[main]: clean up

.Rproj.user/461AD266/pcs/files-pane.pper

@@ -1,9 +0,0 @@
-{
-    "path": "~/football_competitiveness",
-    "sortOrder": [
-        {
-            "columnIndex": 2,
-            "ascending": true
-        }
-    ]
-}

.Rproj.user/461AD266/pcs/source-pane.pper

@@ -1,3 +0,0 @@
-{
-    "activeTab": 0
-}

.Rproj.user/461AD266/pcs/windowlayoutstate.pper

@@ -1,14 +0,0 @@
-{
-    "left": {
-        "splitterpos": 312,
-        "topwindowstate": "NORMAL",
-        "panelheight": 744,
-        "windowheight": 782
-    },
-    "right": {
-        "splitterpos": 469,
-        "topwindowstate": "NORMAL",
-        "panelheight": 744,
-        "windowheight": 782
-    }
-}

.Rproj.user/461AD266/pcs/workbench-pane.pper

@@ -1,5 +0,0 @@
-{
-    "TabSet1": 0,
-    "TabSet2": 0,
-    "TabZoom": {}
-}

.Rproj.user/461AD266/sources/prop/9DEA2FB2

@@ -1,4 +0,0 @@
-{
-    "source_window_id": "",
-    "Source": "Source"
-}

.Rproj.user/461AD266/sources/prop/INDEX

@@ -1 +0,0 @@
-~%2Ffootball_competitiveness%2Fdata_manipulation.R="9DEA2FB2"

.Rproj.user/461AD266/sources/session-9bca3639/2E827BA4

@@ -1,24 +0,0 @@
-{
-    "id": "2E827BA4",
-    "path": "~/football_competitiveness/data_manipulation.R",
-    "project_path": "data_manipulation.R",
-    "type": "r_source",
-    "hash": "0",
-    "contents": "",
-    "dirty": false,
-    "created": 1785865647905.0,
-    "source_on_save": false,
-    "relative_order": 1,
-    "properties": {
-        "source_window_id": "",
-        "Source": "Source"
-    },
-    "folds": "",
-    "lastKnownWriteTime": 1785865410,
-    "encoding": "UTF-8",
-    "collab_server": "",
-    "source_window": "",
-    "last_content_update": 1785865410,
-    "read_only": false,
-    "read_only_alternatives": []
-}

