{"id":1108819,"date":"2025-01-08T17:04:00","date_gmt":"2025-01-08T09:04:00","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1108819.html"},"modified":"2025-01-08T17:04:03","modified_gmt":"2025-01-08T09:04:03","slug":"python%e5%a6%82%e4%bd%95%e5%90%8c%e6%97%b6%e7%94%bb%e4%b8%a4%e4%b8%aa%e9%a5%bc%e5%9b%be","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1108819.html","title":{"rendered":"python\u5982\u4f55\u540c\u65f6\u753b\u4e24\u4e2a\u997c\u56fe"},"content":{"rendered":"

\"python\u5982\u4f55\u540c\u65f6\u753b\u4e24\u4e2a\u997c\u56fe\"<\/p>\n

\u4f7f\u7528Python\u540c\u65f6\u753b\u4e24\u4e2a\u997c\u56fe\u7684\u65b9\u6cd5\u662f\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528subplot\u65b9\u6cd5\u3001\u8bbe\u7f6e\u5408\u9002\u7684\u56fe\u5f62\u5e03\u5c40\u3002<\/strong> \u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5728\u540c\u4e00\u5f20\u56fe\u4e2d\u663e\u793a\u4e24\u4e2a\u6216\u66f4\u591a\u7684\u997c\u56fe\u3002\u4e0b\u9762\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u65b9\u6cd5\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n

\n

\u4e00\u3001\u4f7f\u7528Matplotlib\u5e93<\/h3>\n<\/p>\n

Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\u4e4b\u4e00\u3002\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u5305\u62ec\u7ed8\u5236\u997c\u56fe\u3002\u8981\u5f00\u59cb\u4f7f\u7528Matplotlib\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5\u8be5\u5e93\u3002\u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5Matplotlib\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install matplotlib<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u4f60\u53ef\u4ee5\u5f00\u59cb\u7f16\u5199\u4ee3\u7801\u6765\u7ed8\u5236\u997c\u56fe\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528subplot\u65b9\u6cd5<\/h3>\n<\/p>\n
Matplotlib\u4e2d\u7684subplot\u65b9\u6cd5\u5141\u8bb8\u4f60\u5728\u540c\u4e00\u5f20\u56fe\u4e2d\u521b\u5efa\u591a\u4e2a\u5b50\u56fe\u3002\u6bcf\u4e2a\u5b50\u56fe\u53ef\u4ee5\u5305\u542b\u4e00\u4e2a\u72ec\u7acb\u7684\u997c\u56fe\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528subplot\u65b9\u6cd5\u7ed8\u5236\u4e24\u4e2a\u997c\u56fe\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
labels1 = ['A', 'B', 'C', 'D']<\/p>\n
sizes1 = [15, 30, 45, 10]<\/p>\n
labels2 = ['E', 'F', 'G', 'H']<\/p>\n
sizes2 = [10, 20, 30, 40]<\/p>\n
\u521b\u5efa\u4e00\u4e2a\u56fe\u5f62\u5bf9\u8c61\u548c\u4e24\u4e2a\u5b50\u56fe<\/strong><\/h2>\n
fig, (ax1, ax2) = plt.subplots(1, 2)<\/p>\n
\u5728\u7b2c\u4e00\u4e2a\u5b50\u56fe\u4e2d\u7ed8\u5236\u997c\u56fe<\/strong><\/h2>\n
ax1.pie(sizes1, labels=labels1, autopct='%1.1f%%', startangle=90)<\/p>\n
ax1.axis('equal')  # \u4fdd\u8bc1\u997c\u56fe\u662f\u5706\u7684<\/p>\n
\u5728\u7b2c\u4e8c\u4e2a\u5b50\u56fe\u4e2d\u7ed8\u5236\u997c\u56fe<\/strong><\/h2>\n
