<jupyter_start><jupyter_text>Project<jupyter_code>#imports
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np 
import pylab 
import scipy.stats as stats<jupyter_output><empty_output><jupyter_text>Data<jupyter_code>df = pd.read_csv('understat.com.csv')
df_per_game = pd.read_csv('understat_per_game.csv')
list(df_per_game.columns)
train, validate, test = np.split(df_per_game.samplefrac=1, random_state=42),[int(.6*len(df_per_game)), int(.8*len(df_per_game))])
train
test.describe()
y=test['wins']
y
x=test['scored']
x
# QQ plot
stats.probplot(x, dist="norm", plot=pylab)<jupyter_output><empty_output>
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{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '49333', 'license': 'MIT', 'n_tokens_mistral': 260, 'n_tokens_neox': 254, 'n_words': 40, 'path': 'data science/DIT863 - stat/project/Project.ipynb', 'repo_name': 'ezztherose/notebooks', 'size': '620'}