常见图形种类及其意义：
散点图;
# 需求：探究房屋面积和房屋价格的关系 # 1、准备数据 x = [225.98, 247.07, 253.14, 457.85, 241.58, 301.01, 20.67, 288.64, 163.56, 120.06, 207.83, 342.75, 147.9 , 53.06, 224.72, 29.51, 21.61, 483.21, 245.25, 399.25, 343.35] y = [196.63, 203.88, 210.75, 372.74, 202.41, 247.61, 24.9 , 239.34, 140.32, 104.15, 176.84, 288.23, 128.79, 49.64, 191.74, 33.1 , 30.74, 400.02, 205.35, 330.64, 283.45] # 2、创建画布 plt.figure(figsize=(20, 8), dpi=80) # 3、绘制图像 plt.scatter(x, y) # 4、显示图像 plt.show()
柱状图;
对比每部电影的票房收入：
# 1、准备数据 movie_names = ['雷神3：诸神黄昏','正义联盟','东方快车谋杀案','寻梦环游记','全球风暴', '降魔传','追捕','七十七天','密战','狂兽','其它'] tickets = [73853,57767,22354,15969,14839,8725,8716,8318,7916,6764,52222] # 2、创建画布 plt.figure(figsize=(20, 8), dpi=80) # 3、绘制柱状图 x_ticks = range(len(movie_names)) plt.bar(x_ticks, tickets, color=['b','r','g','y','c','m','y','k','c','g','b']) # 修改x刻度 plt.xticks(x_ticks, movie_names) # 添加标题 plt.title("电影票房收入对比") # 添加网格显示 plt.grid(linestyle="--", alpha=0.5) # 4、显示图像 plt.show()
比较相同天数的票房;
# 1、准备数据 movie_name = ['雷神3：诸神黄昏','正义联盟','寻梦环游记'] first_day = [10587.6,10062.5,1275.7] first_weekend=[36224.9,34479.6,11830] # 2、创建画布 plt.figure(figsize=(20, 8), dpi=80) # 3、绘制柱状图 plt.bar(range(3), first_day, width=0.2, label="首日票房") plt.bar([0.2, 1.2, 2.2], first_weekend, width=0.2, label="首周票房") # 显示图例 plt.legend() # 修改刻度 plt.xticks([0.1, 1.1, 2.1], movie_name) # 4、显示图像 plt.show()
直方图：
直方图和柱状图的对比：
案例电影时长分布：
# 需求：电影时长分布状况 # 1、准备数据 time = [131, 98, 125, 131, 124, 139, 131, 117, 128, 108, 135, 138, 131, 102, 107, 114, 119, 128, 121, 142, 127, 130, 124, 101, 110, 116, 117, 110, 128, 128, 115, 99, 136, 126, 134, 95, 138, 117, 111,78, 132, 124, 113, 150, 110, 117, 86, 95, 144, 105, 126, 130,126, 130, 126, 116, 123, 106, 112, 138, 123, 86, 101, 99, 136,123, 117, 119, 105, 137, 123, 128, 125, 104, 109, 134, 125, 127,105, 120, 107, 129, 116, 108, 132, 103, 136, 118, 102, 120, 114,105, 115, 132, 145, 119, 121, 112, 139, 125, 138, 109, 132, 134,156, 106, 117, 127, 144, 139, 139, 119, 140, 83, 110, 102,123,107, 143, 115, 136, 118, 139, 123, 112, 118, 125, 109, 119, 133,112, 114, 122, 109, 106, 123, 116, 131, 127, 115, 118, 112, 135,115, 146, 137, 116, 103, 144, 83, 123, 111, 110, 111, 100, 154,136, 100, 118, 119, 133, 134, 106, 129, 126, 110, 111, 109, 141,120, 117, 106, 149, 122, 122, 110, 118, 127, 121, 114, 125, 126,114, 140, 103, 130, 141, 117, 106, 114, 121, 114, 133, 137, 92,121, 112, 146, 97, 137, 105, 98, 117, 112, 81, 97, 139, 113,134, 106, 144, 110, 137, 137, 111, 104, 117, 100, 111, 101, 110,105, 129, 137, 112, 120, 113, 133, 112, 83, 94, 146, 133, 101,131, 116, 111, 84, 137, 115, 122, 106, 144, 109, 123, 116, 111,111, 133, 150] # 2、创建画布 plt.figure(figsize=(20, 8), dpi=80) # 3、绘制直方图 distance = 2 group_num = int((max(time) - min(time)) / distance) plt.hist(time, bins=group_num, density=True) # 修改x轴刻度 plt.xticks(range(min(time), max(time) + 2, distance)) # 添加网格 plt.grid(linestyle="--", alpha=0.5) # 4、显示图像 plt.show()
饼图：
显示不同电影的拍片占比;
# 1、准备数据 movie_name = ['雷神3：诸神黄昏','正义联盟','东方快车谋杀案','寻梦环游记','全球风暴','降魔传','追捕','七十七天','密战','狂兽','其它'] place_count = [60605,54546,45819,28243,13270,9945,7679,6799,6101,4621,20105] # 2、创建画布 plt.figure(figsize=(20, 8), dpi=80) # 3、绘制饼图 plt.pie(place_count, labels=movie_name, colors=['b','r','g','y','c','m','y','k','c','g','y'], autopct="%1.2f%%") # 显示图例 plt.legend() plt.axis('equal') # 4、显示图像 plt.show()
总结:
