labels = df_grouped1.loc["male"].index #male的索引值其实就是Pclass的值1、2、3 #创建figure和axes对象 fig,ax = plt.subplots(figsize=(8,5),dpi=80) #在子图对象上画条形图 ax.barh(np.arange(len(female)),female,label="female",height=0.5) ax.barh(np.arange(len(male)),-male,label=...
import datetime # my fake data dates = np.array([datetime.datetime(2000,1,1) + datetime.timedelta(days=i) for i in range(365*5)]) data = np.sin(np.arange(365*5)/365.0*2*np.pi - 0.25*np.pi) + np.random.rand(365*5) /3 # creates fig with 2 subplots fig = plt.figure(figs...
np.random.seed(randomSeed) def getBatch(self, batchSize, isTrain): if isTrain: index = np.random.choice(len(self.trainImage), batchSize, True) return self.trainImage[index], self.trainLabel[index] else: index = np.random.choice(len(self.testImage), batchSize, True) return self.testI...
time_stamps = np.linspace(0, 240, 13) # Define the labels time_labels = ["00:00", "02:00", "04:00", "06:00", "08:00", "10:00", "12:00", "14:00", "16:00", "18:00", "20:00", "22:00", "24:00"] plt.xlim(0, 240) # Defines the limit of your x-axis pl...
features = np.arange(0, 100, dtype=np.int32)## (100,)labels = np.zeros(100, dtype=np.int32)#(100,)data= tf.data.Dataset.from_tensor_slices((features, labels))#创建数据集data = data.repeat()#无限期地补充数据data = data.shuffle(buffer_size=100)#打乱数据data = data.batch(batch_...
百度试题 结果1 题目x=np.arange(6),x表示x从2到6(包括6)的切片()判断题] 相关知识点: 试题来源: 解析 正确 反馈 收藏
import numpy as np x=np.arange(3,10) print(x) 以上三句的输出结果是 A.[3 4 5 6 7 8 9]B.[3 4 5 6 7 8 9 10]C.[4 5 6 7 8 9 10]D.[4 5 6 7 8 9]相关知识点: 试题来源: 解析 A.[3 4 5 6 7 8 9] 反馈 收藏 ...
women_means=[25,32,34,20,25]x=np.arange(len(labels))# the label locationswidth=0.35# the width of the barsfig,ax=plt.subplots()rects1=ax.bar(x-width/2,men_means,width,label='Men')rects2=ax.bar(x+width/2,women_means,width,label='Women')ax.set_xticks(x)ax.set_xticklabels([...
import numpy as np x = np.arange(12).reshape(4, 3) display(x) rows = np.array([[0,0],[3,3]]) cols = np.array([[0,2],[0,2]]) display(x[rows,cols]) print(x[[0, 3],][:,[0, 2]])
ind=np.arange(len(men_means)) width=0.2 fig=plt.figure() ax=fig.add_subplot(111) ax.bar(ind-width/2,men_means,width,label='男生平均成绩') ax.bar(ind+0.2,women_means,width,label='女生平均成绩') ax.set_title('高二各班男生、女生英语平均成绩') ...