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Code/Ageofretirment.R

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+library(usmap)
+library(ggplot2)
+library(extrafont)
+
+# Create a data frame with state names and average retirement age
+retirement_data <- data.frame(
+  state = c("District of Columbia", "Hawaii", "Massachusetts", "South Dakota", "Maryland", "Connecticut", "New Jersey", "Vermont", "Rhode Island", "New Hampshire",
+            "Colorado", "Virginia", "North Dakota", "Minnesota", "Utah", "Nebraska", "Iowa", "Texas", "Kansas", "California",
+            "New York", "Washington", "Pennsylvania", "Wisconsin", "Florida", "Montana", "Illinois", "Idaho", "Wyoming", "Tennessee",
+            "Oregon", "Maine", "Nevada", "Delaware", "Arizona", "North Carolina", "South Carolina", "Ohio", "Indiana", "Missouri", "Georgia", "Mississippi",
+            "Louisiana", "New Mexico", "Michigan", "Kentucky", "Alabama", "Oklahoma", "Arkansas", "Alaska", "West Virginia"),
+  values = c(67, 66, 66, 66, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 64, 64, 64, 64, 64, 64, 64, 64, 64, 64, 63,
+                             63, 63, 63, 63, 63, 63, 63, 63, 63, 63, 63, 62, 62, 62, 62, 62, 62, 62, 61, 61)
+)
+
+# Your existing code for creating the plot
+Retirement_plot <- plot_usmap(data = retirement_data, color = "#0061ff") +
+  scale_fill_continuous(
+    low = "#60efff", high = "#0061ff", name = "", label = scales::comma
+  ) + theme(legend.position = "right",
+            legend.text = element_text(size = 16)) +
+  labs(title = "Average Retirement Age in Every State")
+
+# Change the title font
+Retirement_plot + theme(
+  plot.title = element_text(family = "Lucida Sans Unicode", size = 16, face = "bold", hjust = 0.5, vjust = - 10)
+) + 
+  annotate(geom = "text", x = 0.5, y = -0.5, label = "Mean: 63.86 and Median: 64", size = 5, hjust = -0.4, vjust = 30)
+
+ggsave("Retirement_plot.jpg",width = 3840, height = 2160, units = c("px"))
+
+# Mean and median of the plot:
+Median <- median(retirement_data$values)
+Median
+Mean <- mean(retirement_data$values)
+Mean
+
+

Code/Employment_Rate.R

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+# Load the ggplot2 library
+library(ggplot2)
+library(extrafont)
+# Create a data frame from the provided data
+data <- data.frame(
+  Country = c("Netherlands", "Iceland", "Australia", "New Zealand", "Switzerland", "Norway", "Canada", "Denmark",
+              "United Kingdom", "Austria", "Germany", "United States", "Ireland", "G7", "Japan", "Finland",
+              "Sweden", "Israel", "OECD - Total", "Mexico", "Colombia", "Estonia", "Türkiye", "Euro area",
+              "France", "European Union", "Slovenia", "Luxembourg", "Latvia", "Costa Rica", "Portugal",
+              "Lithuania", "Poland", "Korea", "Belgium", "Hungary", "Czech Republic", "Russia", "Spain", "Chile",
+              "Slovak Republic", "Italy", "Greece", "South Africa"),
+  Employment_Rate = c(77.05, 69.35, 65.18, 62.81, 61.39, 59.04, 57.80, 56.27, 54.38, 53.83, 51.35, 51.28, 48.84, 48.23, 47.85, 47.02, 46.37,
+                      43.84, 43.75, 41.95, 37.45, 37.45, 36.97, 36.51, 35.41, 35.39, 33.08, 30.45, 30.23, 30.02, 29.23,
+                      29.10, 28.18, 27.76, 26.90, 26.50, 25.63, 25.16, 23.78, 23.65, 21.82, 20.30, 18.25, 10.45)
+)
+
+# Highlight "Netherlands" and "Iceland" with different colors
+highlighted_countries <- c("Spain", "United States")
+data$Highlight <- ifelse(data$Country %in% highlighted_countries, "Highlighted", "Other")
+
+# Create a ggplot
+plot <- ggplot(data, aes(x = reorder(Country, Employment_Rate), y = Employment_Rate, fill = Highlight)) +
+  geom_bar(stat = "identity") +
+  labs(x = "Country", y = "Employment Rate") +
+  ggtitle("Employment Rate by Country (15-24 years-olds)") +
+  scale_fill_manual(values = c("Highlighted" = c("#d62828"), "Other" = "#003049"))
+
+# Rotate the x-axis labels for better readability
+plot + theme_minimal() +
+  theme(
+    text = element_text(family = "Lucida Sans Unicode", size = 12),
+    legend.position = "none",
+        axis.text.x = element_text(angle = 45, hjust = 1, size = 12),
+        axis.title.x = element_text(size = 14),  
+        axis.title.y = element_text(size = 14),  
+        plot.title = element_text(size = 16, hjust = 0.5))  
+
+ggsave("EmplymentRate.jpg",width = 3840, height = 2160, units = c("px"))
+
+spain_employment_rate <- data[data$Country == "Spain", "Employment_Rate"]
+print(spain_employment_rate)
+
+usa_employment_rate <- data[data$Country == "United States", "Employment_Rate"]
+print(usa_employment_rate)

