{"id":978611,"date":"2024-12-27T06:39:14","date_gmt":"2024-12-26T22:39:14","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/978611.html"},"modified":"2024-12-27T06:39:16","modified_gmt":"2024-12-26T22:39:16","slug":"python-%e5%a6%82%e4%bd%95%e5%88%b6%e4%bd%9c%e5%9b%be%e8%a1%a8","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/978611.html","title":{"rendered":"python \u5982\u4f55\u5236\u4f5c\u56fe\u8868"},"content":{"rendered":"

\"python<\/p>\n

Python\u5236\u4f5c\u56fe\u8868\u7684\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u5229\u7528Seaborn\u5e93\u3001\u901a\u8fc7Plotly\u5e93\u3001\u5229\u7528Pandas\u5185\u7f6e\u7ed8\u56fe\u529f\u80fd\u3002<\/strong>\u5176\u4e2d\uff0cMatplotlib\u662f\u6700\u57fa\u7840\u548c\u5e7f\u6cdb\u4f7f\u7528\u7684\u7ed8\u56fe\u5e93\uff0c\u9002\u5408\u5236\u4f5c\u5404\u79cd\u7c7b\u578b\u7684\u9759\u6001\u3001\u4ea4\u4e92\u5f0f\u548c\u52a8\u753b\u56fe\u8868\u3002\u4ee5\u4e0b\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Matplotlib\u5e93\u6765\u5236\u4f5c\u56fe\u8868\u3002<\/p>\n<\/p>\n

Python\u662f\u4e00\u79cd\u529f\u80fd\u5f3a\u5927\u7684\u7f16\u7a0b\u8bed\u8a00\uff0c\u51ed\u501f\u5176\u4e30\u5bcc\u7684\u5e93\u652f\u6301\uff0c\u80fd\u591f\u8f7b\u677e\u5b9e\u73b0\u6570\u636e\u7684\u53ef\u89c6\u5316\u3002\u5176\u4e2d\uff0cMatplotlib\u3001Seaborn\u3001Plotly\u548cPandas\u662f\u6700\u5e38\u7528\u7684\u5e93\u3002Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00<\/strong>\uff0c\u5b83\u80fd\u591f\u521b\u5efa\u5404\u79cd\u9759\u6001\u3001\u52a8\u6001\u548c\u4ea4\u4e92\u5f0f\u56fe\u8868\u3002\u901a\u8fc7Matplotlib\uff0c\u6211\u4eec\u53ef\u4ee5\u4ece\u7b80\u5355\u7684\u6298\u7ebf\u56fe\u5230\u590d\u6742\u76843D\u56fe\u8868\u8fdb\u884c\u7ed8\u5236\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u6df1\u5165\u63a2\u8ba8\u5982\u4f55\u4f7f\u7528Matplotlib\u5e93\u6765\u5236\u4f5c\u56fe\u8868\u3002<\/p>\n<\/p>\n

\u4e00\u3001MATPLOTLIB\u7b80\u4ecb<\/h3>\n<\/p>\n

Matplotlib\u662f\u4e00\u4e2a\u7528\u4e8ePython\u76842D\u7ed8\u56fe\u5e93\uff0c\u80fd\u591f\u751f\u6210\u5404\u79cd\u4e13\u4e1a\u8d28\u91cf\u7684\u56fe\u8868\u3002\u5b83\u7684\u6838\u5fc3\u662fpyplot\u6a21\u5757\uff0c\u8fd9\u4e2a\u6a21\u5757\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u51fd\u6570\uff0c\u4f7f\u5f97\u7ed8\u56fe\u53d8\u5f97\u7b80\u5355\u3002<\/p>\n<\/p>\n

