matplotlib官方文档：https://matplotlib.org/contents.html?v=20190307135750
matplotlib是一个绘图库，它可以创建常用的统计图，包括条形图、箱型图、折线图、散点图和直方图。
import matplotlib.pyplot as plt from matplotlib.font_manager import FontProperties %matplotlib inline font = FontProperties(fname='/Library/Fonts/Heiti.ttc') # 修改背景为条纹 plt.style.use('ggplot') classes = ['3班', '4班', '5班', '6班'] classes_index = range(len(classes)) print(list(classes_index)) [0, 1, 2, 3]
student_amounts = [66, 55, 45, 70] # 画布设置 fig = plt.figure() # 1,1,1表示一张画布切割成1行1列共一张图的第1个；2,2,1表示一张画布切割成2行2列共4张图的第一个（左上角） ax1 = fig.add_subplot(1, 1, 1) ax1.bar(classes_index, student_amounts, align='center', color='darkblue') ax1.xaxis.set_ticks_position('bottom') ax1.yaxis.set_ticks_position('left') plt.xticks(classes_index, classes, rotation=0, fontsize=13, fontproperties=font) plt.xlabel('班级', fontproperties=font, fontsize=15) plt.ylabel('学生人数', fontproperties=font, fontsize=15) plt.title('班级-学生人数', fontproperties=font, fontsize=20) # 保存图片，bbox_inches='tight'去掉图形四周的空白 # plt.savefig('classes_students.png', dpi=400, bbox_inches='tight') plt.show() 
import numpy as np import matplotlib.pyplot as plt from matplotlib.font_manager import FontProperties %matplotlib inline font = FontProperties(fname='/Library/Fonts/Heiti.ttc') # 修改背景为条纹 plt.style.use('ggplot') mu1, mu2, sigma = 50, 100, 10 # 构造均值为50的符合正态分布的数据 x1 = mu1+sigma*np.random.randn(10000) print(x1) [59.00855949 43.16272141 48.77109774 ... 57.94645859 54.70312714 58.94125528]
# 构造均值为100的符合正态分布的数据 x2 = mu2+sigma*np.random.randn(10000) print(x2)
[115.19915511 82.09208214 110.88092454 ... 95.0872103 104.21549068 133.36025251]
fig = plt.figure() ax1 = fig.add_subplot(121) # bins=50表示每个变量的值分成50份，即会有50根柱子 ax1.hist(x1, bins=50, color='darkgreen') ax2 = fig.add_subplot(122) ax2.hist(x2, bins=50, color='orange') fig.suptitle('两个正态分布', fontproperties=font, fontweight='bold', fontsize=15) ax1.set_title('绿色的正态分布', fontproperties=font) ax2.set_title('橙色的正态分布', fontproperties=font) plt.show() 
import numpy as np from numpy.random import randn import matplotlib.pyplot as plt from matplotlib.font_manager import FontProperties %matplotlib inline font = FontProperties(fname='/Library/Fonts/Heiti.ttc') # 修改背景为条纹 plt.style.use('ggplot') np.random.seed(1) # 使用numpy的累加和，保证数据取值范围不会在（0，1）内波动 plot_data1 = randn(40).cumsum() print(plot_data1) [ 1.62434536 1.01258895 0.4844172 -0.58855142 0.2768562 -2.02468249 -0.27987073 -1.04107763 -0.72203853 -0.97140891 0.49069903 -1.56944168 -1.89185888 -2.27591324 -1.1421438 -2.24203506 -2.41446327 -3.29232169 -3.25010794 -2.66729273 -3.76791191 -2.6231882 -1.72159748 -1.21910314 -0.31824719 -1.00197505 -1.12486527 -2.06063471 -2.32852279 -1.79816732 -2.48982807 -2.8865816 -3.5737543 -4.41895994 -5.09020607 -5.10287067 -6.22018102 -5.98576532 -4.32596314 -3.58391898]
plot_data2 = randn(40).cumsum() plot_data3 = randn(40).cumsum() plot_data4 = randn(40).cumsum() plt.plot(plot_data1, marker='o', color='red', linestyle='-', label='红实线') plt.plot(plot_data2, marker='x', color='orange', linestyle='--', label='橙虚线') plt.plot(plot_data3, marker='*', color='yellow', linestyle='-.', label='黄点线') plt.plot(plot_data4, marker='s', color='green', linestyle=':', label='绿点图') # loc='best'给label自动选择最好的位置 plt.legend(loc='best', prop=font) plt.show()
import numpy as np from numpy.random import randn import matplotlib.pyplot as plt from matplotlib.font_manager import FontProperties %matplotlib inline font = FontProperties(fname='/Library/Fonts/Heiti.ttc') # 修改背景为条纹 plt.style.use('ggplot') x = np.arange(1, 20, 1) print(x) [ 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19]
# 拟合一条水平散点线 np.random.seed(1) y_linear = x+10*np.random.randn(19) print(y_linear)
[ 17.24345364 -4.11756414 -2.28171752 -6.72968622 13.65407629 -17.01538697 24.44811764 0.38793099 12.19039096 7.50629625 25.62107937 -8.60140709 9.77582796 10.15945645 26.33769442 5.00108733 15.27571792 9.22141582 19.42213747]
[ 6.82815214 -7.00619177 20.4472371 25.01590721 30.02494339 45.00855949 42.16272141 62.77109774 71.64230566 97.3211192 126.30355467 137.08339248 165.03246473 189.128273 216.54794359 249.28753869 288.87335401 312.82689651 363.34415698]
# s是散点大小 fig = plt.figure() ax1 = fig.add_subplot(121) plt.scatter(x, y_linear, s=30, color='r', label='蓝点') plt.scatter(x, y_quad, s=100, color='b', label='红点') ax2 = fig.add_subplot(122) plt.plot(x, y_linear, color='r') plt.plot(x, y_quad, color='b') # 限制x轴和y轴的范围取值 plt.xlim(min(x)-1, max(x)+1) plt.ylim(min(y_quad)-10, max(y_quad)+10) fig.suptitle('散点图+直线图', fontproperties=font, fontsize=20) ax1.set_title('散点图', fontproperties=font) ax1.legend(prop=font) ax2.set_title('直线图', fontproperties=font) plt.show() 