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gdp <- read.csv('D:\\gdp\\cinema.csv')Data include movies information(score,genre,overview,crew,orig_title,status,orig_lang,budget_x,revenue,cost), Information of attributes names - name of the movie date_x - year-month-day score - score obtained for the movie on scale of 100 genre - type of the genre of the movie overview -overview of the movie in short crew - names of crew involved in the movie orig_title - original title of the movie status - status of the movie weather released or not yet released orig_lang -original language in which movie got released budget_x -total budget of the movie revenue country - total revenue generated to the country country -country in which the movie was released
The IMDB dataset contains information about movies, including their names user ratings, genres, overviews, cast and crew members, original titles, production status, original languages, budgets, revenues, and countries of origin. This data can be used for various analyses, such as identifying trends in movie genres, exploring the relationship between budget and revenue, and predicting the success of future movies.
class(gdp)## [1] "data.frame"str(gdp)## 'data.frame': 10178 obs. of 12 variables:
## $ names : chr "Creed III" "Avatar: The Way of Water" "The Super Mario Bros. Movie" "Mummies" ...
## $ date_x : chr "03-02-2023" "12/15/2022 " "04-05-2023" "01-05-2023" ...
## $ score : int 73 78 76 70 61 66 80 83 59 58 ...
## $ genre : chr "Drama, Action" "Science Fiction, Adventure, Action" "Animation, Adventure, Family, Fantasy, Comedy" "Animation, Comedy, Family, Adventure, Fantasy" ...
## $ overview : chr "After dominating the boxing world, Adonis Creed has been thriving in both his career and family life. When a ch"| __truncated__ "Set more than a decade after the events of the first film, learn the story of the Sully family (Jake, Neytiri, "| __truncated__ "While working underground to fix a water main, Brooklyn plumbers—and brothers—Mario and Luigi are transported d"| __truncated__ "Through a series of unfortunate events, three mummies end up in present-day London and embark on a wacky and hi"| __truncated__ ...
## $ crew : chr "Michael B. Jordan, Adonis Creed, Tessa Thompson, Bianca Taylor, Jonathan Majors, Damien Anderson, Wood Harris, "| __truncated__ "Sam Worthington, Jake Sully, Zoe Saldaña, Neytiri, Sigourney Weaver, Kiri / Dr. Grace Augustine, Stephen Lang, "| __truncated__ "Chris Pratt, Mario (voice), Anya Taylor-Joy, Princess Peach (voice), Charlie Day, Luigi (voice), Jack Black, Bo"| __truncated__ "Óscar Barberán, Thut (voice), Ana Esther Alborg, Nefer (voice), Luis Pérez Reina, Carnaby (voice), María Luisa "| __truncated__ ...
## $ orig_title: chr "Creed III" "Avatar: The Way of Water" "The Super Mario Bros. Movie" " Momias" ...
## $ status : chr " Released" " Released" " Released" " Released" ...
## $ orig_lang : chr " English" " English" " English" " Spanish, Castilian" ...
## $ budget_x : num 7.50e+07 4.60e+08 1.00e+08 1.23e+07 7.70e+07 ...
## $ revenue : num 2.72e+08 2.32e+09 7.24e+08 3.42e+07 3.41e+08 ...
## $ country : chr "AU" "AU" "AU" "AU" ...summary(gdp)## names date_x score genre
## Length:10178 Length:10178 Min. : 0.0 Length:10178
## Class :character Class :character 1st Qu.: 59.0 Class :character
## Mode :character Mode :character Median : 65.0 Mode :character
## Mean : 63.5
## 3rd Qu.: 71.0
## Max. :100.0
## overview crew orig_title status
## Length:10178 Length:10178 Length:10178 Length:10178
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## orig_lang budget_x revenue country
## Length:10178 Min. : 1 Min. :0.000e+00 Length:10178
## Class :character 1st Qu.: 15000000 1st Qu.:2.859e+07 Class :character
## Mode :character Median : 50000000 Median :1.529e+08 Mode :character
## Mean : 64882379 Mean :2.531e+08
## 3rd Qu.:105000000 3rd Qu.:4.178e+08
## Max. :460000000 Max. :2.924e+09standard_deviation <- sd(gdp$budget_x, na.rm= TRUE)
variation <- var(gdp$score, na.rm= TRUE)
summ <- sum(gdp$revenue)
print(standard_deviation)## [1] 57075645print(variation)## [1] 183.2507print(summ)## [1] 2.57646e+12plot(gdp\(budget_x, gdp\)score, main=“Scatter Plot of X vs Y”, xlab=“budget_x”, ylab=“score”)
hist(gdp$budget_x, main=“Histogram of Values”, xlab=“budget_x”)
boxplot(gdp$budget_x, main=“Box Plot of Values”)
pie(table(gdp$budget_x), main=“Pie Chart of Category”)
result <- aggregate(gdp\(budget_x,by=list(gdp\)budget_x), mean) result barplot(result\(x, names.arg=result\)Group.1, xlab=“budget_x”, ylab=“score”, col=rainbow(6), main=“budget_x vs score”,border=“black”)