Can someone correct my R script for the following errors while keeping it as intact as possible Error in `mutate()`:

! Problem while computing `year = year(date)`.

Caused by error in `as.POSIXlt.default()`:

! do not know how to convert 'x' to class POSIXlt

Run `rlang::last_error()` to see where the error occurred.

Error in group_by(., year) : object 'nottem_tidy_df' not found

Error in ggplot(average_temp_by_year_df, aes(year, avg_temp)) : 

 object 'average_temp_by_year_df' not found

Error in ggplot(class_counts, aes(x = Class, y = prop_survived)) : 

 object 'class_counts' not found

# Title: My Name - RStudio Importing and Visualizing Data

# Check if pacman is installed and install it if not

if (!require("pacman")) install.packages("pacman")

print("Pacman Installed")

# Use pacman to load/install required packages

pacman::p_load(pacman, datasets, tidyverse, tsibble, lubridate)

print("Packages Loaded")

# Load the nottem dataset

data("nottem")

print("Nottem Loaded")

# Store the nottem dataset as a tibble

nottem_df <- as_tibble(nottem)

print("Nottem Stored as Tibble")

# Store the nottem dataset as a tidy df

nottem_tidy_df <- nottem_df %>%

mutate(year = year(date),

month = month(date)) %>%

select(date, year, month, temperature)

print("Nottem Stored as Tidy df")

# Average annual temperature by year df

average_temp_by_year_df <- nottem_tidy_df %>%

group_by(year) %>%

summarize(avg_temp = mean(temperature))

print("Average Annual Temp by Year Stored as df")

# Plot the annual temperature by year

ggplot(average_temp_by_year_df, aes(year, avg_temp)) +

geom_line() +

geom_smooth(method = "loess") +

ggtitle("Annual Temperature by Year") +

xlab("Year") +

ylab("Temperature (C)")+

ggsave("Annual_Temperature_by_Year.png")

print("AAT Plotted")

# Load the Titanic dataset

data("Titanic")

print("Titanic Loaded")

# Store the Titanic dataset as a tibble

titanic_tibble_df <- as_tibble(Titanic)

print("Titanic Dataset Sored as Tibble")

# Uncount the tibble Titanic dataset and make each of the 4 variables a factor

titanic_factors_df <- titanic_tibble_df %>%

mutate_at(c("Class", "Age", "Sex", "Survived"), as.factor)

print("Tibble Uncounted")

# Compute the proportion of people that survived

num_survived <- sum(titanic_factors_df$Survived == "Yes")

num_total <- nrow(titanic_factors_df)

prop_survived <- num_survived/num_total

print("Surviver Ratio Computed")

# Count the number of passengers in each class

class_count_df <- titanic_factors_df %>%

group_by(Class) %>%

summarize(count = n())

print("Passengers Counted by Class")

# Count the number of passengers who survived in each class

class_survived_df <- titanic_factors_df %>%

filter(Survived == "Yes") %>%

group_by(Class) %>%

summarize(survived_count = n())

print("Class Survivers Counted")

# Append the class totals to the survival totals df

class_totals_df <- class_count_df %>%

left_join(class_survived_df, by = "Class")

print("Df Appended")

# Compute the proportion of those that survived by class

class_totals_df$prop_survived <- class_totals_df$survived_count/class_totals_df$count

print("Class Surviver Ratio Computed")

# Plot the proportion of those that survived by class

ggplot(class_counts, aes(x = Class, y = prop_survived)) +

geom_bar(stat = "identity") +

scale_y_continuous(limits = c(0, 1), labels = scales::percent_format()) +

labs(x = "Class", y = "Proportion of Passengers Survived",

title = "Proportion of Passengers Survived by Class") +

ggsave("proportion_survived_by_class.png")

print("Class Survivers Plotted")