Final.knit

library(sunburstR)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(tidyr)
library(readr)
library(htmlwidgets)
library(htmltools)

data <- read_csv("~/Downloads/DATA VISUALIZATION/Final Project/master Data/All India level Person Arrested under Cyber Crime (IT Act + IPC Section) by Age Group during 2002-2011.csv")

## Rows: 176 Columns: 9
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): Category, Crime Head
## dbl (7): Below 18 Years, Between 18 - 30 Years, Between 30 -45 Years, Betwee...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

data_sunburst <- data %>%
  filter(Category != "Grand Total (Offences under IT Act + IPC)") %>%
  select(Category, `Crime Head`, Year,
         `Below 18 Years`, `Between 18 - 30 Years`,
         `Between 30 -45 Years`, `Between 45 - 60 Years`,
         `Above 60 Years`) %>%
  pivot_longer(
    cols = c(`Below 18 Years`, `Between 18 - 30 Years`,
             `Between 30 -45 Years`, `Between 45 - 60 Years`,
             `Above 60 Years`),
    names_to = "Age_Group",
    values_to = "Total_Arrested"
  ) %>%
  filter(Total_Arrested > 0) %>%
  mutate(
    Category = ifelse(is.na(Category), "Unknown", Category),
    `Crime Head` = ifelse(is.na(`Crime Head`), "Unknown", `Crime Head`),
    Year = ifelse(is.na(Year), "Unknown", Year),
    Age_Group = ifelse(is.na(Age_Group), "Unknown", Age_Group),
    path = paste(Category, `Crime Head`, Year, Age_Group, sep = "-")
  ) %>%
  select(path, total = Total_Arrested, Age_Group)

head(data_sunburst)  # Verify data

## # A tibble: 6 × 3
##   path                                                           total Age_Group
##   <chr>                                                          <dbl> <chr>    
## 1 Offences under IT Act-Tampering Computer Source Department (S…     4 Between …
## 2 Offences under IT Act-Tampering Computer Source Department (S…     3 Between …
## 3 Offences under IT Act-Hacking Computer Systems - i) Loss/ Dam…     4 Between …
## 4 Offences under IT Act-Hacking Computer Systems - ii) Hacking …    28 Between …
## 5 Offences under IT Act-Hacking Computer Systems - ii) Hacking …     5 Between …
## 6 Offences under IT Act-Hacking Computer Systems - ii) Hacking …     1 Between …

age_colors <- c(
  "Below 18 Years" = "#1b9e77",
  "Between 18 - 30 Years" = "#d95f02",
  "Between 30 -45 Years" = "#7570b3",
  "Between 45 - 60 Years" = "#e7298a",
  "Above 60 Years" = "#66a61e"
)

sunburst(data_sunburst, 
         count = TRUE, 
         percent = TRUE,
         colors = age_colors,
         legend = list(w = 150, h = 20, r = 10),
         legendOrder = names(age_colors))

## Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON.

# Remove 'Grand Total' and structure data correctly for each year
data_sunburst <- data %>%
  filter(Category != "Grand Total (Offences under IT Act + IPC)") %>%
  select(Category, `Crime Head`, Year,
         `Below 18 Years`, `Between 18 - 30 Years`,
         `Between 30 -45 Years`, `Between 45 - 60 Years`,
         `Above 60 Years`) %>%
  pivot_longer(
    cols = c(`Below 18 Years`, `Between 18 - 30 Years`,
             `Between 30 -45 Years`, `Between 45 - 60 Years`,
             `Above 60 Years`),
    names_to = "Age_Group",
    values_to = "Total_Arrested"
  ) %>%
  filter(Total_Arrested > 0) %>%
  mutate(
    path = paste(Category, `Crime Head`, Age_Group, sep = "-")  # Exclude Year from path to filter dynamically
  ) %>%
  select(path, total = Total_Arrested, Year, Age_Group)

head(data_sunburst)  # Check data

## # A tibble: 6 × 4
##   path                                                     total  Year Age_Group
##   <chr>                                                    <dbl> <dbl> <chr>    
## 1 Offences under IT Act-Tampering Computer Source Departm…     4  2002 Between …
## 2 Offences under IT Act-Tampering Computer Source Departm…     3  2002 Between …
## 3 Offences under IT Act-Hacking Computer Systems - i) Los…     4  2002 Between …
## 4 Offences under IT Act-Hacking Computer Systems - ii) Ha…    28  2002 Between …
## 5 Offences under IT Act-Hacking Computer Systems - ii) Ha…     5  2002 Between …
## 6 Offences under IT Act-Hacking Computer Systems - ii) Ha…     1  2002 Between …

age_colors <- c(
  "Below 18 Years" = "#1b9e77",
  "Between 18 - 30 Years" = "#d95f02",
  "Between 30 -45 Years" = "#7570b3",
  "Between 45 - 60 Years" = "#e7298a",
  "Above 60 Years" = "#66a61e"
)

unique_years <- unique(data_sunburst$Year)

for (year_selected in unique_years) {
  # Filter data for the specific year
  data_filtered <- data_sunburst %>%
    filter(Year == year_selected)
  
  # Create Sunburst Chart
  chart <- sunburst(data_filtered, 
                    count = TRUE, 
                    percent = TRUE,
                    colors = age_colors,
                    legend = list(w = 150, h = 20, r = 10),
                    legendOrder = names(age_colors))

  # Add a title with the year
  chart <- htmlwidgets::prependContent(chart, htmltools::tags$h2(paste("Sunburst Chart - Year:", year_selected)))

print(chart)
}

## Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON.
## Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON.
## Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON.
## Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON.
## Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON.
## Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON.
## Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON.
## Input to asJSON(keep_vec_names=TRUE) is a named vector. In a future version of jsonlite, this option will not be supported, and named vectors will be translated into arrays instead of objects. If you want JSON object output, please use a named list instead. See ?toJSON.