Global Pollution

file.exists("global-plastics-production.csv")

## [1] TRUE

install.packages("read.csv")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.4'
## (as 'lib' is unspecified)

## Warning: package 'read.csv' is not available for this version of R
## 
## A version of this package for your version of R might be available elsewhere,
## see the ideas at
## https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages

GPP <- read.csv("global-plastics-production.csv")

# Check the structure for Dorder Data
str(GPP)

## 'data.frame':    69 obs. of  4 variables:
##  $ Entity          : chr  "World" "World" "World" "World" ...
##  $ Code            : chr  "OWID_WRL" "OWID_WRL" "OWID_WRL" "OWID_WRL" ...
##  $ Year            : int  1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 ...
##  $ Plastic_Produced: int  2000000 2000000 2000000 3000000 3000000 4000000 5000000 5000000 6000000 7000000 ...

head(GPP)

##   Entity     Code Year Plastic_Produced
## 1  World OWID_WRL 1950          2000000
## 2  World OWID_WRL 1951          2000000
## 3  World OWID_WRL 1952          2000000
## 4  World OWID_WRL 1953          3000000
## 5  World OWID_WRL 1954          3000000
## 6  World OWID_WRL 1955          4000000

install.packages("ggplot2")

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.4'
## (as 'lib' is unspecified)

## also installing the dependencies 'colorspace', 'utf8', 'farver', 'labeling', 'munsell', 'RColorBrewer', 'viridisLite', 'fansi', 'pillar', 'pkgconfig', 'gtable', 'isoband', 'scales', 'tibble', 'withr'

library(ggplot2)

ggplot(GPP, aes(x = Plastic_Produced )) +
    geom_histogram()

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

#Evaluate attendance by weather
ggplot(GPP, aes(x=Year, y=Plastic_Produced)) +
geom_point() +
ggtitle("Plastic produce from 1950 to 2020") +
theme(plot.title = element_text(lineheight=3, face="bold", color="black", size=10))