Need help with stats/data science question in python, thank you! NFL Play-by-play Modeling and Classification In [1]

Need help with stats/data science question in python, thank you!

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NFL Play-by-play Modeling and Classification In [1] import os import pandas as pd import numpy as np import seaborn as sb import statsmodels.api as sm import sklearn. tree as tr import sklearn.ensemble as ens import sklearn. I inear_model as slm from sklearn.model_selection import train_test_split import matplotlib.pyplot as plt. pd.set_option('display.max_colwidth', pd.set_option('mode.chained_assignment', None) None) In [3] base = "/scratch/stat s206s23_class_root/stat s206s23_class/materials/data" nfl = pd. read_csv (os.path.join(base, "NFL_play_by_play_2022.csv.gz")) nfl.shape Out [3] (50147, 340) These data record play-by-play information for all games in the 2022 National Football League (NFL) season. These data were downloaded using the nf Iverse package for the R programming language (another statistics and data science environment), lightly edited, and saved in a tabular format for us to use in Python. There are many measurements for each play, some of which are computed values from nf Iverse. Here's a brief list using the data dictionary. NFL Play-by-play Modeling and Classification In [1] import os import pandas as pd import numpy as np import seaborn as sb import statsmodels.api as sm import sklearn. tree as tr import sklearn.ensemble as ens import sklearn. I inear_model as slm from sklearn.model_selection import train_test_split import matplotlib.pyplot as plt. pd.set_option('display.max_colwidth', pd.set_option('mode.chained_assignment', None) None) In [3] base = "/scratch/stat s206s23_class_root/stat s206s23_class/materials/data" nfl = pd. read_csv (os.path.join(base, "NFL_play_by_play_2022.csv.gz")) nfl.shape Out [3] (50147, 340) These data record play-by-play information for all games in the 2022 National Football League (NFL) season. These data were downloaded using the nf Iverse package for the R programming language (another statistics and data science environment), lightly edited, and saved in a tabular format for us to use in Python. There are many measurements for each play, some of which are computed values from nf Iverse. Here's a brief list using the data dictionary.