Code/FacetPlot.R

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+library(dplyr)
+library(ggplot2)
+library(reshape2)
+library(extrafont)
+
+# Importing time_spent and cleaning the data (transforming to hours)
+time_spent
+time_spent_edited <- time_spent[,-c(1,2)]
+colnames(time_spent_edited) <- c("Age","Alone","Friends","Children","Family","Partner","Coworkers")
+time_spent_edited <- time_spent_edited %>%
+  mutate(time_spent_edited[,c(2:7)]/60)
+time_spent_edited <- time_spent_edited %>%
+  mutate(round(time_spent_edited[,c(2:7)],2))
+rownames(time_spent_edited) <- time_spent_edited$Age
+View(time_spent_edited)
+
+# Melting data to form the necessary column names and numbers
+time_spent_long <- melt(time_spent_edited, id.vars = "Age", variable.name = "Activity", value.name = "Hours")
+
+# Define custom colors for each activity (total of 6 colors)
+custom_colors <- c("#e03c31", "#f7ea48","#2dc84d", "#90e0ef", "#147bd1", "#FF00FF")
+
+# Create a faceted plot with custom line colors and modified titles
+facet_plot <- ggplot(time_spent_long, aes(x = Age, y = Hours, color = Activity)) +
+  geom_line(size = 1.75) +
+  labs(x = "Age", y = "Hours Spent") +
+  scale_x_continuous(limits = c(15, max(time_spent_long$Age))) +
+  facet_wrap(~Activity, ncol = 3) +  # Display facets in 3 columns
+  scale_color_manual(values = custom_colors) +  # Assign custom colors to each facet
+  theme_minimal() +
+  theme(
+    text = element_text(family = "Lucida Sans Unicode", size = 12),
+    axis.title = element_text(size = 15),
+    panel.background = element_rect(fill = "white"),
+    panel.grid.major = element_line(color = "gray"),
+    strip.text = element_text(size = 17, color = "black"),
+    strip.background = element_rect(size=0.8, linetype='solid'),
+    legend.position = "none"  # Remove the legend
+  )
+ggsave("Facet_plot.jpg",width = 3840, height = 2160, units = c("px"))
+# Print the faceted plot
+print(facet_plot)
+
+#Creating a line graph with each representation of time spend based on age
+ggplot(time_spent_long, aes(x = Age, y = Hours, color = Activity)) +
+  geom_line(size = 1.2) +
+  scale_color_manual(values = custom_colors) +
+  labs(x = "Age", y = "Hours Spent") +
+  scale_x_continuous(limits = c(15, max(time_spent_edited$Age))) +
+  theme_minimal() +
+  theme(
+    text = element_text(family = "Lucida Sans Unicode", size = 12),
+    axis.title = element_text(size = 12),
+    plot.background = element_rect(fill = "white"),
+    plot.title = element_text(size = 16, face = "bold", hjust = 0.5)  # Center the title horizontally
+  ) +
+  ggtitle("Time Spent during life")
+ggsave("Time_spent.jpg",width = 3840, height = 2160, units = c("px"))

