Design-Codes

I imported the data from the SAS website and created a dataframe named “ImmigrantVisaNumber2014.” The original data pertains to “Immigrant Visa Number Use by Category Fiscal Year 2014”.

ImmigrantVisaNumber2014 = data.frame( 
Category = factor(c("F1", "F2A", "F2B", "F3" ,"F4", "E1", "E2", "E3", "E4", "E5", "DV"), levels = c("F1", "F2A", "F2B","F3", "F4", "E1", "E2", "E3", "E4", "E5", "DV")), 
Visa_Issuances_At_Offices_Abroad = c(21511, 80041, 15137, 21931, 59140, 1680, 1880, 7088, 1489, 922, 51018), 
USCIS_Adjustments = c(2480, 9451, 2382, 2100, 7020, 38928, 47191, 35611, 6798, 1464 , 1324) 
) 

Re-Design 1: Bar Plot with GGplot2

library(ggplot2)  
melted_data = reshape2::melt(ImmigrantVisaNumber2014, id.vars = "Category")  

melted_data$variable = factor(melted_data$variable, levels = 
c("Visa_Issuances_At_Offices_Abroad","USCIS_Adjustments")) 
ggplot(melted_data, aes(x = Category, y = value, fill = variable)) +
geom_bar(stat = "identity", width = 0.4) +  
labs(title = "Immigrant Visa Number\nUse By Category\nFiscal Year 2014",x = "Category", y = "Count") +  
scale_fill_manual(values = c("USCIS_Adjustments" = "indianred", "Visa_Issuances_At_Offices_Abroad" = "steelblue")) +  
theme(legend.position = "bottom", 
      text = element_text(size = 10, face = "bold"), 
      axis.text.x = element_text(size = 6, face = "bold"), 
      axis.text.y = element_text(size = 6, face = "bold"), 
      axis.title.x = element_text(size = 10, face = "bold"), 
      axis.title.y = element_text(size = 10, face = "bold"), 
      plot.title = element_text(size = 10, face = "bold", hjust = 0.5),
      legend.title = element_text(face = "bold")) + 
guides(fill = guide_legend(title = NULL)) 

Design 1: Bar Plot with Plotly

library(ggplot2)
library(reshape2)
library(plotly)

Attaching package: 'plotly'

The following object is masked from 'package:ggplot2':

    last_plot

The following object is masked from 'package:stats':

    filter

The following object is masked from 'package:graphics':

    layout

melted_data = reshape2::melt(ImmigrantVisaNumber2014, id.vars = "Category")

melted_data$variable = factor(melted_data$variable, levels = c("Visa_Issuances_At_Offices_Abroad", "USCIS_Adjustments"))

gg = ggplot(melted_data, aes(x = Category, y = value, fill = variable)) +
  geom_bar(stat = "identity", position = "dodge", width = 0.7) +
  labs(title = "Immigrant Visa Number Use By Category Fiscal Year 2014", x = "Category", y = "Count") +
  scale_fill_manual(values = c("USCIS_Adjustments" = "indianred", "Visa_Issuances_At_Offices_Abroad" = "steelblue")) +
  theme(legend.position = "bottom",
        text = element_text(size = 10, face = "bold"),
        axis.text.x = element_text(size = 6, face = "bold"),
        axis.text.y = element_text(size = 6, face = "bold"),
        axis.title.x = element_text(size = 10, face = "bold"),
        axis.title.y = element_text(size = 10, face = "bold"),
        plot.title = element_text(size = 9, face = "bold", hjust = 0.5),  # Add a comma here
        legend.title = element_text(face = "bold")) +guides(fill = guide_legend(title = NULL))

plotly_gg = ggplotly(gg)

plotly_gg = plotly_gg %>%
  layout(legend = list(orientation = "h", y = -0.2, x = 0.2))

print(plotly_gg)

Design 2: Line Plot with Plotly

library(ggplot2) 
library(plotly) 
base_plot = ggplot(melted_data, aes(x = Category, y = value, color = variable, group = variable)) + geom_line() + facet_wrap(~variable, scales = "free_y") + 
labs(title = "Immigrant Visa Number Use By Category FY 2014", x = "Category", y = "Count") + 
scale_color_manual(values = c("Visa_Issuances_At_Offices_Abroad" = "skyblue", "USCIS_Adjustments" = "red")) + theme(legend.position = "bottom") 

highlight_plot = ggplotly(base_plot, tooltip = c("Category", "value", "variable")) 

highlight_plot = highlight_plot %>%  
layout(legend = list(orientation = "h", x = 0.2, y = -0.1, traceorder = 'normal')) 

highlight_plot = highlight_plot %>%  
layout(title = list(text = "Immigrant Visa Number Use By Category FY 2014", x = 0.5, xanchor = "center")) 

highlight_plot 

Design 3: Bubble Plot with Plotly

library(ggplot2) 
library(plotly) 

base_plot = ggplot(melted_data, aes(x = Category, y = value, size = value, color = variable)) + geom_point(alpha = 0.9) + labs(title = "Immigrant Visa Number Use By Category FY 2014", x = "Category", y = "Count") + scale_color_manual(values = c("Visa_Issuances_At_Offices_Abroad" = "skyblue", "USCIS_Adjustments" = "red")) + 
theme( text = element_text(size = 10, face = "bold"), 
       axis.text.x = element_text(size = 10, face = "bold"), 
       axis.text.y = element_text(size = 10, face = "bold"), 
       axis.title.x = element_text(size = 12, face = "bold"), 
       axis.title.y = element_text(size = 12, face = "bold"), 
       plot.title = element_text(size = 10, face = "bold", hjust = 0.5)) 

highlight_plot <- ggplotly(base_plot, tooltip = c("Category", "value", "variable")) 

highlight_plot <- highlight_plot %>%layout( 
  title = list(text = "Bubble Chart of Visa Issuances and USCIS Adjustments", x = 0.5, xanchor = "center"), 
  legend = list(orientation = "h", x = 0.2, y = -0.3, traceorder = 'normal', title = list(text = NULL))) 

highlight_plot