1\u3001Matplotlib\u7684\u5b89\u88c5\u4e0e\u5bfc\u5165<\/h4>\n<\/p>\n

\u5728\u4f7f\u7528Matplotlib\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u786e\u4fdd\u5b89\u88c5\u4e86\u8be5\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\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\u5c31\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165Matplotlib\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001Matplotlib\u7684\u57fa\u672c\u7ed8\u56fe\u6d41\u7a0b<\/h4>\n<\/p>\n
\u4f7f\u7528Matplotlib\u8fdb\u884c\u7ed8\u56fe\u901a\u5e38\u5305\u62ec\u4ee5\u4e0b\u51e0\u4e2a\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
    \n
  • \u51c6\u5907\u6570\u636e\uff1a\u5b9a\u4e49\u8981\u7ed8\u5236\u7684\u6570\u636e\u3002<\/li>\n
  • \u521b\u5efa\u56fe\u5f62\u548c\u8f74\uff1a\u4f7f\u7528plt.figure()<\/code>\u548cplt.subplot()<\/code>\u51fd\u6570\u3002<\/li>\n
  • \u7ed8\u5236\u56fe\u8868\uff1a\u8c03\u7528\u7ed8\u56fe\u51fd\u6570\uff0c\u5982plt.plot()<\/code>\u3001plt.bar()<\/code>\u7b49\u3002<\/li>\n
  • \u6dfb\u52a0\u6807\u7b7e\u548c\u6807\u9898\uff1a\u4f7f\u7528plt.xlabel()<\/code>\u3001plt.ylabel()<\/code>\u548cplt.title()<\/code>\u3002<\/li>\n
  • \u663e\u793a\u56fe\u8868\uff1a\u4f7f\u7528plt.show()<\/code>\u51fd\u6570\u3002<\/li>\n<\/ul>\n
    \u4e8c\u3001MATPLOTLIB\u7ed8\u56fe\u793a\u4f8b<\/h3>\n<\/p>\n
    \u901a\u8fc7\u4e00\u4e2a\u5177\u4f53\u7684\u793a\u4f8b\u6765\u5c55\u793a\u5982\u4f55\u4f7f\u7528Matplotlib\u7ed8\u5236\u56fe\u8868\u3002<\/p>\n<\/p>\n
    1\u3001\u7ed8\u5236\u7b80\u5355\u7684\u6298\u7ebf\u56fe<\/h4>\n<\/p>\n
    \u6298\u7ebf\u56fe\u662f\u6700\u5e38\u89c1\u7684\u56fe\u8868\u7c7b\u578b\u4e4b\u4e00\uff0c\u9002\u7528\u4e8e\u663e\u793a\u6570\u636e\u968f\u65f6\u95f4\u7684\u53d8\u5316\u8d8b\u52bf\u3002<\/p>\n<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u51c6\u5907\u6570\u636e<\/strong><\/h2>\n
    x = [1, 2, 3, 4, 5]<\/p>\n
    y = [2, 3, 5, 7, 11]<\/p>\n
    \u521b\u5efa\u56fe\u5f62\u548c\u8f74<\/strong><\/h2>\n
    plt.figure()<\/p>\n
    \u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
    plt.plot(x, y)<\/p>\n
    \u6dfb\u52a0\u6807\u7b7e\u548c\u6807\u9898<\/strong><\/h2>\n
    plt.xlabel('X\u8f74')<\/p>\n
    plt.ylabel('Y\u8f74')<\/p>\n
    plt.title('\u7b80\u5355\u6298\u7ebf\u56fe\u793a\u4f8b')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2\u3001\u7ed8\u5236\u67f1\u72b6\u56fe<\/h4>\n<\/p>\n
    \u67f1\u72b6\u56fe\u9002\u7528\u4e8e\u6bd4\u8f83\u4e0d\u540c\u7c7b\u522b\u4e4b\u95f4\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u51c6\u5907\u6570\u636e<\/strong><\/h2>\n
    categories = ['A', 'B', 'C', 'D']<\/p>\n
    values = [5, 7, 3, 4]<\/p>\n
    \u521b\u5efa\u56fe\u5f62\u548c\u8f74<\/strong><\/h2>\n
    plt.figure()<\/p>\n
    \u7ed8\u5236\u67f1\u72b6\u56fe<\/strong><\/h2>\n
