TMDB Data Analysis
Introduction
This document provides a detailed analysis of the TMDB dataset. The analysis includes data processing, visualizations, correlation calculations, and confidence interval calculations.
Data Loading and Processing
# Load necessary libraries
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.2 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(ggthemes)
library(ggplot2)
library(gapminder)
library(dplyr)# Read the dataset
tmdb <- read.csv("TMDB.csv")
head(tmdb)## Names Orig_title Orig_lang
## 1 Creed III Creed III English
## 2 Avatar: The Way of Water Avatar: The Way of Water English
## 3 The Super Mario Bros. Movie The Super Mario Bros. Movie English
## 4 Mummies Momias Spanish, Castilian
## 5 Supercell Supercell English
## 6 Cocaine Bear Cocaine Bear English
## Genre Release_Date Score Budget
## 1 Drama, Action 02-03-2023 73 75.0
## 2 Science Fiction, Adventure, Action 15-12-2022 78 460.0
## 3 Animation, Adventure, Family, Fantasy, Comedy 05-04-2023 76 100.0
## 4 Animation, Comedy, Family, Adventure, Fantasy 05-01-2023 70 12.3
## 5 Action 17-03-2023 61 77.0
## 6 Thriller, Comedy, Crime 23-02-2023 66 35.0
## Revenue Status Country
## 1 271.6167 Released AU
## 2 2316.7949 Released AU
## 3 724.4590 Released AU
## 4 34.2000 Released AU
## 5 340.9420 Released US
## 6 80.0000 Released AU
## Crew
## 1 Michael B. Jordan, Adonis Creed, Tessa Thompson, Bianca Taylor, Jonathan Majors, Damien Anderson, Wood Harris, Tony 'Little Duke' Evers, Phylicia Rashād, Mary Anne Creed, Mila Davis-Kent, Amara Creed, Florian Munteanu, Viktor Drago, José Benavidez Jr., Felix Chavez, Selenis Leyva, Laura Chavez
## 2 Sam Worthington, Jake Sully, Zoe Saldaña, Neytiri, Sigourney Weaver, Kiri / Dr. Grace Augustine, Stephen Lang, Colonel Miles Quaritch, Kate Winslet, Ronal, Cliff Curtis, Tonowari, Joel David Moore, Norm Spellman, CCH Pounder, Mo'at, Edie Falco, General Frances Ardmore
## 3 Chris Pratt, Mario (voice), Anya Taylor-Joy, Princess Peach (voice), Charlie Day, Luigi (voice), Jack Black, Bowser (voice), Keegan-Michael Key, Toad (voice), Seth Rogen, Donkey Kong (voice), Fred Armisen, Cranky Kong (voice), Kevin Michael Richardson, Kamek (voice), Sebastian Maniscalco, Spike (voice)
## 4 Óscar Barberán, Thut (voice), Ana Esther Alborg, Nefer (voice), Luis Pérez Reina, Carnaby (voice), María Luisa Solá, Madre (voice), Jaume Solà, Sekhem (voice), José Luis Mediavilla, Ed (voice), José Javier Serrano Rodríguez, Danny (voice), Aleix Estadella, Dennis (voice), María Moscardó, Usi (voice)
## 5 Skeet Ulrich, Roy Cameron, Anne Heche, Dr Quinn Brody, Daniel Diemer, William Brody, Jordan Kristine Seamón, Harper Hunter, Alec Baldwin, Zane Rogers, Richard Gunn, Bill Brody, Praya Lundberg, Amy, Johnny Wactor, Martin, Anjul Nigam, Ramesh
## 6 Keri Russell, Sari, Alden Ehrenreich, Eddie, O'Shea Jackson Jr., Daveed, Ray Liotta, Syd, Kristofer Hivju, Olaf (Kristoffer), Margo Martindale, Ranger Liz, Christian Convery, Henry, Isiah Whitlock Jr., Bob, Jesse Tyler Ferguson, Peter
## Overview
## 1 After dominating the boxing world, Adonis Creed has been thriving in both his career and family life. When a childhood friend and former boxing prodigy, Damien Anderson, resurfaces after serving a long sentence in prison, he is eager to prove that he deserves his shot in the ring. The face-off between former friends is more than just a fight. To settle the score, Adonis must put his future on the line to battle Damien — a fighter who has nothing to lose.
## 2 Set more than a decade after the events of the first film, learn the story of the Sully family (Jake, Neytiri, and their kids), the trouble that follows them, the lengths they go to keep each other safe, the battles they fight to stay alive, and the tragedies they endure.
## 3 While working underground to fix a water main, Brooklyn plumbers—and brothers—Mario and Luigi are transported down a mysterious pipe and wander into a magical new world. But when the brothers are separated, Mario embarks on an epic quest to find Luigi.
## 4 Through a series of unfortunate events, three mummies end up in present-day London and embark on a wacky and hilarious journey in search of an old ring belonging to the Royal Family, stolen by ambitious archaeologist Lord Carnaby.
## 5 Good-hearted teenager William always lived in hope of following in his late father’s footsteps and becoming a storm chaser. His father’s legacy has now been turned into a storm-chasing tourist business, managed by the greedy and reckless Zane Rogers, who is now using William as the main attraction to lead a group of unsuspecting adventurers deep into the eye of the most dangerous supercell ever seen.
## 6 Inspired by a true story, an oddball group of cops, criminals, tourists and teens converge in a Georgia forest where a 500-pound black bear goes on a murderous rampage after unintentionally ingesting cocaine.# Create new variables
tmdb$Profit <- tmdb$Revenue - tmdb$Budget
tmdb$ROI <- (tmdb$Profit / tmdb$Budget) * 100
tmdb$ProfitMargin <- (tmdb$Profit / tmdb$Revenue) * 100Visualizations
Histograms
hist_vars <- c("Score")
for(var in hist_vars) {
print(ggplot(tmdb, aes_string(var)) +
geom_histogram(binwidth = 10, fill = "blue", color = "black", alpha = 0.7) +
ggtitle(paste("Histogram of", var)))
}## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation idioms with `aes()`.
