data = [[18.9,10.4],[21.3,8.7],[19.5,11.6],[20.5,9.7],[19.9,9.4],[22.3,11],[21.4,10.6],[9,9.4],[10.4,9],[9.3,11.3],[11.6,8.5],[11.8,10.4],[10.3,10],[8.7,9.5],[14.3,17.2],[14.1,15.5],[14,16.5],[16.5,17.7],[15.1,17.3],[16.4,15],[15.7,18]]

data=[77,70,72,89,89,70,90,87,94,63,81,99,94,80,95,67,65,88,60,67,85,88,87,75,62,65,95,62,61,93,30]

r = [1,2,3,4,5] #极径

theta=[0.0,1.5707963267948966,3.141592653589793,4.71238898038469,6.283185307179586] #角度

year=range(2005,2020)

height=[157,160,162,163,167,170,176,175,174,179,182,182,182,182.182,183]

name_list = ['语文','数学','英语']

c1 = [81.4,83,87.1]

c2 = [85.6,87.4,90]

c3 = [78,81.2,86.1]

# 中文支持
plt.rcParams['font.sans-serif'] = ['SimHei']

# 正常显示负号
plt.rcParams['axes.unicode_minus'] = False

# 修改线条样式
plt.rcParams['lines.linewidth']=5   #线条宽
plt.rcParams['lines.color']='red'   #线条颜色
plt.rcParams['lines.linestyle']='--' #线条样式

线条样式的有效值有：

'-', '--', '-.', ':', 'solid', 'dashed', 'dashdot', 'dotted', 'none', ' ', ''

中文字体显示设置的另一个参考：

https://www.runoob.com/numpy/numpy-matplotlib.html

x=[22,22,23,24,25,25,26,27,28,29,30,30,32,32,32,33,34,34,35,36,37,38,38,39,40,42,43,43,45,45,46,48,48,48,50,52,56,57,60,62]
y=[176,186,164,177,183,194,180,179,190,170,168,192,173,178,181,186,177,187,180,195,179,186,187,190,182,184,176,178,164,185,181,175,173,172,172,169,168,182,188,174]
z=[70, 220, 50, 170, 210, 270, 150, 150, 360, 150, 150, 200, 150, 170, 170, 160, 180, 460, 480, 480, 490, 300, 300, 250, 300, 250, 350, 180, 100, 250, 160, 170, 160, 180, 150, 150, 130, 180, 100, 160]

QAQ

import matplotlib.pyplot as plt

import numpy as np

%matplotlib inline

plt.rcParams['font.sans-serif']=['SimHei']

ch=[72,80,66,77,92]

math=[62,92,72,75,88]

eng=[76,81,73,75,80]

plt.bar(绘制的轴，数据，数据起始绘制位置是bottom=，颜色color=，数据标签label=)
plt.ylim(0,300) #y的范围是0-300
plt.legend(loc='upper right') #在右上添加标签
plt.grid(axis='y', color='gray', linestyle=':', linewidth=2) #添加背景的虚线

常用的配置

snow_area=[83.1,350.7,5903.3,2716.2,4446.5,2975,4615.1,8543,137.1,5073,980.8,5603.9,829.8,3367.1,7166.3,9521.1,393 

1.4,4479.5,2077.3,2594.3,289.3,1260.9,4649.5,1816.5,3255,176.2,2548.7,1966.9,159.4,579.9,2297.1] 

total_output=[52.3,194.2,3321.9,1232.9,2492.3,2017.1,3601.6,5435.2,98.6,3360.6,656,3252.5,496.1,2029.9,4505.2,5777,2 

428.5,2805.2,1170.8,1420.6,149.2,806.2,2846.6,855.5,1567.7,99.8,1114.2,883.1,61.1,331.8,1474.81]

per_hectare=[6296,5538,5627,4539,5605,6780,7804,6362,7190,6624,6689,5804,5978,6028,6287,6068,6177,6262,5636,54 

76,5157,6394,6122,4710,4816,5663,4371,4490,3832,5721,6420]

area=['北京','天津','河北','山西','内蒙古','辽宁','吉林','黑龙江','上海','江苏','浙江','安徽','福建','江西','山东','河南','湖北 

','湖南','广东','广西','海南','重庆','四川','贵州','云南','西藏','陕西','甘肃','青海','宁夏','新疆']

data1=[......]

data2=[......]

data3=[......]

name=[......]