.Rproj.user/461AD266/sources/session-9bca3639/2E827BA4-contents

@@ -1,126 +0,0 @@
-European_performance_data = read_csv('Data/European performance historical data.csv')
-Points_difference_data <- read_csv("Data/Points difference.csv")
-Players_used_data <- read_csv("Data/European clubs number of players used.csv")
-Top_goalscorers_data <- read_csv("Data/Average top scorers.csv")
-Market_value_data <- read_csv("Data/Market values.csv")
-gini_coeffecient_data <- Market_value_data %>%
-  select(-`Average market value of clubs`)
-all_seasons <- unique(European_performance_data$Season)
-
-overall_country_performance <- European_performance_data %>%
-  group_by(Country) %>%
-  summarise(total_performance = sum(European_performance, na.rm = TRUE)) %>%
-  arrange(desc(total_performance))
-
-#season by season performance
-country_performance_by_season <- European_performance_data %>%
-  filter(Country %in% c("Germany", "Spain", "England", "Portugal", "Italy", "France")) %>%
-  group_by(Country, Season) %>%
-  summarise(
-    European_performance = sum(European_performance, na.rm = TRUE),
-    .groups = "drop"
-  ) %>%
-  complete(Country, Season = all_seasons, fill = list(European_performance = 0))
-#season by season performance by competition
-country_performance_by_season_comp_breakdown <- European_performance_data %>%
-  filter(Country %in% c("Germany", "Spain", "England", "Portugal", "Italy", "France")) %>%
-  group_by(Country, Season) %>%
-  summarise(
-    CL = sum(European_performance[Competition == "CL"], na.rm = TRUE),
-    EL = sum(European_performance[Competition == "EL"], na.rm = TRUE),
-    .groups = "drop"
-  ) %>%
-  complete(Country, Season = all_seasons, fill = list(CL = 0, EL = 0)) %>%
-  pivot_longer(cols = c("CL", "EL"), names_to = "competition", values_to = "European_performance") %>%
-  mutate(European_performance = ifelse(competition == "CL", European_performance/2, European_performance)) #halving score for CL as had double weighting
-
-#join all metrics data together
-#impute missing Gini coefficient with average for league - assumed the same over time
-season_league_metrics_dataset <- Points_difference_data %>%
-  left_join(Players_used_data, by = c("Country", "Season")) %>%
-  left_join(Top_goalscorers_data, by = c("Country", "Season")) %>%
-  left_join(gini_coeffecient_data, by = c("Country", "Season")) %>%
-  mutate(season_start = as.integer(str_extract(Season, "^\\d{4}"))) %>%
-  group_by(Country) %>%
-  mutate(Gini_coefficient = coalesce(Gini_coefficient, mean(Gini_coefficient, na.rm = TRUE))) %>%
-  ungroup()
-
-#average country performance
-average_country_metrics <- season_league_metrics_dataset %>%
-  group_by(Country) %>%
-  summarise(across(!contains("eason"), mean, na.rm = TRUE))
-
-#scaling to min-max of variables
-average_country_metrics_scaled <- average_country_metrics
-average_country_metrics_scaled[,-1] <- lapply(average_country_metrics[,-1], function(x) {
-  (x - min(x)) / (max(x) - min(x))
-})
-
-#scaling metrics normally
-scaled_metrics_data <- season_league_metrics_dataset %>%
-  mutate(across(
-    c(First_and_second, First_and_CL, First_and_relegated, CL_and_relegated,
-      Winners_GD, Top_4_total_GD, Average_number_of_players,
-      Average_goals_by_top_3_players, Gini_coefficient),
-    ~ as.numeric(scale(.))
-  ))
-
-#join metrics data to European performance data
-#calculate European performance in next season as lead
-season_league_full_dataset <- season_league_metrics_dataset %>%
-  left_join(country_performance_by_season, by = c("Country", "Season")) %>%
-  arrange(Season, Country) %>%
-  group_by(Country) %>%
-  mutate(lead_european_performance = dplyr::lead(European_performance)) %>%
-  ungroup()
-
-#join metrics data to European performance data by competition
-#calculate European performance in next season as lead
-season_league_full_dataset_comp_breakdown <- season_league_metrics_dataset %>%
-  left_join(country_performance_by_season_comp_breakdown, by = c("Country", "Season")) %>%
-  arrange(Season, Country) %>%
-  group_by(Country, competition) %>%
-  mutate(lead_european_performance = dplyr::lead(European_performance)) %>%
-  ungroup()
-
-#full data scaled
-scaled_full_data <- scaled_metrics_data %>%
-  left_join(country_performance_by_season, by = c("Country", "Season")) %>%
-  arrange(Season, Country) %>%
-  group_by(Country) %>%
-  mutate(lead_european_performance = dplyr::lead(European_performance)) %>%
-  ungroup()
-
-#data by competition scaled
-scaled_full_data_comp_breakdown <- scaled_metrics_data %>%
-  left_join(country_performance_by_season_comp_breakdown, by = c("Country", "Season")) %>%
-  arrange(Season, Country) %>%
-  group_by(Country, competition) %>%
-  mutate(lead_european_performance = dplyr::lead(European_performance)) %>%
-  ungroup()
-
-#full dataset with competition breakdown and full
-pivoted_scaled_full_data_comp_breakdown <- scaled_full_data_comp_breakdown %>%
-  pivot_wider(names_from = competition, values_from = c(European_performance, lead_european_performance)) %>%
-  mutate(European_performance = 2*European_performance_CL + European_performance_EL,
-         lead_european_performance = 2*lead_european_performance_CL + lead_european_performance_EL)
-
-#basic profiling based on European performance
-quantile_splits <- scaled_full_data %>%
-  mutate(
-    performance_group = ntile(European_performance, 3)
-  )
-european_performance_groups_characteristics <- quantile_splits %>%
-  group_by(performance_group) %>%
-  summarise(across(where(is.numeric), mean, na.rm = TRUE)) %>%
-  select(-season_start) %>%
-  mutate(label = case_when(
-    performance_group == 1 ~ "Worst performing",
-    performance_group == 2 ~ "Middle performing",
-    performance_group == 3 ~ "Best performing"
-  )) %>%
-  mutate(performance_group = case_when(
-    label == "Worst performing" ~ 1,
-    label == "Middle performing" ~ 3,
-    label == "Best performing" ~ 2
-  ))

.gitignore

@@ -0,0 +1,21 @@
+# R session files
+.Rhistory
+.Rapp.history
+.RData
+.RDataTmp
+.Ruserdata
+
+# RStudio project/user state
+.Rproj.user/
+
+# renv local library/state (keep renv.lock and renv/activate.R tracked)
+renv/library/
+renv/python/
+renv/staging/
+
+# IDE/project metadata
+.idea/
+.vscode/
+
+# OS cruft
+.DS_Store

football_competitiveness.Rproj

@@ -1,13 +0,0 @@
-Version: 1.0
-
-RestoreWorkspace: Default
-SaveWorkspace: Default
-AlwaysSaveHistory: Default
-
-EnableCodeIndexing: Yes
-UseSpacesForTab: Yes
-NumSpacesForTab: 2
-Encoding: UTF-8
-
-RnwWeave: Sweave
-LaTeX: pdfLaTeX