Data Visualization

#Load data into R workspace( import directly as this command is specific to the Path specified) #Load the Library that can load data into the workspace library(readr) # Data Loading led <- read_csv("C:/Users/David/Desktop/DATA_ANALYSIS_R/Final_Answer/led.csv") View(led) dim(led) size(led) #The library required for the data manipulation and visualisation library(tidyverse) class(led) sum(is.na(led)) summary(led) #Cleaning the data by ommitting the missing values ASP_LED_CLEAN <- na.omit(led) sum(is.na(ASP_LED_CLEAN)) summary(ASP_LED_CLEAN) #Selecting the data we want to use after cleaning LED_WHO_DS<-select(ASP_LED_CLEAN,Lifeexpectancy,Year,BMI,Incomecompositionofresources,Alcohol) view(LED_WHO_DS) summary(LED_WHO_DS) #Basic graphic plotting are possible at this stage #Eg ggplot ( data = LED_WHO_DS ) + + geom_bar ( mapping = aes ( x = Lifeexpectancy) ) #etc, just change the geom attributes. #************END OF SCRIPT****************************************************************88