Chapter 2
Nguyen Tuan Anh
2025-12-25
#De Bai lam viec voi tap du lieu economic va truc quan bieu dien ti le thu nhap ca nhan cua nguoi dan My. Chung ta can truc quan de lieu theo chuoi thoi gian de xem xet ti le thu thap cua nguoi dan My tang hay giam tu 1
library(ggplot2)
library(scales)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
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## intersect, setdiff, setequal, unionlibrary(plotly)##
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## layoutdata("economics")
economics %>% head()## # A tibble: 6 × 6
## date pce pop psavert uempmed unemploy
## <date> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1967-07-01 507. 198712 12.6 4.5 2944
## 2 1967-08-01 510. 198911 12.6 4.7 2945
## 3 1967-09-01 516. 199113 11.9 4.6 2958
## 4 1967-10-01 512. 199311 12.9 4.9 3143
## 5 1967-11-01 517. 199498 12.8 4.7 3066
## 6 1967-12-01 525. 199657 11.8 4.8 3018truc quan du lieu
{r} ggplot(data = economics, mapping = aes(x = date, y = psavert)) + geom_line(color=#00FFFF) + labs(tilte = “bang tu nam 1967 den 2015”, x=“time”, y= “ti le tiet kiem” ) Nguyễn
library(ggplot2)
library(scales)
library(dplyr)
library(plotly)
data("economics")
head(economics)## # A tibble: 6 × 6
## date pce pop psavert uempmed unemploy
## <date> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1967-07-01 507. 198712 12.6 4.5 2944
## 2 1967-08-01 510. 198911 12.6 4.7 2945
## 3 1967-09-01 516. 199113 11.9 4.6 2958
## 4 1967-10-01 512. 199311 12.9 4.9 3143
## 5 1967-11-01 517. 199498 12.8 4.7 3066
## 6 1967-12-01 525. 199657 11.8 4.8 3018truc quan du lieu
ggplot(data = economics, mapping = aes(x = date, y = psavert)) +
geom_line(color="#880000", size = 1) +
geom_smooth() +
scale_x_date(date_breaks = "5 years", labels = date_format("%b-%y")) +
labs(title = "bang tu nam 1967 den 2015",
subtitle = " 5 nam tu 1967 den 2015",
x="time",
y= "ti le tiet kiem"
)+
theme_minimal() -> p## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
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## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.ggplotly(p)## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'thuc hanh noi dung du lieu
library(quantmod)## Loading required package: xts## Loading required package: zoo##
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## method from
## as.zoo.data.frame zoolibrary(ggplot2)
library(scales)
library(dplyr)
library(plotly)lay du lieu co phieu apple
apple <- getSymbols("AAPL", return.class="data.frame", from = "2025-1-7")
tail(AAPL, n=4)## AAPL.Open AAPL.High AAPL.Low AAPL.Close AAPL.Volume AAPL.Adjusted
## 2025-12-31 273.06 273.68 271.75 271.86 27293600 271.86
## 2026-01-02 272.26 277.84 269.00 271.01 37838100 271.01
## 2026-01-05 270.64 271.51 266.14 267.26 45647200 267.26
## 2026-01-06 267.00 267.55 262.12 262.36 52282100 262.36lay du lieu co phieu nvidia
nvidia <- getSymbols("NVDA", return.class="data.frame", from = "2025-1-7")
tail(NVDA, n=4)## NVDA.Open NVDA.High NVDA.Low NVDA.Close NVDA.Volume NVDA.Adjusted
## 2025-12-31 189.57 190.56 186.49 186.50 120100500 186.50
## 2026-01-02 189.84 192.93 188.26 188.85 148240500 188.85
## 2026-01-05 191.76 193.63 186.15 188.12 183529700 188.12
## 2026-01-06 190.52 192.17 186.82 187.24 176174700 187.24tien xu li du lieu apple
apple <- AAPL %>%
mutate(Date = as.Date(row.names(.))) %>%
select(Date, AAPL.Close) %>%
rename(Close = AAPL.Close) %>%
mutate(Company = "Apple")tien xu li du lieu nvidia
nvidia <- NVDA %>%
mutate(Date = as.Date(row.names(.),format = "%Y-%m-%d")) %>%
select(Date, NVDA.Close) %>%
rename(Close = NVDA.Close) %>%
mutate(Company = "nvidia")gop <- rbind(apple, nvidia)truc quan du lieu
ggplot(data=gop, mapping = aes(x=Date, y=Close, color=Company)) +
geom_line(size=1) +
geom_smooth() +
scale_x_date(date_breaks = "1 month", labels = date_format("%b-%y")) +
theme(axis.text.x = element_text(angle = 36, hjust = 1)) +
labs(title="Gia dong cua co phieu",
subtitle = "12-2024 den nay",
x="",
y="Closing price")## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'