python使用Matplotlib绘制多种常见图形

import numpy as np 
import matplotlib.pyplot as plt
%matplotlib inline #写了这个就可以不用写plt.show()
plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签
plt.rcParams['axes.unicode_minus']=False #用来正常显示负号
X = np.linspace(0, 2*np.pi,100)# 均匀的划分数据
Y = np.sin(X)
Y1 = np.cos(X)
plt.title("Hello World!!")
plt.plot(X,Y)
plt.plot(X,Y1)

X = np.linspace(0, 2*np.pi,100)  
Y = np.sin(X)
Y1 = np.cos(X)
plt.subplot(211) # 等价于 subplot(2,1,1)  #一个图版画两个图
plt.plot(X,Y)
plt.subplot(212)
plt.plot(X,Y1,color = 'r')

data = [5,25,50,20]
plt.bar(range(len(data)),data)

data = [5,25,50,20]
plt.barh(range(len(data)),data)

data = [[5,25,50,20],
        [4,23,51,17],
        [6,22,52,19]]
X = np.arange(4)
plt.bar(X + 0.00, data[0], color = 'b', width = 0.25,label = "A")
plt.bar(X + 0.25, data[1], color = 'g', width = 0.25,label = "B")
plt.bar(X + 0.50, data[2], color = 'r', width = 0.25,label = "C")
# 显示上面设置的 lable
plt.legend()

data = [[5,25,50,20],
        [4,23,51,17],
        [6,22,52,19]]
X = np.arange(4)
plt.bar(X, data[0], color = 'b', width = 0.25)
plt.bar(X, data[1], color = 'g', width = 0.25,bottom = data[0])
plt.bar(X, data[2], color = 'r', width = 0.25,bottom = np.array(data[0]) + np.array(data[1]))
plt.show()

N = 50
x = np.random.rand(N)
y = np.random.rand(N)
plt.scatter(x, y)

N = 50
x = np.random.rand(N)
y = np.random.rand(N)
colors = np.random.randn(N) # 颜色可以用数值表示
area = np.pi * (15 * np.random.rand(N))**2  #  调整大小
plt.scatter(x, y, c=colors, alpha=0.5, s = area)

N = 50
x = np.random.rand(N)
y = np.random.rand(N)
colors = np.random.randint(0,2,size =50)
plt.scatter(x, y, c=colors, alpha=0.5,s = area)

a = np.random.rand(100)
plt.hist(a,bins= 20)
plt.ylim(0,15)

a = np.random.randn(10000)
plt.hist(a,bins=50)
plt.title("标准正太分布")

x = np.random.randint(20,100,size = (30,3))
plt.boxplot(x)
plt.ylim(0,120)
# 在x轴的什么位置填一个 label，我们这里制定在 1，2，3 位置，写上 A，B，C
plt.xticks([1,2,3],['A','B','C'])
plt.hlines(y = np.median(x,axis = 0)[0] ,xmin =0,xmax=3)

# 设置画布颜色为 blue
fig, ax = plt.subplots(facecolor='blue')
# y 轴数据
data = [[5,25,50,20],
        [4,23,51,17],
        [6,22,52,19]]
X = np.arange(4)
plt.bar(X+0.00, data[0], color = 'darkorange', width = 0.25,label = 'A')
plt.bar(X+0.25, data[1], color = 'steelblue', width = 0.25,label="B")
plt.bar(X+0.50, data[2], color = 'violet', width = 0.25,label = 'C')
ax.set_title("Figure 2")
plt.legend()
 
# 添加文字描述 方法一
W = [0.00,0.25,0.50]
for i in range(3):
    for a,b in zip(X+W[i],data[i]):
        plt.text(a,b,"%.0f"% b,ha="center",va= "bottom")
plt.xlabel("Group")
plt.ylabel("Num")
plt.text(0.0,48,"TEXT")

X = np.linspace(0, 2*np.pi,100)# 均匀的划分数据
Y = np.sin(X)
Y1 = np.cos(X)
plt.plot(X,Y)
plt.plot(X,Y1)
plt.annotate('Points',
         xy=(1, np.sin(1)),
         xytext=(2, 0.5), fontsize=16,
         arrowprops=dict(arrowstyle="->"))

plt.title("这是一副测试图！")

%pylab inline
pylab.rcParams['figure.figsize'] = (10, 6) # 调整图片大小
# np.random.seed(19680801)
n_bins = 10
x = np.random.randn(1000, 3)
fig, axes = plt.subplots(nrows=2, ncols=2)
ax0, ax1, ax2, ax3 = axes.flatten()
colors = ['red', 'tan', 'lime']
ax0.hist(x, n_bins, nORMed=1, histtype='bar', color=colors, label=colors)
ax0.legend(prop={'size': 10})
ax0.set_title('bars with legend')
ax1.hist(x, n_bins, normed=1, histtype='bar', stacked=True)
ax1.set_title('stacked bar')
ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False)
ax2.set_title('stack step (unfilled)')
# Make a multiple-histogram of data-sets with different length.
x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]]
ax3.hist(x_multi, n_bins, histtype='bar')
ax3.set_title('different sample sizes')

import pandas as pd
df = pd.DataFrame(np.random.rand(50, 2), columns=['a', 'b'])
# 散点图
df.plot.scatter(x='a', y='b')

df = pd.DataFrame(np.random.rand(10,4),columns=['a','b','c','d'])
# 绘制柱状图
df.plot.bar()

# 堆积的柱状图
df.plot.bar(stacked=True)

# 水平的柱状图
df.plot.barh(stacked=True)

df = pd.DataFrame({'a':np.random.randn(1000)+1,'b':np.random.randn(1000),'c':np.random.randn(1000) - 1}, columns=['a', 'b', 'c'])
# 直方图
df.plot.hist(bins=20)

# 箱线图
df = pd.DataFrame(np.random.rand(10, 5), columns=['A', 'B', 'C', 'D', 'E'])
df.plot.box()