用python画篮球场_Python可视化分析——科比整个职业生涯的投篮点分布

import pandas as pd

import numpy as np

from matplotlib import pyplot as plt

# 导入数据

file_path = "C:/Users/pc/Desktop/kobe_data.csv"

df = pd.read_csv(file_path)

print(df.shape)

df.head(10)

(30697, 25)

action_type

combined_shot_type

game_event_id

game_id

lat

loc_x

loc_y

lon

minutes_remaining

period

...

shot_type

shot_zone_area

shot_zone_basic

shot_zone_range

team_id

team_name

game_date

matchup

opponent

shot_id

0

Jump Shot

Jump Shot

10

20000012

33.9723

167

72

-118.1028

10

1

...

2PT Field Goal

Right Side(R)

Mid-Range

16-24 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

1

1

Jump Shot

Jump Shot

12

20000012

34.0443

-157

0

-118.4268

10

1

...

2PT Field Goal

Left Side(L)

Mid-Range

8-16 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

2

2

Jump Shot

Jump Shot

35

20000012

33.9093

-101

135

-118.3708

7

1

...

2PT Field Goal

Left Side Center(LC)

Mid-Range

16-24 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

3

3

Jump Shot

Jump Shot

43

20000012

33.8693

138

175

-118.1318

6

1

...

2PT Field Goal

Right Side Center(RC)

Mid-Range

16-24 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

4

4

Driving Dunk Shot

Dunk

155

20000012

34.0443

0

0

-118.2698

6

2

...

2PT Field Goal

Center(C)

Restricted Area

Less Than 8 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

5

5

Jump Shot

Jump Shot

244

20000012

34.0553

-145

-11

-118.4148

9

3

...

2PT Field Goal

Left Side(L)

Mid-Range

8-16 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

6

6

Layup Shot

Layup

251

20000012

34.0443

0

0

-118.2698

8

3

...

2PT Field Goal

Center(C)

Restricted Area

Less Than 8 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

7

7

Jump Shot

Jump Shot

254

20000012

34.0163

1

28

-118.2688

8

3

...

2PT Field Goal

Center(C)

Restricted Area

Less Than 8 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

8

8

Jump Shot

Jump Shot

265

20000012

33.9363

-65

108

-118.3348

6

3

...

2PT Field Goal

Left Side(L)

In The Paint (Non-RA)

8-16 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

9

9

Running Jump Shot

Jump Shot

294

20000012

33.9193

-33

125

-118.3028

3

3

...

2PT Field Goal

Center(C)

In The Paint (Non-RA)

8-16 ft.

1610612747

Los Angeles Lakers

2000-10-31

LAL @ POR

POR

10

10 rows × 25 columns

print(df.columns)

# 关键数据 loc_x、loc_y(出手位置坐标)和 shot_made_flag(是否投中)这三列。

print(df["shot_made_flag"].unique())

Index(['action_type', 'combined_shot_type', 'game_event_id', 'game_id', 'lat',

'loc_x', 'loc_y', 'lon', 'minutes_remaining', 'period', 'playoffs',

'season', 'seconds_remaining', 'shot_distance', 'shot_made_flag',

'shot_type', 'shot_zone_area', 'shot_zone_basic', 'shot_zone_range',

'team_id', 'team_name', 'game_date', 'matchup', 'opponent', 'shot_id'],

dtype='object')

[nan 0. 1.]

# 去除空值行

kobe = df[pd.notnull(df["shot_made_flag"])]

print(kobe.shape)

(25697, 25)

# 动作类型

print(kobe.action_type.unique())

print(kobe.combined_shot_type.unique())

# 投篮类型 2分/3分

print(kobe.shot_type.unique())

# 投篮类型次数统计

print(kobe.shot_type.value_counts())

['Jump Shot' 'Driving Dunk Shot' 'Layup Shot' 'Running Jump Shot'

'Reverse Dunk Shot' 'Slam Dunk Shot' 'Driving Layup Shot'

'Turnaround Jump Shot' 'Reverse Layup Shot' 'Tip Shot'

'Running Hook Shot' 'Alley Oop Dunk Shot' 'Dunk Shot'

'Alley Oop Layup shot' 'Running Dunk Shot' 'Driving Finger Roll Shot'

'Running Layup Shot' 'Finger Roll Shot' 'Fadeaway Jump Shot'

'Follow Up Dunk Shot' 'Hook Shot' 'Turnaround Hook Shot' 'Jump Hook Shot'

