Help with questions and analyze for me, thank you! Variables:…

Question Help with questions and analyze for me, thank you! Variables:… Help with questions and analyze for me, thank you! Variables:Player_name: name of the playerPlayer_id: specific id number given to a specific playerSeason_id: specific id number given to identify the season the stats are fromGp: number of games played that seasonAge: how old the player was during that seasonMin: total number of minutes a player was on the court that particular seasonFgm: total number of field goals made in that seasonFga: the total number of field goals attempted in that seasonFg3m: the total number of 3 point field goals made that seasonFtm: the number of free throws made that seasonFta: number of free throws attempted that seasonOreb: total number of offensive rebounds grabbed that seasonDreb: total number of defensive rebounds grabbed that seasonAst: total number of assists the player had that seasonTov: total number of turnovers the player had that seasonStl: total number of steals the player had that seasonBlk: total number of blocks the player had that seasonPts: total number of points the player had that seasonREF Dataset link: https://github.com/Jman4190/nba-stats-model/blob/master/nba-stats-csv/2018_19_projections_plus_real_player_name.csv (All questions refer to the dataset link above, you need to make your own analysis in order to solve these questions, use relevant python and data science knowledge to do so and import as necessary). The answers are relatively easy but need an thorough analysis and walk through on each question so that everything is addressed 1 by 1 to solve the question at hand.  Analysis Plan:Around what age do players tend to have their highest scoring season (most pts)?Variables Involved: Cleaning: Modeling/Computation: Graphs: When predicting the total number of points scored in a season what predictor improves the r2 score the most when compared to a model with all other variables?Variables Involved: Cleaning: Modeling/Computation: Graphs: What predictors are the most effective at predicting how many points a player scores in a season?Variables Involved: Cleaning: Modeling/Computation: Graphs: When looking at all the statistical predictors (points, oreb, dreb, ast, stl, blk, & tov) what clusters do you start to see in the data?Variables Involved: Cleaning: Modeling/Computation: Graphs: When looking at the season id which season had the highest scoring players?Variables Involved: Cleaning: Modeling/Computation: Graphs: What is the breakdown of field goals and field goal attempts by 2 pt field goals, 3 pointers and free throws and how it has evolved. (Can get the spatial data and might even be able to make this on a more granular level. Some cool ideas to visualize this)Variables Involved: Cleaning: Modeling/Computation: Graphs: How do players ages affect their statistics and what is the ideal age for their primes (If there is one of course)?Variables Involved: Cleaning: Modeling/Computation: Graphs: How can we make an effective scoring algorithm that can score players based on their roles and their performance stats (ex. score a Shooting Guard based on their % of successful dunks).Variables Involved: Cleaning: Modeling/Computation: Graphs: Make another algorithm that determines the best team setup and rotations based on the scoring algorithm.Variables Involved: Cleaning: Modeling/Computation: Graphs:What player has the best point to minute ratio and has the best production time on court per minute?Variables Involved: Cleaning: Modeling/Computation: Graphs: Computer Science Engineering & Technology Python Programming I&C SCI X426.49 Share QuestionEmailCopy link Comments (0)