasi)## tanggal akumulasi_aktif akumulasi_sembuh akumulasi_meninggal
## 780 2022-04-21 11628 1077361 15731
## 781 2022-04-22 10753 1078344 15735
## 782 2022-04-23 9882 1079297 15737
## 783 2022-04-24 8709 1080519 15748
## 784 2022-04-25 5428 1083851 15751
## 785 2022-04-26 3253 1086129 15752Make Line chart
library(ggplot2)
ggplot(data = cov_jabar_akumulasi, aes(x = tanggal, y = akumulasi_aktif)) +
geom_line()
Transformation Data
library(dplyr)
library(tidyr)## Warning: package 'tidyr' was built under R version 4.2.2dim(cov_jabar_akumulasi)## [1] 785 4cov_jabar_akumulasi_pivot <-
cov_jabar_akumulasi %>%
gather(
key = "kategori",
value = "jumlah",
-tanggal
) %>%
mutate(
kategori = sub(pattern = "akumulasi_", replacement = "", kategori)
)
dim(cov_jabar_akumulasi_pivot)## [1] 2355 3glimpse(cov_jabar_akumulasi_pivot)## Rows: 2,355
## Columns: 3
## $ tanggal <date> 2020-03-03, 2020-03-04, 2020-03-05, 2020-03-06, 2020-03-07, …
## $ kategori <chr> "aktif", "aktif", "aktif", "aktif", "aktif", "aktif", "aktif"…
## $ jumlah <int> 0, 1, 2, 3, 3, 3, 3, 3, 2, 3, 6, 6, 4, 2, 13, 14, 17, 29, 34,…Finally
library(ggplot2)
library(hrbrthemes)
#membuat grafik komparasi
ggplot(cov_jabar_akumulasi_pivot, aes(tanggal, jumlah, colour = (kategori))) +
geom_line(size = 0.9) +
scale_y_continuous(sec.axis = dup_axis(name = NULL)) +
scale_colour_manual(
values = c(
"aktif" = "salmon",
"meninggal" = "darkslategray4",
"sembuh" = "olivedrab2"
),
labels = c("Aktif", "Meninggal", "Sembuh")
) +
labs(
x = NULL,
y = "Jumlah kasus akumulasi",
colour = NULL,
title = "Dinamika kasus COVID-19 di Jawa Barat",
caption = "Sumber data: covid.19.go.id"
) +
theme_ipsum(
base_size = 13,
plot_title_size = 21,
grid = "Y",
ticks = TRUE
) +
theme(
plot.title = element_text(hjust = 0.5),
legend.position = "top"
)## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
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