Solution trials

Solution_for_Denis.md

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+    library(dplyr)
+    library(readr)
+    library(ggplot2)
+
+    dat <- read.csv2("wows_playerbase_data.csv", stringsAsFactors = FALSE)
+    dat <- dat[-c(762:805), ]
+
+    dat$Battles <- gsub(" ", "", dat$Battles) 
+    dat$Avg..damage <- gsub(" ", "", dat$Avg..damage) 
+    dat$Win.rate <- gsub("%", "", dat$Win.rate)  
+    dat$Win.rate <- gsub(" ", "", dat$Win.rate)
+
+    dat$Battles <- as.numeric(dat$Battles) 
+    dat$Avg..damage <- as.numeric(dat$Avg..damage) 
+    dat$Win.rate <- as.numeric(dat$Win.rate) 
+    #dat
+
+    dat <- dat %>% filter(Tier >= 3 & Tier <= 10)
+    #dat
+
+    dat <- dat %>% filter(Battles >= 200000)
+    #dat
+
+    dat <- subset(dat, !(Type %in% c("Submarine ", "Aircraft Carrier ")))
+    #dat
+
+    dat1 <- dat %>%
+      group_by(Nation, Tier, Type) %>%
+      filter(Battles == max(Battles, na.rm = TRUE)) %>%
+      ungroup()
+    #dat1
+
+    dat1 <- dat1 %>%
+      group_by(Nation, Tier) %>%
+      mutate(ship_type_count = n_distinct(Type)) %>%
+      filter(ship_type_count == 3) %>%
+      ungroup()
+
+    #print(dat1)
+
+    dat_groups <- dat1 %>%
+      group_by(Nation, Tier) %>%
+      slice_head(n = 3) %>%  
+      ungroup()
+
+    #print(dat_groups)
+
+    dat_grouped <- dat_groups %>%
+      group_by(Nation, Tier, Type) %>%
+      summarise(
+        total_battles = sum(Battles, na.rm = TRUE), 
+        avg_winrate = mean(Win.rate, na.rm = TRUE), 
+        avg_damage = mean(Avg..damage, na.rm = TRUE))
+
+    ## `summarise()` has grouped output by 'Nation', 'Tier'. You can override using
+    ## the `.groups` argument.
+
+    #dat_grouped
+
+    dat_grouped <- dat_grouped %>%
+      group_by(Nation, Tier) %>%
+      mutate(
+        points = ifelse(total_battles == max(total_battles), 1, 0)
+      ) %>%
+      ungroup()
+
+    nation_points <- dat_grouped %>%
+      group_by(Nation) %>%
+      summarise(
+        total_points = sum(points)
+      ) %>%
+      arrange(desc(total_points))  # Sort nations by total points, descending order
+
+    most_unpopular_nation <- nation_points %>%
+      filter(total_points == min(total_points))
+
+    top_3_nations <- nation_points %>%
+      slice_head(n = 3)  # Select the top 3 nations based on total points
+
+    top_3_nations
+
+    ## # A tibble: 3 × 2
+    ##   Nation     total_points
+    ##   <chr>             <dbl>
+    ## 1 "Germany "            8
+    ## 2 "Japan "              8
+    ## 3 "U.K. "               8
+
+    most_unpopular_nation
+
+    ## # A tibble: 1 × 2
+    ##   Nation      total_points
+    ##   <chr>              <dbl>
+    ## 1 "Pan-Asia "            1
+
+    top_ships <- dat_grouped %>%
+      group_by(Nation, Tier, Type) %>%
+      filter(total_battles == max(total_battles)) %>% 
+      slice(1) 
+
+    head(top_ships)
+
+    ## # A tibble: 6 × 7
+    ## # Groups:   Nation, Tier, Type [6]
+    ##   Nation     Tier Type          total_battles avg_winrate avg_damage points
+    ##   <chr>     <int> <chr>                 <dbl>       <dbl>      <dbl>  <dbl>
+    ## 1 "France "     5 "Battleship "       2164223        49.7      36275      0
+    ## 2 "France "     5 "Cruiser "          3956587        52.2      25688      1
+    ## 3 "France "     5 "Destroyer "         794031        51.1      22116      0
+    ## 4 "France "     6 "Battleship "       3650246        52.3      47474      0
+    ## 5 "France "     6 "Cruiser "          4357927        50.6      28773      1
+    ## 6 "France "     6 "Destroyer "        2167144        50.6      24839      0
+
+    dat_points_summary <- dat_grouped %>%
+      group_by(Nation, Tier) %>%
+      summarise(tier_points = sum(points)) %>%
+      ungroup()
+
+    ## `summarise()` has grouped output by 'Nation'. You can override using the
+    ## `.groups` argument.
+
+    nation_total_points <- dat_points_summary %>%
+      group_by(Nation) %>%
+      summarise(total_points = sum(tier_points)) %>%
+      ungroup() %>%
+      arrange(desc(total_points))
+
+    ggplot(dat_points_summary, aes(x = tier_points, y = reorder(Nation, -tier_points), fill = factor(Tier))) +
+      geom_bar(stat = "identity") +
+        geom_text(aes(label = Tier), position = position_stack(vjust = 0.5), color = "white") +  # Add tier labels on the bars
+
+      labs(
+        x = "Points",
+        y = "Nation",
+        title = "Popularity of Nations by Tier in World of Warships",
+        fill = "Tier"
+      ) +
+      theme_minimal() +
+      theme(legend.position = "bottom")
+
+![](Solution_for_Denis_files/figure-markdown_strict/unnamed-chunk-14-1.png)