## ℹ See also `vignette("ggplot2-in-packages")` for more information.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
hist_vars <- c("Revenue")
for(var in hist_vars) {
print(ggplot(tmdb, aes_string(var)) +
geom_histogram(binwidth = 10, fill = "blue", color = "black", alpha = 0.7) +
ggtitle(paste("Histogram of", var)))
}
hist_vars <- c("Budget")
for(var in hist_vars) {
print(ggplot(tmdb, aes_string(var)) +
geom_histogram(binwidth = 10, fill = "blue", color = "black", alpha = 0.7) +
ggtitle(paste("Histogram of", var)))
}
hist_vars <- c("Profit")
for(var in hist_vars) {
print(ggplot(tmdb, aes_string(var)) +
geom_histogram(binwidth = 10, fill = "blue", color = "black", alpha = 0.7) +
ggtitle(paste("Histogram of", var)))
}
Boxplots
box_vars <- c("Score")
for(var in box_vars) {
print(ggplot(tmdb, aes_string(x = "1", y = var)) +
geom_boxplot() +
ggtitle(paste("Boxplot of", var)))
}
box_vars <- c("Revenue")
for(var in box_vars) {
print(ggplot(tmdb, aes_string(x = "1", y = var)) +
geom_boxplot() +
ggtitle(paste("Boxplot of", var)))
}
box_vars <- c("Budget")
for(var in box_vars) {
print(ggplot(tmdb, aes_string(x = "1", y = var)) +
geom_boxplot() +
ggtitle(paste("Boxplot of", var)))
}
Scatter Plots with Regression Lines
# Score vs. Budget and Profit
print(ggplot(tmdb, aes(x = Budget, y = Score)) +
geom_point() +
geom_smooth(method = lm, col = "red") +
ggtitle("Score vs. Budget with Regression Line"))## `geom_smooth()` using formula = 'y ~ x'
print(ggplot(tmdb, aes(x = Profit, y = Score)) +
geom_point() +
geom_smooth(method = lm, col = "red") +
ggtitle("Score vs. Profit with Regression Line"))## `geom_smooth()` using formula = 'y ~ x'
# Revenue vs. Budget and ROI
print(ggplot(tmdb, aes(x = Budget, y = Revenue)) +
geom_point() +
geom_smooth(method = lm, col = "red") +
ggtitle("Revenue vs. Budget with Regression Line"))## `geom_smooth()` using formula = 'y ~ x'
print(ggplot(tmdb, aes(x = ROI, y = Revenue)) +
geom_point() +
geom_smooth(method = lm, col = "red") +
ggtitle("Revenue vs. ROI with Regression Line"))## `geom_smooth()` using formula = 'y ~ x'
# Score vs. Revenue and ProfitMargin
print(ggplot(tmdb, aes(x = Revenue, y = Score)) +
geom_point() +
geom_smooth(method = lm, col = "red") +
ggtitle("Score vs. Revenue with Regression Line"))## `geom_smooth()` using formula = 'y ~ x'
print(ggplot(tmdb, aes(x = ProfitMargin, y = Score)) +
geom_point() +
geom_smooth(method = lm, col = "red") +
ggtitle("Score vs. ProfitMargin with Regression Line"))## `geom_smooth()` using formula = 'y ~ x'## Warning: Removed 73 rows containing non-finite values (`stat_smooth()`).
Correlation Coefficients
cor_set1_budget <- cor(tmdb$Budget, tmdb$Score)
cor_set1_profit <- cor(tmdb$Profit, tmdb$Score)
cor_set2_budget <- cor(tmdb$Budget, tmdb$Revenue)
cor_set2_ROI <- cor(tmdb$ROI, tmdb$Revenue)
cor_set3_revenue <- cor(tmdb$Revenue, tmdb$Score)
cor_set3_profitMargin <- cor(tmdb$ProfitMargin, tmdb$Score)
correlations <- data.frame(
Set = c("Set 1 (Budget)", "Set 1 (Profit)", "Set 2 (Budget)", "Set 2 (ROI)", "Set 3 (Revenue)", "Set 3 (ProfitMargin)"),
Correlation = c(cor_set1_budget, cor_set1_profit, cor_set2_budget, cor_set2_ROI, cor_set3_revenue, cor_set3_profitMargin)
)
correlations## Set Correlation
## 1 Set 1 (Budget) -0.2354700991
## 2 Set 1 (Profit) 0.1656486921
## 3 Set 2 (Budget) 0.6738295692
## 4 Set 2 (ROI) -0.0009230343
## 5 Set 3 (Revenue) 0.0965328705
## 6 Set 3 (ProfitMargin) NaNConfidence Intervals
conf_int_score <- t.test(tmdb$Score)$conf.int
conf_int_revenue <- t.test(tmdb$Revenue)$conf.int
confidence_intervals <- data.frame(
Variable = c("Score", "Revenue"),
Lower_Bound = c(conf_int_score[1], conf_int_revenue[1]),
Upper_Bound = c(conf_int_score[2], conf_int_revenue[2])
)
confidence_intervals## Variable Lower_Bound Upper_Bound
## 1 Score 63.23403 63.76007
## 2 Revenue 247.74272 258.53746Conclusion
Based on the visualizations, correlations, and confidence intervals, we can derive insights about the relationships between the variables in the TMDB dataset. Further statistical tests and modeling can provide deeper insights and predictions based on this data.