visualization_proportions.Rmd

---
title: "Data visualization proportion"
author: "Md Easin Hasan"
date: "3/28/2021"
output: word_document
---

```{r}
data<-read.csv(file="owid-covid-data_new.csv",header=TRUE)
dim(data)

USA_20 <- data[74514:74514, ]
UK_20 <- data[74081:74081, ]
CAN_20 <- data[13100:13100, ]
FRA_20 <- data[25899:25899, ]
ITA_20 <- data[35349:35349, ]
data_20<-rbind(USA_20,UK_20,CAN_20,FRA_20,ITA_20)
data_f20 <- data_20[,c(1,4,8)]

USA_21 <- data[74602:74602, ]
UK_21 <- data[74169:74169, ]
CAN_21 <- data[13188:13188, ]
FRA_21 <- data[25987:25987, ]
ITA_21 <- data[35437:35437, ]
data_21<-rbind(USA_21,UK_21,CAN_21,FRA_21,ITA_21)
data_f21 <- data_21[,c(1,4,8)]
data_final <- rbind(data_f20,data_f21)

```

```{r}
#library(tidyverse)
#library(magrittr)
library(ggplot2)
#library(reshape2)
#library(scales)

ggplot(data_final, aes(x = date, y = total_deaths, fill = iso_code)) +
  xlab("Years") + ylab("Total deaths")+
  geom_bar(stat="identity", position = 'dodge')+
  geom_col()+
  scale_x_discrete(name = "Countries", labels=c("2020-12-31" = "2020", "2021-03-29" = "2021"))+
  scale_y_continuous(name="Total deaths")
```

From this data visualization, we can see the total deaths due to Covid-19 in Canada, France, Great Britain, Italy, and United States respectively.

## Data visualization proportion improvement:

```{r}

plot <- ggplot(data_final, aes(date, total_deaths, fill=iso_code))
plot <- plot + geom_bar(stat = "identity", position = 'dodge')+
  scale_x_discrete(name = "Years", labels=c("2020-12-31" = "2020", "2021-03-29" = "2021"))+
  scale_y_continuous(name="Total deaths")
plot
```

From this data visualization, we can see the total deaths due to Covid-19 in Canada, France, Great Britain, Italy, and United States in 2020 and 2021 respectively. The number of total deaths very higher in USA compare to other countries.