帮我写一份R语言的电影受欢迎分析

好的，以下是一份简单的 R 语言电影受欢迎分析的代码：

# 加载必要的包
library(tidyverse)
library(ggplot2)
library(scales)

# 读取数据
movies <- read_csv("movies.csv")

# 数据清洗
movies_clean <- movies %>% 
  # 删除无用列
  select(-c("budget", "homepage", "id", "keywords", "original_language", 
            "original_title", "overview", "spoken_languages", "status", 
            "tagline", "title", "production_companies", "production_countries", 
            "release_date", "revenue", "runtime", "vote_count")) %>% 
  # 删除缺失值
  drop_na()

# 对电影评分进行分析
movies_clean %>%
  # 根据评分进行排序
  arrange(desc(vote_average)) %>% 
  # 选取前10个电影
  slice(1:10) %>% 
  # 画图
  ggplot(aes(x = reorder(title, vote_average), y = vote_average)) + 
  geom_bar(stat = "identity", fill = "steelblue") +
  coord_flip() +
  labs(title = "Top 10 Movies by Rating", x = "Movie Title", y = "Rating") +
  theme(plot.title = element_text(hjust = 0.5)) +
  scale_y_continuous(limits = c(7, 9), expand = c(0, 0)) +
  theme(axis.text = element_text(size = 10), axis.title = element_text(size = 12))

# 对电影流行度进行分析
movies_clean %>%
  # 根据流行度进行排序
  arrange(desc(popularity)) %>% 
  # 选取前10个电影
  slice(1:10) %>% 
  # 画图
  ggplot(aes(x = reorder(title, popularity), y = popularity)) + 
  geom_bar(stat = "identity", fill = "steelblue") +
  coord_flip() +
  labs(title = "Top 10 Movies by Popularity", x = "Movie Title", y = "Popularity") +
  theme(plot.title = element_text(hjust = 0.5)) +
  scale_y_continuous(expand = c(0, 0), labels = comma) +
  theme(axis.text = element_text(size = 10), axis.title = element_text(size = 12))

# 对电影类型进行分析
movies_clean %>%
  # 将电影类型拆分成多行
  separate_rows(genres, sep = "\\|") %>% 
  # 统计每种类型的电影数目
  group_by(genres) %>% 
  summarise(count = n()) %>% 
  # 根据电影数目进行排序
  arrange(desc(count)) %>% 
  # 画图
  ggplot(aes(x = reorder(genres, count), y = count)) + 
  geom_bar(stat = "identity", fill = "steelblue") +
  coord_flip() +
  labs(title = "Number of Movies by Genre", x = "Genre", y = "Number of Movies") +
  theme(plot.title = element_text(hjust = 0.5)) +
  scale_y_continuous(expand = c(0, 0), labels = comma) +
  theme(axis.text = element_text(size = 10), axis.title = element_text(size = 12))

这份代码首先加载了必要的包，然后读取了一个名为 `movies.csv` 的电影数据集。接着对数据进行了清洗，删除了无用列和缺失值。然后对电影评分、流行度和类型进行了分析，并画出对应的图表。最终可以得到一份电影受欢迎程度的分析报告。