科比投篮预测，可视化与探索性数据分析（二）

第一关：

import pandas as pd
import matplotlib.pyplot as plt
pd.set_option('display.max_columns', 1000)
pd.set_option('display.width', 1000)
pd.set_option('display.max_colwidth', 1000)


def student():
    # ********** Begin ********** #
    data = pd.read_csv("./data.csv").dropna()
    plt.figure(figsize=(10,10))
    d = data["shot_made_flag"].groupby(data["action_type"]).mean()
    x = []
    y = []
    for i in d.index:
        if list(data["action_type"].values).count(i)>20:
            y.append(i)
            x.append(d[i])
    asd = pd.DataFrame([x,y]).T
    asd.sort_values(by = [0],inplace = True)
    plt.scatter(asd[0], asd[1])
    plt.title("Accuracy by shot type")
    plt.xlabel("Accuracy")
    plt.savefig("Task4/img/T1.png")
    
    # ********** End ********** #

第二关：

import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
pd.set_option('display.max_columns', 1000)
pd.set_option('display.width', 1000)
pd.set_option('display.max_colwidth', 1000)
def student():
    # ********** Begin ********** #
    data = pd.read_csv("./data.csv")
    plt.figure(figsize=(16,8))
    plt.subplot(1,3,1)
    x = data["shot_made_flag"].groupby(data["season"])