Data Dive week 2

Load the data

data <- read.csv ("C:\\Users\\91630\\OneDrive\\Desktop\\statistics\\age_gaps.CSV")

1st column - numeric summary

summary_C1 <- summary(data$actor_1_age)

print(summary_C1)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   18.00   33.00   39.00   40.64   47.00   81.00

Perspectives

Actor 1 in the sample has a median age of 39 years, according to the summary data for actor_1_age. This indicates that in 50% of the cases, actor 1 was 39 years of age or younger, emphasizing the fact that a significant portion of the sample included performers in major roles who are comparatively middle-aged.

Importance

The dataset appears to depict love partnerships where at least one of the protagonists is in their late thirties, according to the median age, which acts as a central tendency for the distribution of actor ages. This realization could affect how people view the age dynamics portrayed in romantic movies and could also be indicative of preferences or trends in casting choices.

Additional queries

• Which directors and which genres are associated with a higher median age for actor 1?

• What changes have you noticed in actor 1’s median age over the years?

• Is the median age significantly different based on character 1’s gender?

2nd column - numeric summary

summary_C2 <- summary(data$actor_2_age)

print(summary_C2)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   17.00   25.00   29.00   30.21   34.00   68.00

Perspectives

Actor 2’s median age in the dataset is 29, according to the actor_2_age summary statistics. This indicates a preference for younger actors in supporting roles in romantic films, as 50% of the instances have two actors who are 29 years of age or younger.

Importance

Actor 2’s median age is 29, suggesting a rather young age profile for supporting roles. This can be a reflection of a trend in the industry to cast younger actors in supporting roles, or it might be a reflection of the public’s taste for particular age dynamics in romantic film relationships.

Additional queries

• What is the difference between the median age of actors 2 and 1?

• Is the median age of actor 2 higher in any certain genres or directors?

• Does actor 2’s median age change over a period of years or decades?

3rd Column - Categorical summary

unique_values_C3 <- unique(data$character_1_gender)

count_values_C3 <- table(data$character_1_gender)

cat("Categorical Summary for character_1_gender:\n")

## Categorical Summary for character_1_gender:

print(data.frame(Value = unique_values_C3, Count = count_values_C3))

##   Value Count.Var1 Count.Freq
## 1 woman        man        941
## 2   man      woman        214

Perspectives

Character_1_gender’s categorical summary shows that relationships in which the first character is a “woman” (941 instances) predominate in the dataset compared to instances in which the first character is a “man” (214 instances). This suggests that female characters play the main parts in love movies, resulting in a notable gender imbalance.

Importance

The significant difference in the numbers between the counts points to a general pattern in how gender interactions are portrayed in romantic comedies. This can be the result of audience choices, industry norms, or narrative devices that usually center romantic stories around female characters.

Additional queries

• What variations exist in the gender pair distribution between directors or genres?

• Are there any particular eras or decades in history where the gender roles in love movies shift dramatically?

• Are the basic themes or tones of the movie connected to the gender pairings?

Theory

• Is there a statistically significant correlation between the average age difference between the characters in Woody Allen’s films and his directing involvement?

• Is there a pattern to the way that romantic movie pairings consistently pair older male actors with younger female actresses?

• Is there a discernible shift in the typical age difference between romantic comedy characters, and may this shift be connected to distinct eras or decades of movie production?

  Total Function

  The characters in the majority of Woody Allen’s films have an average age difference of 20.15, indicating a substantial age gap.
  

  woody_allen_movies <- subset(data,director == "Woody Allen")
  
  
  average_age_difference_woody_allen <- mean(woody_allen_movies$age_difference)
  
  
  cat("Average Age Difference for Woody Allen's Movies:", round(average_age_difference_woody_allen, 2))

  ## Average Age Difference for Woody Allen's Movies: 20.15

Visual Summaries

library(ggplot2)


ggplot(data, aes(x = age_difference)) +
  geom_histogram(binwidth = 5, fill = "red", color = "black", alpha = 0.7) +
  labs(title = "Histogram of Age Differences in Romantic Movies",
       x = "Age Difference",
       y = "Frequency") +
  theme_minimal()

ggplot(data, aes(x = director, y = age_difference, fill = director)) +
  geom_boxplot() +
  labs(title = "Boxplot of Age Differences by Director",
       x = "Director",
       y = "Age Difference") +
  theme_minimal()

ggplot(data, aes(x = character_1_gender)) +
  geom_bar(fill = "lavender", color = "black") +
  labs(title = "Distribution of Character 1 Gender", x = "Gender", y = "Count")

Visual summaries

Insight

The age difference histogram:

According to the histogram, the majority of age differences in romantic films occur between the ages of 0 and 20, with a peak occurring at 10. This indicates that a lot of movies feature relationships with small age differences.

A boxplot by the filmmaker that shows the disparities in age:

The romantic comedy boxplot demonstrates how various directors handle age disparities in their works. While some directors like to keep their ages more uniform, others have a wider variation. The age difference in Woody Allen’s films, for instance, is rather noticeable.

Character 1’s Distribution of Gender:

The bar graph demonstrates that in love movies, women are more frequently featured as Character 1. This may suggest a recurrent theme or inclination in the way main characters in love relationships are portrayed.

Importance

The relationship between age in romance films:

The histogram shows that in romantic films, directors often select characters with middle-aged differences. This can be a calculated move to build relatable relationships on television and appeal to a wide audience.

The Impact of Direction on Age Inequalities:

The box plot demonstrates how different filmmakers may choose to represent age differences in their works. The wider scope of Woody Allen’s films, for instance, suggests a potential signature in his storytelling style.

Gender Parity in Executive Roles:

A recurring trend in romance movies with a strong female lead is depicted by the character gender distribution bar chart. Gaining insight from this tendency may reveal preferences among audiences or reveal historical cinematic practices.

Additional queries

The Influence of Age Differences on Film Success: Is there a relationship between the variety of age differences in romantic films and the general success or reception of the films? Are audiences more drawn to particular age groups?

Evolution Over Decades: How have age differences in love films evolved over the years? Have trends or preferences changed significantly?

Gender Dynamics in Romantic Relationships: How do gender dynamics manifest themselves in the relationships portrayed in these films, beyond the first character? Do the roles that are assigned to male and female characters in love novels follow any patterns?