Code/SeparatedGrphicsProject.R

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+library(dplyr)
+library(ggplot2)
+library(reshape2)
+library(extrafont)
+
+#Graphing line plots of each variable in their own graph
+ggplot(time_spent_long, aes(x = Age, y = Minutes, color = Activity)) +
+  geom_line() +
+  labs(x = "Age", y = "Minutes Spent") +
+  scale_x_continuous(limits = c(15, max(time_spent_long$Age))) +
+  facet_wrap(~Activity)
+
+#Filtering for Alone. Making a table and a graph
+Alone_Table <- time_spent_edited %>%
+  summarize(Age,Alone)
+Alone_Table
+ggplot(time_spent_edited, aes(x=Age,y=Alone))+
+  geom_line(size = 1.5, color = "#e03c31") +
+  theme_minimal() +
+  theme(
+    text = element_text(family = "Lucida Sans Unicode", size = 12),
+    axis.title = element_text(size = 15, color = "#e03c31"),
+    legend.position = "none",  # Remove the legend
+    plot.title = element_text(size = 24, color = "#e03c31", hjust = 0.5)  # Título grande en el centro
+  ) +
+  labs(
+    x = "Age",
+    y = "Hours Alone",
+    title = "Time Alone"
+  )
+ggsave("Alone.jpg",width = 3840, height = 2160, units = c("px"))
+
+#Filtering for With_Friends. Making a table and a graph
+Friends_Table <- time_spent_edited %>%
+  summarize(Age,Friends)
+Friends_Table
+ggplot(time_spent_edited, aes(x=Age,y=Friends))+
+  geom_line(size = 1.5, color = "#f7ea48") +
+  theme_minimal() +
+  theme(
+    text = element_text(family = "Lucida Sans Unicode", size = 12),
+    axis.title = element_text(size = 15, color = "#f7ea48"),
+    legend.position = "none",  # Remove the legend
+    plot.title = element_text(size = 24, color = "#f7ea48", hjust = 0.5)  # Título grande en el centro
+  ) +
+  labs(
+    x = "Age",
+    y = "Hours with Friends",
+    title = "Time with Friends"
+  )
+ggsave("Friends.jpg",width = 3840, height = 2160, units = c("px"))
+
+#Filtering for With_Children. Making a table and a graph
+Children_Table <- time_spent_edited %>%
+  summarize(Age,Children)
+Children_Table
+ggplot(time_spent_edited, aes(x=Age,y=Children))+
+  geom_line(size = 1.5, color = "#2dc84d") +
+  theme_minimal() +
+  theme(
+    text = element_text(family = "Lucida Sans Unicode", size = 12),
+    axis.title = element_text(size = 15, color = "#2dc84d"),
+    legend.position = "none",  # Remove the legend
+    plot.title = element_text(size = 24, color = "#2dc84d", hjust = 0.5)  # Título grande en el centro
+  ) +
+  labs(
+    x = "Age",
+    y = "Hours with Children",
+    title = "Time with your Children"
+  )
+ggsave("Children.jpg",width = 3840, height = 2160, units = c("px"))
+
+mean(time_spent_edited$Children)
+median(time_spent_edited$Children)
+
+#Filtering for With_Immediate_Family. Making a table and a graph
+Family_Table <-time_spent_edited %>%
+  summarize(Age,Family)
+Family_Table
+ggplot(time_spent_edited, aes(x=Age,y=Family))+
+  geom_line()
+ggplot(time_spent_edited, aes(x=Age,y=Family))+
+  geom_line(size = 1.5, color = "#90e0ef") +
+  theme_minimal() +
+  theme(
+    text = element_text(family = "Lucida Sans Unicode", size = 12),
+    axis.title = element_text(size = 15, color = "#90e0ef"),
+    legend.position = "none",  # Remove the legend
+    plot.title = element_text(size = 24, color = "#90e0ef", hjust = 0.5)  # Título grande en el centro
+  ) +
+  labs(
+    x = "Age",
+    y = "Hours with Family",
+    title = "Time with your Family"
+  )
+
+ggsave("Family.jpg",width = 3840, height = 2160, units = c("px"))
+
+#Filtering for With_Partner. Making a table and a graph
+Partner_Table <-time_spent_edited %>%
+  summarize(Age,Partner)
+Partner_Table
+ggplot(time_spent_edited, aes(x=Age,y=Partner))+
+  geom_line()
+ggplot(time_spent_edited, aes(x=Age,y=Partner))+
+  geom_line(size = 1.5, color = "#147bd1") +
+  theme_minimal() +
+  theme(
+    text = element_text(family = "Lucida Sans Unicode", size = 12),
+    axis.title = element_text(size = 15, color = "#147bd1"),
+    legend.position = "none",  # Remove the legend
+    plot.title = element_text(size = 24, color = "#147bd1", hjust = 0.5)  # Título grande en el centro
+  ) +
+  labs(
+    x = "Age",
+    y = "Hours with Patner",
+    title = "Time with your Partner"
+  )
+ggsave("Partner.jpg",width = 3840, height = 2160, units = c("px"))
+
+#Filtering for Coworker. Making a table and a graph
+Partner_Table <-time_spent_edited %>%
+  summarize(Age,Coworkers)
+Partner_Table
+ggplot(time_spent_edited, aes(x=Age,y=Coworkers))+
+  geom_line()
+ggplot(time_spent_edited, aes(x=Age,y=Coworkers))+
+  geom_line(size = 1.5, color = "#FF00FF") +
+  theme_minimal() +
+  theme(
+    text = element_text(family = "Lucida Sans Unicode", size = 12),
+    axis.title = element_text(size = 15, color = "#FF00FF"),
+    legend.position = "none",  # Remove the legend
+    plot.title = element_text(size = 24, color = "#FF00FF", hjust = 0.5)  # Título grande en el centro
+  ) +
+  labs(
+    x = "Age",
+    y = "Hours with Coworkers",
+    title = "Time with your Coworkers"
+  )
+ggsave("Coworker.jpg",width = 3840, height = 2160, units = c("px"))