'Running Finger Roll Shot' 'Jump Bank Shot' 'Turnaround Finger Roll Shot'

'Hook Bank Shot' 'Driving Hook Shot' 'Running Tip Shot'

'Running Reverse Layup Shot' 'Driving Finger Roll Layup Shot'

'Fadeaway Bank shot' 'Pullup Jump shot' 'Finger Roll Layup Shot'

'Turnaround Fadeaway shot' 'Driving Reverse Layup Shot'

'Driving Slam Dunk Shot' 'Step Back Jump shot' 'Turnaround Bank shot'

'Reverse Slam Dunk Shot' 'Floating Jump shot' 'Putback Slam Dunk Shot'

'Running Bank shot' 'Driving Bank shot' 'Driving Jump shot'

'Putback Layup Shot' 'Putback Dunk Shot' 'Running Finger Roll Layup Shot'

'Pullup Bank shot' 'Running Slam Dunk Shot' 'Cutting Layup Shot'

'Driving Floating Jump Shot' 'Running Pull-Up Jump Shot' 'Tip Layup Shot'

'Driving Floating Bank Jump Shot']

['Jump Shot' 'Dunk' 'Layup' 'Tip Shot' 'Hook Shot' 'Bank Shot']

['2PT Field Goal' '3PT Field Goal']

2PT Field Goal 20285

3PT Field Goal 5412

Name: shot_type, dtype: int64

# 职业生涯赛季

kobe['season'].unique()

# kobe['season'] = kobe['season'].apply(lambda x: int(x.split('-')[1]) )

# kobe['season'].unique()

array(['2000-01', '2001-02', '2002-03', '2003-04', '2004-05', '2005-06',

'2006-07', '2007-08', '2008-09', '2009-10', '2010-11', '2011-12',

'2012-13', '2013-14', '2014-15', '2015-16', '1996-97', '1997-98',

'1998-99', '1999-00'], dtype=object)

# 所属球队ID和队名，职业生涯都效力于湖人队

print(kobe['team_id'].unique())

print(kobe['team_name'].unique())

[1610612747]

['Los Angeles Lakers']

# 球队对阵及日期表

vsdf = pd.DataFrame({'matchup':kobe.matchup, 'opponent':kobe.opponent, 'game_date':kobe.game_date})

matchup opponent game_date

1 LAL @ POR POR 2000-10-31

2 LAL @ POR POR 2000-10-31

3 LAL @ POR POR 2000-10-31

4 LAL @ POR POR 2000-10-31

5 LAL @ POR POR 2000-10-31

6 LAL @ POR POR 2000-10-31

8 LAL @ POR POR 2000-10-31

9 LAL @ POR POR 2000-10-31

10 LAL @ POR POR 2000-10-31

11 LAL vs. UTA UTA 2000-11-01

#plt.subplot(211) first is raw second Column

alpha = 0.02

plt.figure(figsize=(16,10))

# loc_x and loc_y 坐标位置

plt.subplot(121)

plt.scatter(kobe.loc_x, kobe.loc_y, color='#DA70D6', alpha=alpha)

plt.title('loc_x and loc_y')

# lat and lon 经纬度

plt.subplot(122)

plt.scatter(kobe.lon, kobe.lat, color='#FFD700', alpha=alpha)

plt.title('lat and lon')

Text(0.5, 1.0, 'lat and lon')

# 出手区域数据分布

gs = kobe.groupby('shot_zone_area')

print (kobe['shot_zone_area'].value_counts())

print (len(gs))

Center(C) 11289

Right Side Center(RC) 3981

Right Side(R) 3859

Left Side Center(LC) 3364

Left Side(L) 3132

Back Court(BC) 72

Name: shot_zone_area, dtype: int64

6

# 根据不同区域绘制散点图

import matplotlib.cm as cm

plt.figure(figsize=(20,10))

def scatter_plot_by_category(feat):

alpha = 0.1

gs = kobe.groupby(feat)

cs = cm.rainbow(np.linspace(0, 1, len(gs)))

for g, c in zip(gs, cs):

plt.scatter(g[1].loc_x, g[1].loc_y, color=c, alpha=alpha)

# shot_zone_area

plt.subplot(131)

scatter_plot_by_category('shot_zone_area')

plt.title('shot_zone_area')

# shot_zone_basic

plt.subplot(132)

scatter_plot_by_category('shot_zone_basic')

plt.title('shot_zone_basic')

# shot_zone_range

plt.subplot(133)

scatter_plot_by_category('shot_zone_range')

plt.title('shot_zone_range')

