LA-01

Introduction

This report analyzes air quality data using time-series plots, seasonal trends, and correlations.

Load Libraries

library(ggplot2)
library(tidyverse)

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library(lubridate)
library(corrplot)

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library(magrittr)

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##     extract

data <- read.csv("C:/Users/Vigne/Downloads/air+quality/AirQualityUCI.csv", sep=";", dec=",")
data <- data[,1:13]

data$Datetime <- lubridate::dmy_hms(paste(data$Date, data$Time))

## Warning: 114 failed to parse.

data <- na.omit(data)

data$Month <- lubridate::month(data$Datetime, label = TRUE)

pollutants <- data %>%
  select(Datetime, CO.GT., NO2.GT., NOx.GT.) %>%
  pivot_longer(-Datetime)

corr_data <- data %>%
  select(CO.GT., NO2.GT., NOx.GT., PT08.S1.CO., PT08.S2.NMHC.)

corr_matrix <- cor(corr_data, use = "complete.obs")

Time Series

ggplot(data, aes(Datetime, CO.GT.)) + geom_line()

Multi-line Plot

pollutants <- data %>%
  select(Datetime, CO.GT., NO2.GT., NOx.GT.) %>%
  pivot_longer(-Datetime)

ggplot(pollutants, aes(Datetime, value, color=name)) + geom_line()

Seasonal Trend

ggplot(data, aes(Month, CO.GT.)) + geom_boxplot()

## Correlation Heatmap

corr_data <- data %>%
  select(CO.GT., NO2.GT., NOx.GT., PT08.S1.CO., PT08.S2.NMHC.)

corr_matrix <- cor(corr_data, use="complete.obs")

corrplot(corr_matrix, method="color")