# 绘制柱状图

plt.figure(figsize=(20,10))    #调整画布大小，以免文字堆积在一起

plt.bar(range(1,len(data1)+1),data1)

plt.xticks(range(1,len(data1)+1),name)

# 设置标题、标签

plt.show()

# 绘制饼图

plt.figure(figsize=(15,15))

plt.pie(data1,labels=name,autopct="%1.1f%%")    # 设置标签和百分比符号

# 设置标题

plt.show()

# 绘制气泡图

data3=[item/20 for item in data3]    # 调整data的大小，以免气泡图的气泡过大或过小

plt.scatter(data1,data2,s=data3)

# 设置标题、标签

data1=[......]

data2=[......]

data3=[......]

name=[......]

# 计算最大值，使用python的内置函数max（）

data1_max=max(data1)

data2_max=max(data2)

data3_max=max(data3)

# 计算均值，统计数据的总量并除以其数量可得到其均值

data1_mean=sum(data1)/len(data1)

data2_mean=sum(data2)/len(data2)

data3_mean=sum(data3)/len(data3)

# 计算中位数，对数据进行排序，如果数据长度为奇数，取中间的那个数，如果数据长度为偶数，取中间两个数的均值

def median(List):

    List=sorted(List)

    if len(List)%2==1:
        return List[len(List)//2]

    else:

        return (List[len(List)//2]+List[len(List)//2-1])/2

data1_median=median(data1)

data2_median=median(data2)

data3_median=median(data3)

# 计算标准差，需要提前导入math模块

def stdev(List):

    mean=sum(List)/len(List)

    sum=0

    for item in List:

        sum+=(item-mean)**2

    sum/=len(List)

    return math.sqrt(sum)

data1_stdev=stedv(data1)

data2_stdev=stedv(data2)

data3_stdev=stedv(data3)

# 三个维度的数据

x=[......]

y=[......]

z=[......]

plt.scatter(x,y,s=z)    # 气泡大小设置为z，能够同时显示三个维度之间的关系

name_list=['name1','name2',name3']

data1=[......]

data2=[......]

data3=[......]

width=0.4    # 每个柱状图的宽度

x1=[1,3,5]

plt.bar(x1,c1,label='name1',fc='r',width=width)

x2=[......]    # x1加上宽度

plt.bar(x2,c1,label='name2',fc='g',width=width)

x3=[......]    # x2加上宽度

plt.bar(x3,c1,label='name3',fc='b',width=width)

plt.xticks(x2,name_list)    # 在x2的底部显示出name

plt.legend()    # 将每个name对应的颜色体现在图像中

# 添加标题、xy轴标签

n=5

number=['1','2','3','4','5']

data1=[......]

data2=[......]

data3=[......]

data4=[data2[i]+data1[i] for i in range(5)]    #data4是data1加上data2的数据，作为data3的底部

x=np.arange(n)

plt.bar(x,data1,color='r',label='标签1')

plt.bar(x,data1,bottom=data1,color='g',label='标签2')    # bottom的参数是设置底部数据

plt.bar(x,data3,bottom=data4,color='c',label='标签3')

plt.ylim(0,300)    #这里设置y轴的区间

plt.title(标题）

plt.legend(loc='upper right')

plt.grid(axis='y',color='gray',linestyle=':',linewidth=2)

plt.xticks(x,number)

plt.xlabel(x轴标签）

x=[1,2,3]

name=['name1','name2','name3']

y=[data1,data2,data3]

plt.bar(x,y)

plt.title(标题）    # 设置标题

plt.xlabel(x轴标签）    # 设置x轴标签

plt.ylabel(y轴标签）    # 设置y轴标签

plt.xticks(x,name)    # 将x轴上的数字替换成对应的名字

for i in range(1,len(name)+1):

    plt.text(i,y[i-1]+1,y[i-1])    # 在固定位置添加文本，text的参数分别为x，y，数据。

plt.rcParams['font.sans-serif']=['SimHei']#中文支持
plt.rcParams['axes.unicode_minus']=False #正常显示负号
plt.rcParams['lines.linewidth']=5 #设置线条宽度
plt.rcParams['lines.color']='red' #设置线条颜色
plt.rcParams['lines.linestyle']='-' #设置线条样式