Text(0.5, 1.0, 'shot_zone_range')

以下篮球场的绘制较为繁杂，参考了 B站素材

from matplotlib import pyplot as plt

from matplotlib.patches import Arc, Circle, Rectangle

def draw_ball_field(color='#20458C', lw=2):

"""

绘制篮球场

"""

# 新建一个大小为(6,6)的绘图窗口

plt.figure(figsize=(12, 12))

# 获得当前的Axes对象ax,进行绘图

ax = plt.gca()

# 对篮球场进行底色填充

lines_outer_rec = Rectangle(xy=(-250, -47.5), width=500, height=470, linewidth=lw, color='#F0F0F0', fill=True)

# 设置篮球场填充图层为最底层

lines_outer_rec.set_zorder(0)

# 将rec添加进ax

ax.add_patch(lines_outer_rec)

# 绘制篮筐,半径为7.5

circle_ball = Circle(xy=(0, 0), radius=7.5, linewidth=lw, color=color, fill=False)

# 将circle添加进ax

ax.add_patch(circle_ball)

# 绘制篮板,尺寸为(60,1)

plate = Rectangle(xy=(-30, -7.5), width=60, height=-1, linewidth=lw, color=color, fill=False)

# 将rec添加进ax

ax.add_patch(plate)

# 绘制2分区的外框线,尺寸为(160,190)

outer_rec = Rectangle(xy=(-80, -47.5), width=160, height=190, linewidth=lw, color=color, fill=False)

# 将rec添加进ax

ax.add_patch(outer_rec)

# 绘制2分区的内框线,尺寸为(120,190)

inner_rec = Rectangle(xy=(-60, -47.5), width=120, height=190, linewidth=lw, color=color, fill=False)

# 将rec添加进ax

ax.add_patch(inner_rec)

# 绘制罚球区域圆圈,半径为60

circle_punish = Circle(xy=(0, 142.5), radius=60, linewidth=lw, color=color, fill=False)

# 将circle添加进ax

ax.add_patch(circle_punish)

# 绘制三分线的左边线

three_left_rec = Rectangle(xy=(-220, -47.5), width=0, height=140, linewidth=lw, color=color, fill=False)

# 将rec添加进ax

ax.add_patch(three_left_rec)

# 绘制三分线的右边线

three_right_rec = Rectangle(xy=(220, -47.5), width=0, height=140, linewidth=lw, color=color, fill=False)

# 将rec添加进ax

ax.add_patch(three_right_rec)

# 绘制三分线的圆弧,圆心为(0,0),半径为238.66,起始角度为22.8,结束角度为157.2

three_arc = Arc(xy=(0, 0), width=477.32, height=477.32, theta1=22.8, theta2=157.2, linewidth=lw, color=color, fill=False)

# 将arc添加进ax

ax.add_patch(three_arc)

# 绘制中场处的外半圆,半径为60

center_outer_arc = Arc(xy=(0, 422.5), width=120, height=120, theta1=180, theta2=0, linewidth=lw, color=color, fill=False)

# 将arc添加进ax

ax.add_patch(center_outer_arc)

# 绘制中场处的内半圆,半径为20

center_inner_arc = Arc(xy=(0, 422.5), width=40, height=40, theta1=180, theta2=0, linewidth=lw, color=color, fill=False)

# 将arc添加进ax

ax.add_patch(center_inner_arc)

# 绘制篮球场外框线,尺寸为(500,470)

lines_outer_rec = Rectangle(xy=(-250, -47.5), width=500, height=470, linewidth=lw, color=color, fill=False)

# 将rec添加进ax

ax.add_patch(lines_outer_rec)

return ax

axs = draw_ball_field(color='#20458C', lw=2)

# 设置坐标轴范围

axs.set_xlim(-250, 250)

axs.set_ylim(422.5, -47.5)

# 消除坐标轴刻度

axs.set_xticks([])

axs.set_yticks([])

# 添加备注信息

# plt.annotate('By ohou', xy=(100, 160), xytext=(178, 418))

made = kobe[kobe['shot_made_flag'] == 1]

miss = kobe[kobe['shot_made_flag'] == 0]

# 绘制散点图

axs.scatter(x=miss['loc_x'], y=miss['loc_y'], s=20, marker='x', color='orange')

axs.scatter(x=made['loc_x'], y=made['loc_y'], s=20, marker='o', edgecolors='#3A7711', color="#6B8E23", linewidths=2)

plt.show()

未完待续……