R Notebook

Question 5: Initially check if scraping a specific directory is allowed

paths_allowed("https://www.imdb.com/title/tt7235466/fullcredits?ref_=tt_cl_sm")

 www.imdb.com                      

[1] TRUE

Question 6: How many rows and columns do you get from the table?

Question 7: Step 1. Preserve only the 2nd and the 4th variables in your obtained tibble. Use subset() function to preserve only the non-blank rows; Step 2. Preserve only the non-blankrows. Use subset() function to preserve only the non-blank rows; Step 3. Check the tail of the data frame, further remove rows with blanks. There may be some empty rows at the end of the table. We will not count them as the informative observations. After the above data cleaning, how many observations and columns are left in your cast table?

library(rvest)
url <- "https://www.imdb.com/title/tt7235466/fullcredits?ref_=tt_cl_sm"
webpage <- read_html(url)
series_cast_table <- webpage %>% html_element(xpath = "(//table)[3]") %>% html_table()
cleaned_cast_table <- series_cast_table[, c(2, 4)]
cleaned_cast_table <- cleaned_cast_table[seq(2, nrow(cleaned_cast_table), 2), ]
cleaned_cast_table <- cleaned_cast_table[!(cleaned_cast_table[, 1] == "" | cleaned_cast_table[, 2] == ""), ]
dim(cleaned_cast_table)

[1] 1351    2

Question 8: Which of the following option(s) can help you rename the variables of a tibble (or a data frame)?

library(rvest)
url <- "https://www.imdb.com/title/tt7235466/fullcredits?ref_=tt_cl_sm"
webpage <- read_html(url)
visual_effects_table <- webpage %>% html_elements("table")  # Get all tables
length(visual_effects_table)

[1] 30

Question 9: How many staff worked for the Series Visual Effects?

series_visual_effects <- visual_effects_table[[20]] %>% html_table()
staff_names <- series_visual_effects[[1]] 
staff_count <- sum(!is.na(staff_names) & staff_names != "")
print(staff_count)

[1] 362