Data Visualization

Task 1

First, we load the data

Task 2.1

First let’s load the data

download.file("https://raw.githubusercontent.com/kflisikowski/ds/master/netflix-dataset.csv?raw=true", destfile ="dane.csv",mode="wb")
mydata<-read.csv(file="dane.csv",encoding ="UTF-8",header=TRUE,sep = ",")
attach(mydata)

We will consider a movie or series to be polish if it is available in Poland and has Polish subtitles. Now some data wrangling.

movies <- mydata %>% 
  filter(Languages == "Polish") %>%
  filter (Country.Availability == "Poland") %>%
  select( Country.Availability,Languages, Title, IMDb.Score )

ggplot(mydata, aes(IMDb.Score))+
  geom_histogram(binwidth=0.1, fill = "cornsilk", color="navyblue")+
  facet_wrap(vars(Series.or.Movie))

Task 2.2

Now let’s take a look at density.

ggplot(mydata, aes(IMDb.Score), y=after_stat(density), bw=0.5)+
  geom_density( fill = "cornsilk", color="navyblue")+
  facet_wrap(vars(Series.or.Movie))

Task 3.3

new <- mydata %>%
  select(Languages) %>%
  separate_rows(Languages, sep=", ") %>%
  count(Languages, sort=TRUE) %>%
  top_n(10, n)


ggplot(new, aes(x=n, y=fct_reorder(Languages, n)))+
  geom_col()+
  ylab("Language")+
  xlab("How many titles available")