Tugas 1 Visualisasi Data

library(esquisse)
library(ggplot2)
library(tidyverse)

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library(tidymodels)

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Reading File

data_calories <- read.csv("C:/Users/lenovo/OneDrive/ドキュメント/Visdat/Tugas 1/calories.csv")
data_climate <- read.csv("C:/Users/lenovo/OneDrive/ドキュメント/Visdat/Tugas 1/DailyDelhiClimateTest.csv")

data_climate$date <- as.Date(data_climate$date)
str(data_climate)

## 'data.frame':    114 obs. of  5 variables:
##  $ date        : Date, format: "2017-01-01" "2017-01-02" ...
##  $ meantemp    : num  15.9 18.5 17.1 18.7 18.4 ...
##  $ humidity    : num  85.9 77.2 81.9 70 74.9 ...
##  $ wind_speed  : num  2.74 2.89 4.02 4.54 3.3 ...
##  $ meanpressure: num  59 1018 1018 1016 1014 ...

Visualisasi Data dengan Esquisse

#esquisse::esquisser("data_calories")
#esquisse::esquisser("data_climate")

Visualisasi Data Distribusi (Histogram)

ggplot(data_calories) +
  aes(x = Calories) +
  geom_histogram(bins = 30L, fill = "pink", color = "black", linewidth = 0.7) + 
  geom_vline(aes(xintercept = mean(Calories)), color = "blue", linetype = "dashed", linewidth = 1) +
  labs(title = "Prediksi Kalori yang Terbakar Akibat Olahraga", 
       x = "Jumlah Kalori (Cal)", 
       y = "Frekuensi") +  
  theme_minimal() + 
  theme(plot.title = element_text(hjust = 0.5), 
        axis.title.x = element_text(size = 12),  
        axis.title.y = element_text(size = 12)) 

Visualisasi Data Time Series (Line Chart)

ggplot(data_climate) +
  aes(x = date, y = humidity) +
  geom_line(colour = "#957dad", linewidth = 0.5) + 
  labs(title = "Perubahan Kelembapan Tahun 2017 di Delhi", 
       x = "Bulan (2017)",  
       y = "Kelembapan (gr/m³)") +  
  theme_minimal() +  
  theme(plot.title = element_text(hjust = 0.5, size = 14, face = "bold"), 
        axis.title.x = element_text(size = 10),  
        axis.title.y = element_text(size = 10), 
        axis.text = element_text(size = 10))