ax2.pie(sizes2, labels=labels2, autopct='%1.1f%%', startangle=90)<\/p>\n
ax2.axis('equal')  # \u4fdd\u8bc1\u997c\u56fe\u662f\u5706\u7684<\/p>\n
\u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u5b9a\u4e49\u4e86\u4e24\u4e2a\u6570\u636e\u96c6\uff0c\u6bcf\u4e2a\u6570\u636e\u96c6\u5305\u542b\u6807\u7b7e\u548c\u5bf9\u5e94\u7684\u5927\u5c0f\u3002\u7136\u540e\uff0c\u6211\u4eec\u4f7f\u7528plt.subplots<\/code>\u65b9\u6cd5\u521b\u5efa\u4e00\u4e2a\u56fe\u5f62\u5bf9\u8c61\u548c\u4e24\u4e2a\u5b50\u56fe\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5728\u6bcf\u4e2a\u5b50\u56fe\u4e2d\u5206\u522b\u7ed8\u5236\u997c\u56fe\uff0c\u5e76\u4f7f\u7528plt.show()<\/code>\u65b9\u6cd5\u663e\u793a\u56fe\u5f62\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u8bbe\u7f6e\u5408\u9002\u7684\u56fe\u5f62\u5e03\u5c40<\/h3>\n<\/p>\n
\u5728\u7ed8\u5236\u591a\u4e2a\u5b50\u56fe\u65f6\uff0c\u5408\u9002\u7684\u56fe\u5f62\u5e03\u5c40\u53ef\u4ee5\u4f7f\u56fe\u5f62\u66f4\u52a0\u7f8e\u89c2\u548c\u6613\u4e8e\u7406\u89e3\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528figsize<\/code>\u53c2\u6570\u6765\u8bbe\u7f6e\u56fe\u5f62\u7684\u5927\u5c0f\uff0c\u5e76\u4f7f\u7528subplots_adjust<\/code>\u65b9\u6cd5\u6765\u8c03\u6574\u5b50\u56fe\u4e4b\u95f4\u7684\u95f4\u8ddd\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u8bbe\u7f6e\u56fe\u5f62\u5e03\u5c40\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
labels1 = ['A', 'B', 'C', 'D']<\/p>\n
sizes1 = [15, 30, 45, 10]<\/p>\n
labels2 = ['E', 'F', 'G', 'H']<\/p>\n
sizes2 = [10, 20, 30, 40]<\/p>\n
\u8bbe\u7f6e\u56fe\u5f62\u5927\u5c0f<\/strong><\/h2>\n
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))<\/p>\n
\u8c03\u6574\u5b50\u56fe\u4e4b\u95f4\u7684\u95f4\u8ddd<\/strong><\/h2>\n
fig.subplots_adjust(wspace=0.4)<\/p>\n
\u5728\u7b2c\u4e00\u4e2a\u5b50\u56fe\u4e2d\u7ed8\u5236\u997c\u56fe<\/strong><\/h2>\n
ax1.pie(sizes1, labels=labels1, autopct='%1.1f%%', startangle=90)<\/p>\n
ax1.axis('equal')  # \u4fdd\u8bc1\u997c\u56fe\u662f\u5706\u7684<\/p>\n
\u5728\u7b2c\u4e8c\u4e2a\u5b50\u56fe\u4e2d\u7ed8\u5236\u997c\u56fe<\/strong><\/h2>\n
ax2.pie(sizes2, labels=labels2, autopct='%1.1f%%', startangle=90)<\/p>\n
ax2.axis('equal')  # \u4fdd\u8bc1\u997c\u56fe\u662f\u5706\u7684<\/p>\n
\u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528figsize<\/code>\u53c2\u6570\u8bbe\u7f6e\u4e86\u56fe\u5f62\u7684\u5927\u5c0f\u4e3a12×6\uff0c\u5e76\u4f7f\u7528subplots_adjust<\/code>\u65b9\u6cd5\u5c06\u4e24\u4e2a\u5b50\u56fe\u4e4b\u95f4\u7684\u6c34\u5e73\u95f4\u8ddd\u8bbe\u7f6e\u4e3a0.4\u3002\u8fd9\u6837\uff0c\u53ef\u4ee5\u786e\u4fdd\u4e24\u4e2a\u997c\u56fe\u4e4b\u95f4\u6709\u8db3\u591f\u7684\u7a7a\u95f4\uff0c\u4f7f\u56fe\u5f62\u66f4\u52a0\u7f8e\u89c2\u3002<\/p>\n<\/p>\n
\u56db\u3001\u6dfb\u52a0\u6807\u9898\u548c\u6ce8\u91ca<\/h3>\n<\/p>\n
