more data cleaning

notebooks/dataCleaning.R

@@ -1,5 +1,3 @@
-##################### The first dataset ##############################
-
 ## Loading R packages and source the "getshots" customized own function
 library(jsonlite)
 library(tidyverse)
@@ -9,6 +7,8 @@ library(REdaS)
 library(yd2m)
 library(purrr)
 
+##################### The first dataset ##############################
+
 # code and data from https://github.com/Dato-Futbol/xg-model
 get_shots <- function(file_path, name_detail, save_files = F){
   
@@ -102,10 +102,9 @@ get_data <- function(event_path, info_path) {
 # data2 <- get_data(event_path = "data/events.csv", info_path = "data/ginf.csv")
 # write.csv(data2, file = "data/data2.csv")
 
-
 ##################### The third dataset ##############################
 
-# make angle from the x, y coordinares for the 3rd dataset
+# make angle from the x, y coordinates for the 3rd dataset
 loc2angle <- function(x, y) {
   rads <- atan(7.32 * x / (x^2 + (y - 34)^2 - (7.32/2)^2))
   rads <- ifelse(rads<0, base::pi + rads, rads)
@@ -113,21 +112,16 @@ loc2angle <- function(x, y) {
   deg
 }
 
+# distance to goal
 loc2distance <- function(x, y) {
   sqrt(x^2 + y^2)
 }
 
+# distance between two points on the pitch
 loc2locdistance <- function(x1, y1, x2, y2) {
   sqrt( (x1 - x2)^2 + (y1 - y2)^2 )
 }
 
-# TODO
-# osobno bramkarz, wartość opponent_Goalkeeper
-# kolejność w row_number() wg odlegości do piłki z podziałem na teammate/opponent
-# przykład, najbliżej w teammate -> teammate_1,
-# przykład najbliżej w opponent -> opponent_1
-# w przypadku NA, wypełnić wartościami teammete_(nt+1):11, opponent_(no+1):11
-
 get_shots2 <- function(json_file) {
   data <- fromJSON(json_file) %>% filter(type$name == "Shot") %>% dplyr::select(c(minute, position, location, shot))
   
@@ -161,13 +155,6 @@ get_shots2 <- function(json_file) {
         } else if ( !("teammate" %in% groups_count$teammate) ) {
           groups_count <- groups_count %>% add_row(teammate = "teammate", n = 0)
         }
-        # df$distance <- loc2locdistance(x1 = df$x, y1 = df$y, x2 = data$x1, y1 = data$y1)
-        # df <- df %>% mutate(distance = loc2locdistance(x1 = x, y1 = y, x2 = data$x1, y1 = data$y1)) %>% arrange(distance)
-        # df <- df %>% arrange(distance)
-        # df <- df %>% unnest(c(x, y, teammate))
-        # df$x <- as.numeric(df$x)
-        # df$y <- as.numeric(df$y)
-        # df$teammate <- as.logical(df$teammate) %>% as.numeric()
         
         na_df <- as.data.frame(matrix("na", nrow = 21 - nrow(df), ncol = ncol(df)))
         colnames(na_df) <- colnames(df)
@@ -179,28 +166,23 @@ get_shots2 <- function(json_file) {
           select(-c(teammate, position_name, rown, distance, x1, y1)) %>%
           mutate(x = ifelse(x == "na", NA, x),
                  y = ifelse(x == "na", NA, y))
-        
-        # dff <- dff %>% mutate(row = row_number()) %>% 
-        #   mutate(position_teammate = paste(ifelse(position_name == "Goalkeeper", position_name, row), teammate, sep = "_")) %>% 
-        #   select(-c(teammate, position_name, row))
       } else {
         dff <- as.data.frame(matrix("na", nrow = 21, ncol = 3))
         colnames(dff) <- c("x", "y", "teammate")
         dff$teammate <- rep(c("opponent", "teammate"), c(11, 10))
         dff <- dff %>% group_by(teammate) %>% mutate(rown = row_number()) %>% ungroup() %>% 
-          mutate(position_teammate = paste(teammate, rown)) %>% 
+          mutate(position_teammate = paste(teammate, rown, sep = "_")) %>% 
-          select(c(-teammate, rown)) %>% 
+          select(-c(teammate, rown)) %>% 
           mutate(x = ifelse(x == "na", NA, x),
                  y = ifelse(x == "na", NA, y))
       }
-      # print(dff)
       # print(wider_df)
       # stop("123")
       # %>%
+      # stop("123")
       wider_df <- dff %>%
         pivot_wider(names_from = position_teammate, values_from = c(x, y), names_sep = "_player_")
       # wider_df <- apply(wider_df, MARGIN = 2, unlist)
-      wider_df
     }, data$shot$freeze_frame)
   },
     error = function(e) {
@@ -208,22 +190,7 @@ get_shots2 <- function(json_file) {
       print(json_file)
       print(paste("An error occurred:", e$message))
   })
-  print(df_players_location)
   df_players_location <- df_players_location %>% t()
-  print(df_players_location)
-  
-  # df <- do.call(rbind, df_test$shot$freeze_frame[[1]]$location) %>% as.data.frame()
-  # dff <- cbind(df, df_test$shot$freeze_frame[[1]]$teammate)
-  # colnames(dff) <- c("x", "y", "teammate")
-  # 
-  # 
-  # na_df <- as.data.frame(matrix(NA, nrow = 21 - nrow(df), ncol = ncol(dff)))
-  # colnames(na_df) <- colnames(dff)
-  # dff <- rbind(dff, na_df)
-  # 
-  # wider_df <- dff %>%
-  #   mutate(row = row_number()) %>%
-  #   pivot_wider(names_from = row, values_from = c(x, y, teammate), names_sep = "_player")
   
   tryCatch({ # TODO reduce error cases
     data$number_of_players_opponents <- mapply(function(sublist, x1_threshold) {
@@ -362,18 +329,15 @@ file_names <- list.files(path = "data/la_liga_events/", pattern = "*.json")
 data_list <- lapply(paste("data/la_liga_events/", file_names, sep = ""), get_shots2)
 combined_data <- bind_rows(data_list)
 
-# ss <- lapply(data_list, nrow)
-# sss <- unlist(ss)
-# 
 # # sample data
-data <- fromJSON("data/la_liga_events/ (1000).json") %>% filter(type$name == "Shot") %>% dplyr::select(c(minute, position, location, shot))
+# data <- fromJSON("data/la_liga_events/ (1000).json") %>% filter(type$name == "Shot") %>% dplyr::select(c(minute, position, location, shot))
 
 data3_final <- combined_data %>% select(-c(shot_outcome_name,
                                    shot_saved_off_target,
                                    shot_saved_to_post,
                                    kick_off)) %>% 
   mutate(shot_kick_off = ifelse(is.na(shot_kick_off), FALSE, shot_kick_off))
-pattern <- "^(x_player|y_player|teammate_player)[0-9]+$"
+pattern <- "^(x_player_|y_player_)([0-9]|Goalkeeper)+$"
 cols <- names(data3_final)[grepl(pattern, names(data3_final))]
 data3_final <- data3_final %>% unnest(all_of(cols))
 write_csv(data3_final, file = "data/final_data.csv")