vidooly

Harendra Kumar

May 7, 2018

Languages drawing greatest viewership

languge_viewership <- readxl::read_xlsx("Analysis assignment sheet.xlsx" , sheet = 8)
p1 <- ggplot(data =languge_viewership , aes(x= Language, y = Views )) + geom_bar(stat = 'identity')
p2 <- ggplot(data = languge_viewership , aes(x = Language , y = Engagement )) + geom_bar(stat = 'identity')
grid.arrange(p1, p2)

fig.1

Explanation : As from the fig.1 , We can infer that Hindi videos has highest viewership as well as engagement followed by english. As hindi and english is widey spoken and understood draws major portion .

Genres drawing greatest viewership

genre_viewership <- readxl::read_xlsx("Analysis assignment sheet.xlsx" , sheet = 9)
p3 <- ggplot(data =genre_viewership  , aes(x= Genres , y = Views )) + geom_bar(stat = 'identity')
p4 <- ggplot(data = genre_viewership  , aes(x = Genres , y = Engagement )) + geom_bar(stat = 'identity')
grid.arrange(p3, p4)

fig.2

Explanation : As from the fig.2 , We can infer that people mostly watched videos depending on their interest, which draws major portion. After Interest , Comedy is second most genre as people in free time will mostly like to seen and listen comedy as it is relaxing.

Sub-Genres drawing greatest viewership

interest <- readxl::read_xlsx("Analysis assignment sheet.xlsx" , sheet = 7)
p5 <- ggplot(data =interest , aes(x= Subgenere , y = Views )) + geom_bar(stat = 'identity')
p6 <- ggplot(data = interest , aes(x = Subgenere , y = Engagement )) + geom_bar(stat = 'identity')
grid.arrange(p5,p6)

fig.3

Explanation : As from the fig.3 , We can infer that music has highest viewership as well as enagagments followed by fashion & beauty , food & cooking and health & wellness. Reason could be that as in today’s time pressure of work, family etc is increasing, music play vital role in releasing it as well food & cooking and health & wellness is also people are now a days most aware of.

Comedy

comedy <- readxl::read_xlsx("Analysis assignment sheet.xlsx" , sheet = 6)
p7 <- ggplot(data =comedy , aes(x= Subgenere , y = Views )) + geom_bar(stat = 'identity')
p8 <- ggplot(data = comedy , aes(x = Subgenere , y = Engagement )) + geom_bar(stat = 'identity')
grid.arrange(p7,p8)

fig.4

Explanation : As from the fig.4 , We can infer that comedy has always been in the mainstream. But in today’s time Dark and mature comedy has also become one of the trends in main stream bollywood. Stand-ups comedy is one of popular show that as it’s now become great platform like great indian laughter challenge.

Drama

drama <- readxl::read_xlsx("Analysis assignment sheet.xlsx" , sheet = 5)
p9 <- ggplot(data =drama , aes(x= Subgenere , y = Views )) + geom_bar(stat = 'identity')
p10 <- ggplot(data = drama , aes(x = Subgenere , y = Engagement )) + geom_bar(stat = 'identity')
grid.arrange(p9 ,p10)

fig.5

Explanation : As from the fig.5 , We can infer that superheroes movies like film as drawan major views as well as enagagments as it is liked from young to medium aged group peoples followed by Action/adventure movies like rambo, which was superhit across the globe. Sci-fi movies is also liked my many people some of movies like star wars , which was blockbuster.

Reality

reality <- readxl::read_xlsx("Analysis assignment sheet.xlsx" , sheet = 4)

p11 <- ggplot(data =reality , aes(x= Subgenere , y = Views )) + geom_bar(stat = 'identity')

p12 <- ggplot(data = reality , aes(x = Subgenere , y = Engagement )) + geom_bar(stat = 'identity')
grid.arrange(p11,p12)

fig.6

Explanation : As from the fig.6 , We can infer that today’s society is majorly influence by social media experiements which draws engegments as well as views. Reality events like dance india dance has become famous as it gives platform to people to show their skills an it is liked by the any age group people especially the young age group. But Science and technology has always been a great content , which is liked by every age groups as it teaches alot and is able to get maximum engagements.

Events

events <- readxl::read_xlsx("Analysis assignment sheet.xlsx" , sheet = 3)

p13 <- ggplot(data =events , aes(x= Subgenere , y = Views )) + geom_bar(stat = 'identity')

p14 <- ggplot(data = events , aes(x = Subgenere , y = Engagement )) + geom_bar(stat = 'identity')

grid.arrange(p13,p14)

fig.7

Explanation : As from the fig.7 , We can infer that sports, which is undisputed liked by everyone has both highest views as well as engagements. Awards and ceremonies also has considerable views and engagements , which reasons could be people like watching their sports awards ceremonies as well.

Content formats that dominate by genre

content_format_genre <- readxl::read_xlsx("Analysis assignment sheet.xlsx" , sheet = 2)

p15 <- ggplot(data =content_format_genre , aes(x= Subgenere , y = Short )) + geom_bar(stat = 'identity')

p16 <- ggplot(data = content_format_genre , aes(x = Subgenere , y = Series )) + geom_bar(stat = 'identity')

p17 <- ggplot(data = content_format_genre , aes(x = Subgenere , y = Episodes )) + geom_bar(stat = 'identity')

grid.arrange(p15,p16,p17)

fig.8

Explanation : As from the fig.8 , We can infer that genre is a personal choice of every individual. Therefore , in Short genre, people mostly like to watch events or something of their interests. In Series , people mostly like to watch Comedy and drama. In Episodes , Reality is leader , which is mostly recorded as people like watch based on someone or events like True Detective series’s episodes.