Code/us_child_care.R

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+library(ggplot2)
+
+#Data frame
+data <- data.frame(
+  Year = c(1965, 1975, 1985, 1998),
+  Married_Fathers = c(17, 17, 26, 51),
+  Married_Mothers = c(84, 67, 80, 99),
+  Single_Mothers = c(59, 63, 67, 85)
+)
+
+# Line ggplot
+ggplot(data, aes(x = Year)) +
+  geom_line(aes(y = Married_Fathers, color = "Married Fathers"), size = 1) +
+  geom_line(aes(y = Married_Mothers, color = "Married Mothers"), size = 1) +
+  geom_line(aes(y = Single_Mothers, color = "Single Mothers"), size = 1) +
+  geom_point(aes(y = Married_Fathers, color = "Married Fathers"), size=1.5)+
+  geom_point(aes(y = Married_Mothers, color = "Married Mothers"), size = 1.5)+
+  geom_point(aes(y = Single_Mothers, color = "Single Mothers"), size =1.5)+
+  labs(title = "Child Care Time per day (with children age 18 or under)",
+       x = "Year",
+       y = "minutes") +
+  scale_color_manual(
+    values = c("Married Fathers" = "#00a6ed", "Married Mothers" = "#f6511d", "Single Mothers" = "#ffb400")) +
+  theme_minimal() +
+  theme(legend.title = element_blank(), 
+        plot.title = element_text(size = 20, hjust = 0.5), 
+        legend.text = element_text(size = 18),
+        axis.title = element_text(size = 16),
+        axis.text = element_text(size = 12)) 
+
+
+ggsave("UsChildCare_plot.jpg",width = 3840, height = 2160, units = c("px"))
+
+