一、散点图
from matplotlib import pyplot as plt
from matplotlib import font_manager
y_3 = [11,17,16,11,12,11,12,6,6,7,8,9,12,15,14,17,18,21,16,17,20,14,15,15,15,19,21,22,22,22,23]
y_10 = [26,26,28,19,21,17,16,19,18,20,20,19,22,23,17,20,21,20,22,15,11,15,5,13,17,10,11,13,12,13,6]
plt.figure(figsize=(20, 8), dpi=80)
my_font = font_manager.FontProperties(fname=r"G:\Python_Learning\untitled\test\simsun.ttc") # 调取中文字体
x_3 = range(1, 32)
x_10 = range(51, 82)
plt.scatter(x_3, y_3, label='3月份')
plt.scatter(x_10, y_10, label='10月份')
plt.legend(prop=my_font, loc="upper left")
_x = list(x_3) + list(x_10)
_xtick_labels = ["3月{}日".format(i) for i in x_3]
_xtick_labels += ["10月{}日".format(i - 50) for i in x_10]
plt.xticks(_x[::3], _xtick_labels[::3], fontproperties=my_font, rotation=45)
plt.xlabel("日期", fontproperties=my_font) # 贴轴标题
plt.ylabel("温度℃", fontproperties=my_font)
plt.title("北京2016年3,10月份白天的最高气温散点图", fontproperties=my_font)
plt.show()
二、条形图
（1）一般条形图
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname=r"G:\Python_Learning\untitled\test\simsun.ttc") # 调取中文字体
plt.figure(figsize=(20, 8), dpi=80) # 调图表大小
a = ["战狼2","速度与激情8","功夫瑜伽","西游伏妖篇","变形金刚5：\n最后的骑士","摔跤吧！爸爸","加勒比海盗5：\n死无\
对证","金刚：骷髅岛","极限特工：\n终极回归","生化危机6：\n终章","乘风破浪","神偷奶爸3","智取威虎山","大闹天竺","金\
刚狼3：\n殊死一战","蜘蛛侠：\n英雄归来","悟空传","银河护卫队2","情圣","新木乃伊",]
b=[56.01,26.94,17.53,16.49,15.45,12.96,11.8,11.61,11.28,11.12,10.49,10.3,8.75,7.55,7.32,6.99,6.88,6.86,6.58,6.23]
_x = range(len(a))
_y = b
plt.bar(_x, _y, width=0.2, color='orange')
plt.xticks(_x, a, fontproperties=my_font, rotation=90)
plt.show()
（2）横向条形图
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname=r"G:\Python_Learning\untitled\test\simsun.ttc") # 调取中文字体
plt.figure(figsize=(20, 8), dpi=80) # 调图表大小
a = ["战狼2","速度与激情8","功夫瑜伽","西游伏妖篇","变形金刚5：最后的骑士","摔跤吧！爸爸","加勒比海盗5：死无对证","金刚：骷髅岛","极限特工：终极回归","生化危机6：终章","乘风破浪","神偷奶爸3","智取威虎山","大闹天竺","金刚狼3：殊死一战","蜘蛛侠：英雄归来","悟空传","银河护卫队2","情圣","新木乃伊",]
b = [56.01,26.94,17.53,16.49,15.45,12.96,11.8,11.61,11.28,11.12,10.49,10.3,8.75,7.55,7.32,6.99,6.88,6.86,6.58,6.23]
plt.barh(range(len(a)), b, height=0.3, color='orange')
plt.yticks(range(len(a)), a, fontproperties=my_font)
plt.show()
（3）条形图应用
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname=r"G:\Python_Learning\untitled\test\simsun.ttc") # 调取中文字体
plt.figure(figsize=(20, 8), dpi=80) # 调图表大小
a = ["猩球崛起3：终极之战","敦刻尔克","蜘蛛侠：英雄归来","战狼2"]
b_16 = [15746,312,4497,319]
b_15 = [12357,156,2045,168]
b_14 = [2358,399,2358,362]
x_14 = list(range(len(a)))
x_15 = [i + 0.2 for i in x_14]
x_16 = [i + 0.2 for i in x_15]
plt.bar(range(len(a)), b_14, width=0.2, color='purple', label="9月14日")
plt.bar(x_15, b_15, width=0.2, color='yellow', label="9月15日")
plt.bar(x_16, b_16, width=0.2, color='blue', label="9月16日")
plt.legend(prop=my_font)
plt.ylabel("票房/万元", fontproperties=my_font)
plt.xticks(x_15, a, fontproperties=my_font)
plt.show()
（4）条形图伪直方图
因为直方图的代码函数是处理未经过处理的数据的。但是如果要求显示直方图连在一起的形式，可以用条形图完成这一点。
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname=r"G:\Python_Learning\untitled\test\simsun.ttc") # 调取中文字体
plt.figure(figsize=(20, 8), dpi=80) # 调图表大小
interval = [0,5,10,15,20,25,30,35,40,45,60,90]
width = [5,5,5,5,5,5,5,5,5,15,30,60]
quantity = [836,2737,3723,3926,3596,1438,3273,642,824,613,215,47]
_x = [i-0.5 for i in range(len(quantity)+1)] # -0.5是挪移位置，+1是显示最后一个横坐标
plt.bar(range(len(quantity)), quantity, width=1)
plt.xticks(_x, interval+[150], fontproperties=my_font) # 显示最后一个横坐标
plt.grid(True, linestyle="-.", alpha=0.5) # 显示网络，透明度为0.5
plt.show()
三、直方图
（1）适用条件
未经处理的数据。
（2）直方图例子
from matplotlib import pyplot as plt
from matplotlib import font_manager
my_font = font_manager.FontProperties(fname=r"G:\Python_Learning\untitled\test\simsun.ttc") # 调取中文字体
plt.figure(figsize=(20, 8), dpi=80) # 调图表大小
a = [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]
bin_width = 3 # 设置组距为3,数字3以内为一组
num_bins = int((max(a)-min(a))/bin_width) # 组数量,在python绘图种要让它等于整数，不然绘图偏移
print(num_bins)
plt.hist(a, num_bins, density=True) # density 表示其为频率直方分布图
plt.xticks(list(range(min(a), max(a)+3))[::bin_width], rotation=45) # range后面取不到，所以加一个bin_width
plt.grid(True, linestyle="-.", alpha=0.5) # 显示网络，透明度为0.5
plt.show()
四、更多资源
https://plotly.com/python/
https://echarts.apache.org/examples/zh/index.html#chart-type-line