\u4e3a\u4e86\u4f7f\u56fe\u5f62\u66f4\u52a0\u6613\u4e8e\u7406\u89e3\uff0c\u4f60\u53ef\u4ee5\u4e3a\u6bcf\u4e2a\u5b50\u56fe\u6dfb\u52a0\u6807\u9898\uff0c\u5e76\u5728\u997c\u56fe\u4e0a\u6dfb\u52a0\u6ce8\u91ca\u3002\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u6dfb\u52a0\u6807\u9898\u548c\u6ce8\u91ca\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
labels1 = ['A', 'B', 'C', 'D']<\/p>\n
sizes1 = [15, 30, 45, 10]<\/p>\n
labels2 = ['E', 'F', 'G', 'H']<\/p>\n
sizes2 = [10, 20, 30, 40]<\/p>\n
\u8bbe\u7f6e\u56fe\u5f62\u5927\u5c0f<\/strong><\/h2>\n
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))<\/p>\n
\u8c03\u6574\u5b50\u56fe\u4e4b\u95f4\u7684\u95f4\u8ddd<\/strong><\/h2>\n
fig.subplots_adjust(wspace=0.4)<\/p>\n
\u5728\u7b2c\u4e00\u4e2a\u5b50\u56fe\u4e2d\u7ed8\u5236\u997c\u56fe\uff0c\u5e76\u6dfb\u52a0\u6807\u9898<\/strong><\/h2>\n
ax1.pie(sizes1, labels=labels1, autopct='%1.1f%%', startangle=90)<\/p>\n
ax1.axis('equal')  # \u4fdd\u8bc1\u997c\u56fe\u662f\u5706\u7684<\/p>\n
ax1.set_title('\u997c\u56fe 1')<\/p>\n
\u5728\u7b2c\u4e8c\u4e2a\u5b50\u56fe\u4e2d\u7ed8\u5236\u997c\u56fe\uff0c\u5e76\u6dfb\u52a0\u6807\u9898<\/strong><\/h2>\n
ax2.pie(sizes2, labels=labels2, autopct='%1.1f%%', startangle=90)<\/p>\n
ax2.axis('equal')  # \u4fdd\u8bc1\u997c\u56fe\u662f\u5706\u7684<\/p>\n
ax2.set_title('\u997c\u56fe 2')<\/p>\n
\u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528set_title<\/code>\u65b9\u6cd5\u4e3a\u6bcf\u4e2a\u5b50\u56fe\u6dfb\u52a0\u4e86\u6807\u9898\u3002\u4f60\u8fd8\u53ef\u4ee5\u4f7f\u7528annotate<\/code>\u65b9\u6cd5\u5728\u997c\u56fe\u4e0a\u6dfb\u52a0\u6ce8\u91ca\uff0c\u4ee5\u63d0\u4f9b\u66f4\u591a\u4fe1\u606f\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u4f7f\u7528\u4e0d\u540c\u7684\u989c\u8272\u548c\u6837\u5f0f<\/h3>\n<\/p>\n
\u4e3a\u4e86\u4f7f\u997c\u56fe\u66f4\u52a0\u7f8e\u89c2\u548c\u4fe1\u606f\u4e30\u5bcc\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528\u4e0d\u540c\u7684\u989c\u8272\u548c\u6837\u5f0f\u3002Matplotlib\u63d0\u4f9b\u4e86\u591a\u79cd\u989c\u8272\u6620\u5c04\u548c\u6837\u5f0f\u9009\u9879\uff0c\u4e0b\u9762\u662f\u4e00\u4e2a\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u9009\u9879\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u6570\u636e<\/strong><\/h2>\n
labels1 = ['A', 'B', 'C', 'D']<\/p>\n
sizes1 = [15, 30, 45, 10]<\/p>\n
colors1 = ['#ff9999','#66b3ff','#99ff99','#ffcc99']<\/p>\n
labels2 = ['E', 'F', 'G', 'H']<\/p>\n
sizes2 = [10, 20, 30, 40]<\/p>\n
colors2 = ['#c2c2f0','#ffb3e6','#c4e17f','#76d7c4']<\/p>\n
\u8bbe\u7f6e\u56fe\u5f62\u5927\u5c0f<\/strong><\/h2>\n
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(12, 6))<\/p>\n
\u8c03\u6574\u5b50\u56fe\u4e4b\u95f4\u7684\u95f4\u8ddd<\/strong><\/h2>\n
fig.subplots_adjust(wspace=0.4)<\/p>\n
