第1关：投篮位置
import matplotlib.pyplot as plt
import pandas as pd
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("Task1/data.csv")
data=data.dropna(axis=0)
loc_x=data['loc_x']
loc_y=data['loc_y']
lat=data['lat']
lon=data['lon']
plt.figure(figsize=(10,10))
plt.subplot(1,2,1)
plt.scatter(loc_x,loc_y,alpha=0.02,c='b')
plt.title('loc_x and loc_y')
plt.subplot(1,2,2)
plt.scatter(lon,lat,alpha=0.02,c='g')
plt.title('lat and lon')
plt.savefig('Task1/img/T1.png')
# ********* End *********#
第2关：射击距离
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("Task1/data.csv")
data=data.dropna(axis=0)
loc_x=data['loc_x']
loc_y=data['loc_y']
dist=(loc_x**2+loc_y**2)**0.5
shot_distance=data['shot_distance']
plt.figure(figsize=(5,5))
plt.scatter(dist,shot_distance)
plt.title('dist and shot_distance')
plt.savefig('Task2/img/T1.png')
# ********* End *********#
第3关：射击区范围
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.cm as cm
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")
cmap = plt.cm.rainbow
norm = matplotlib.colors.Normalize()
plt.figure(figsize=(10,10))
plt.subplot(2,1,1)
data1=data
x=data1["shot_made_flag"].groupby(data1["shot_zone_range"]).mean()
x=pd.DataFrame([x.index,x.values]).T
data1=pd.merge(data1,x,left_on="shot_zone_range",right_on=0)
plt.scatter(x=data1["lon"],y=data1["lat"],c=cmap(norm(list(data1[1].values))))
plt.ylim(33.7,34.0883)
plt.subplot(2,1,2)
d=data["shot_zone_range"].groupby(data["shot_zone_range"]).count()
d=pd.DataFrame([d.index,d.values]).T
d.sort_values(by=[1],ascending=False,inplace=True)
c=[]
for i in d[0]:
c.append(data1[data1["shot_zone_range"]==i][1].head(1).values[0])
plt.bar(d[0],d[1],color=cmap(norm(c)))
plt.savefig("Task4/img/T1.png")
plt.show()
# ********* End *********#
第4关：射击区
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.cm as cm
pd.set_option('display.max_columns', 1000)
pd.set_option('display.width', 1000)
pd.set_option('display.max_colwidth', 1000)
def student():
c={"Center(C)":"goldenrod","Right Side Center(RC)":"cornflowerblue","Right Side(R)":"fuchsia","Left Side Center(LC)":"limegreen","Left Side(L)":"turquoise","Back Court(BC)":"red"}
# ********* Begin *********#
plt.figure(figsize=(10,10))
data=pd.read_csv("./data.csv")
plt.subplot(2,1,1)
data1=data
x=data1["shot_made_flag"].groupby(data1["shot_zone_area"]).mean()
x=pd.DataFrame([x.index,x.values]).T
data1=pd.merge(data1,x,left_on="shot_zone_area",right_on=0)
data2=pd.DataFrame([c.keys(),c.values()]).T
data1=pd.merge(data1,data2,left_on="shot_zone_area",right_on=0)
plt.scatter(x=data1["lon"],y=data1["lat"],color=data1["1_y"])
plt.ylim(33.7,34.0883)
plt.subplot(2,1,2)
d=data["shot_zone_area"].groupby(data["shot_zone_area"]).count()
d=pd.DataFrame([d.index,d.values]).T
d.sort_values(by=[1],ascending=False,inplace=True)
plt.bar(d[0],d[1],color=c.values())
plt.xticks(rotation=45)
plt.savefig("Task5/img/T1.png")
plt.show()
# ********* End *********#
第5关：具体投篮区域
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.cm as cm
pd.set_option('display.max_columns', 1000)
pd.set_option('display.width', 1000)
pd.set_option('display.max_colwidth', 1000)
def student():
c={"Mid-Range":"cornflowerblue","Restricted Area":"fuchsia","Above the Break 3":"tomato","In The Paint (Non-RA)":"limegreen","Right Corner 3":"green","Back Court(BC)":"fuchsia","Left Corner 3":"lime","Backcourt":"tan"}
# ********* Begin *********#
plt.figure(figsize=(10,10))
data=pd.read_csv("./data.csv")
plt.subplot(2,1,1)
data1=data
x=data1["shot_made_flag"].groupby(data1["shot_zone_basic"]).mean()
x=pd.DataFrame([x.index,x.values]).T
data1=pd.merge(data1,x,left_on="shot_zone_basic",right_on=0)
data2=pd.DataFrame([c.keys(),c.values()]).T
data1=pd.merge(data1,data2,left_on="shot_zone_basic",right_on=0)
plt.scatter(x=data1["lon"],y=data1["lat"],color=data1["1_y"])
plt.ylim(33.7,34.0883)
plt.subplot(2,1,2)
d=data["shot_zone_area"].groupby(data["shot_zone_basic"]).count()
d=pd.DataFrame([d.index,d.values]).T
d.sort_values(by=[1],ascending=False,inplace=True)
plt.bar(d[0],d[1],color=c.values())
plt.xticks(rotation=45)
plt.savefig("Task6/img/T1.png")
plt.show()
# ********* End *********#
第6关：投篮准确度
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.cm as cm
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.subplot(212)
data1=data[["lat","lon","shot_zone_range","shot_made_flag"]]
x=data1["shot_made_flag"].groupby(data1["shot_zone_range"]).mean()
x=pd.DataFrame([x.index,x.values]).T
data1=pd.merge(data1,x,left_on="shot_zone_range",right_on=0)
d=plt.scatter(x=data1["lon"],y=data1["lat"],c=data1[1])
plt.colorbar(d,)
plt.ylim((33.7, 34.0883))
plt.subplot(222)
data2=data[["lat","lon","shot_zone_area","shot_made_flag"]]
da=data2["shot_made_flag"].groupby(data2["shot_zone_area"]).mean()
d=pd.DataFrame([da.index,da.values]).T
data2=pd.merge(data2,d,left_on="shot_zone_area",right_on=0)
plt.scatter(x=data2["lon"],y=data2["lat"],c=data2[1])
plt.ylim((33.7, 34.0883))
plt.subplot(221)
data3=data[["lat","lon","shot_zone_basic","shot_made_flag"]]
da=data3["shot_made_flag"].groupby(data3["shot_zone_basic"]).mean()
da=pd.DataFrame([da.index,da.values]).T
data3=pd.merge(data3,da,left_on="shot_zone_basic",right_on=0)
plt.scatter(x=data3["lon"],y=data3["lat"],c=data3[1])
plt.ylim((33.7, 34.0883))
plt.savefig("Task7/img/T1.png")
plt.show()
# ********* End *********#
