{"metadata":{"kernelspec":{"name":"ir","display_name":"R","language":"R"},"language_info":{"name":"R","codemirror_mode":"r","pygments_lexer":"r","mimetype":"text/x-r-source","file_extension":".r","version":"4.0.5"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"library(tidyverse) # metapackage of all tidyverse packages","metadata":{"_uuid":"051d70d956493feee0c6d64651c6a088724dca2a","_execution_state":"idle","execution":{"iopub.status.busy":"2021-10-26T03:16:22.176881Z","iopub.execute_input":"2021-10-26T03:16:22.178714Z","iopub.status.idle":"2021-10-26T03:16:23.62686Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#reading data\n\ndf_plays <- df_plays <- read_csv(\"../input/nfl-big-data-bowl-2022/plays.csv\",\n                    col_types = cols())\n\n#using for display names\ndf_players <- read_csv(\"../input/nfl-big-data-bowl-2022/players.csv\",\n                      col_types = cols())","metadata":{"execution":{"iopub.status.busy":"2021-10-26T03:16:25.574697Z","iopub.execute_input":"2021-10-26T03:16:25.576649Z","iopub.status.idle":"2021-10-26T03:16:25.859358Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sort(unique(df_plays$returnerId))","metadata":{"execution":{"iopub.status.busy":"2021-10-26T03:21:52.914855Z","iopub.execute_input":"2021-10-26T03:21:52.916862Z","iopub.status.idle":"2021-10-26T03:21:52.966741Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df_playsReturnerId <- df_plays %>%\n\n    #selecting relevant columns\n    select(gameId, playId, returnerId, playDescription, specialTeamsPlayType) %>%\n    \n    #splitting returnerId into 3 variables\n    separate(returnerId, into = c(\"returnerId1\", \"returnerId2\", \"returnerId3\"),\n            sep = ';') %>%\n\n    #gathering so each row is a returner\n    gather(key = \"type\", value = \"returnerId\", returnerId1, returnerId2, returnerId3) %>%\n\n    #making returnerId an integer\n    mutate(returnerId = as.integer(returnerId)) %>%\n\n    #filtering for punt plays when the returnerId is not NA\n    filter(!is.na(returnerId)) %>%\n\n    #joining players\n    inner_join(df_players, by = c(\"returnerId\" = 'nflId')) %>%\n\n    #selecting relevant columns\n    select(gameId, playId, playDescription, returnerId, displayName, specialTeamsPlayType)\n\n\n","metadata":{"execution":{"iopub.status.busy":"2021-10-26T03:25:54.819278Z","iopub.execute_input":"2021-10-26T03:25:54.821132Z","iopub.status.idle":"2021-10-26T03:25:55.18908Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#showing 10 random rows. See display name referred to in playDescription:\ndf_playsReturnerId %>%\n    sample_n(10)","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#showing 10 random rows (punt only). See display name referred to in playDescription:\ndf_playsReturnerId %>%\n    filter(specialTeamsPlayType == \"Punt\") %>%\n    sample_n(10)","metadata":{},"execution_count":null,"outputs":[]}]}