\u5728\u7b2c\u4e00\u4e2a\u5b50\u56fe\u4e2d\u7ed8\u5236\u997c\u56fe\uff0c\u5e76\u4f7f\u7528\u4e0d\u540c\u7684\u989c\u8272<\/strong><\/h2>\n
ax1.pie(sizes1, labels=labels1, autopct='%1.1f%%', startangle=90, colors=colors1)<\/p>\n
ax1.axis('equal')  # \u4fdd\u8bc1\u997c\u56fe\u662f\u5706\u7684<\/p>\n
ax1.set_title('\u997c\u56fe 1')<\/p>\n
\u5728\u7b2c\u4e8c\u4e2a\u5b50\u56fe\u4e2d\u7ed8\u5236\u997c\u56fe\uff0c\u5e76\u4f7f\u7528\u4e0d\u540c\u7684\u989c\u8272<\/strong><\/h2>\n
ax2.pie(sizes2, labels=labels2, autopct='%1.1f%%', startangle=90, colors=colors2)<\/p>\n
ax2.axis('equal')  # \u4fdd\u8bc1\u997c\u56fe\u662f\u5706\u7684<\/p>\n
ax2.set_title('\u997c\u56fe 2')<\/p>\n
\u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u5b9a\u4e49\u4e86\u989c\u8272\u5217\u8868colors1<\/code>\u548ccolors2<\/code>\uff0c\u5e76\u5728\u7ed8\u5236\u997c\u56fe\u65f6\u4f7f\u7528\u4e86\u8fd9\u4e9b\u989c\u8272\u3002\u4f60\u53ef\u4ee5\u6839\u636e\u9700\u8981\u9009\u62e9\u4e0d\u540c\u7684\u989c\u8272\uff0c\u4ee5\u4f7f\u997c\u56fe\u66f4\u52a0\u7f8e\u89c2\u548c\u6613\u4e8e\u533a\u5206\u3002<\/p>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u5728\u540c\u4e00\u5f20\u56fe\u4e2d\u7ed8\u5236\u591a\u4e2a\u997c\u56fe\uff0c\u5e76\u4f7f\u7528\u4e0d\u540c\u7684\u989c\u8272\u3001\u6837\u5f0f\u548c\u5e03\u5c40\uff0c\u4f7f\u56fe\u5f62\u66f4\u52a0\u7f8e\u89c2\u548c\u4fe1\u606f\u4e30\u5bcc\u3002\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n
    \n
  • \u4f7f\u7528Matplotlib\u5e93<\/li>\n
  • \u4f7f\u7528subplot\u65b9\u6cd5\u521b\u5efa\u591a\u4e2a\u5b50\u56fe<\/li>\n
  • \u8bbe\u7f6e\u5408\u9002\u7684\u56fe\u5f62\u5e03\u5c40<\/li>\n
  • \u6dfb\u52a0\u6807\u9898\u548c\u6ce8\u91ca<\/li>\n
  • \u4f7f\u7528\u4e0d\u540c\u7684\u989c\u8272\u548c\u6837\u5f0f<\/li>\n<\/ul>\n
    \u901a\u8fc7\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u4f60\u53ef\u4ee5\u8f7b\u677e\u5730\u5728Python\u4e2d\u540c\u65f6\u7ed8\u5236\u4e24\u4e2a\u6216\u66f4\u591a\u7684\u997c\u56fe\uff0c\u5e76\u6839\u636e\u9700\u8981\u8fdb\u884c\u81ea\u5b9a\u4e49\u3002\u5e0c\u671b\u8fd9\u7bc7\u6587\u7ae0\u5bf9\u4f60\u6709\u6240\u5e2e\u52a9\uff01<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528Matplotlib\u7ed8\u5236\u591a\u4e2a\u997c\u56fe\uff1f<\/strong>
    \u5728Python\u4e2d\uff0c\u4f7f\u7528Matplotlib\u5e93\u53ef\u4ee5\u8f7b\u677e\u7ed8\u5236\u591a\u4e2a\u997c\u56fe\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u521b\u5efa\u5b50\u56fe\u6765\u5b9e\u73b0\u3002\u4f8b\u5982\uff0c\u4f7f\u7528plt.subplot()<\/code>\u51fd\u6570\u53ef\u4ee5\u5728\u540c\u4e00\u753b\u5e03\u4e0a\u5b89\u6392\u591a\u4e2a\u997c\u56fe\u3002\u4ee3\u7801\u793a\u4f8b\u5305\u62ec\u5b9a\u4e49\u6570\u636e\uff0c\u8c03\u7528plt.pie()<\/code>\u7ed8\u5236\u997c\u56fe\uff0c\u7136\u540e\u4f7f\u7528plt.show()<\/code>\u5c55\u793a\u7ed3\u679c\u3002<\/p>\n
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