    plt.bar(categories, values)<\/p>\n
    \u6dfb\u52a0\u6807\u7b7e\u548c\u6807\u9898<\/strong><\/h2>\n
    plt.xlabel('\u7c7b\u522b')<\/p>\n
    plt.ylabel('\u503c')<\/p>\n
    plt.title('\u67f1\u72b6\u56fe\u793a\u4f8b')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e09\u3001MATPLOTLIB\u9ad8\u7ea7\u529f\u80fd<\/h3>\n<\/p>\n
    Matplotlib\u4e0d\u4ec5\u9650\u4e8e\u7b80\u5355\u7684\u6298\u7ebf\u56fe\u548c\u67f1\u72b6\u56fe\uff0c\u5b83\u8fd8\u652f\u6301\u66f4\u590d\u6742\u7684\u56fe\u8868\u7c7b\u578b\u548c\u81ea\u5b9a\u4e49\u529f\u80fd\u3002<\/p>\n<\/p>\n
    1\u3001\u7ed8\u5236\u591a\u5b50\u56fe<\/h4>\n<\/p>\n
    Matplotlib\u5141\u8bb8\u5728\u540c\u4e00\u56fe\u5f62\u4e2d\u7ed8\u5236\u591a\u4e2a\u5b50\u56fe\uff0c\u8fd9\u5bf9\u4e8e\u6bd4\u8f83\u4e0d\u540c\u6570\u636e\u96c6\u975e\u5e38\u6709\u7528\u3002<\/p>\n<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u51c6\u5907\u6570\u636e<\/strong><\/h2>\n
    x1 = [1, 2, 3, 4, 5]<\/p>\n
    y1 = [2, 3, 5, 7, 11]<\/p>\n
    x2 = [1, 2, 3, 4, 5]<\/p>\n
    y2 = [3, 5, 7, 9, 11]<\/p>\n
    \u521b\u5efa\u56fe\u5f62<\/strong><\/h2>\n
    plt.figure()<\/p>\n
    \u521b\u5efa\u7b2c\u4e00\u4e2a\u5b50\u56fe<\/strong><\/h2>\n
    plt.subplot(2, 1, 1)<\/p>\n
    plt.plot(x1, y1)<\/p>\n
    plt.title('\u5b50\u56fe1')<\/p>\n
    \u521b\u5efa\u7b2c\u4e8c\u4e2a\u5b50\u56fe<\/strong><\/h2>\n
    plt.subplot(2, 1, 2)<\/p>\n
    plt.plot(x2, y2)<\/p>\n
    plt.title('\u5b50\u56fe2')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    plt.tight_layout()<\/p>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2\u3001\u7ed8\u5236\u997c\u56fe<\/h4>\n<\/p>\n
    \u997c\u56fe\u7528\u4e8e\u663e\u793a\u90e8\u5206\u4e0e\u6574\u4f53\u7684\u5173\u7cfb\u3002<\/p>\n<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u51c6\u5907\u6570\u636e<\/strong><\/h2>\n
    labels = ['A', 'B', 'C', 'D']<\/p>\n
    sizes = [15, 30, 45, 10]<\/p>\n
    \u521b\u5efa\u56fe\u5f62<\/strong><\/h2>\n
    plt.figure()<\/p>\n
    \u7ed8\u5236\u997c\u56fe<\/strong><\/h2>\n
    plt.pie(sizes, labels=labels, autopct='%1.1f%%')<\/p>\n
    \u6dfb\u52a0\u6807\u9898<\/strong><\/h2>\n
    plt.title('\u997c\u56fe\u793a\u4f8b')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u56db\u3001MATPLOTLIB\u81ea\u5b9a\u4e49\u4e0e\u4f18\u5316<\/h3>\n<\/p>\n
    Matplotlib\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u81ea\u5b9a\u4e49\u9009\u9879\uff0c\u4f7f\u5f97\u56fe\u8868\u7684\u5916\u89c2\u66f4\u52a0\u4e13\u4e1a\u3002<\/p>\n<\/p>\n
    1\u3001\u8bbe\u7f6e\u56fe\u4f8b\u548c\u7f51\u683c<\/h4>\n<\/p>\n
    \u56fe\u4f8b\u548c\u7f51\u683c\u53ef\u4ee5\u5e2e\u52a9\u8bfb\u8005\u66f4\u597d\u5730\u7406\u89e3\u56fe\u8868\u6570\u636e\u3002<\/p>\n<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u51c6\u5907\u6570\u636e<\/strong><\/h2>\n
    x = [1, 2, 3, 4, 5]<\/p>\n
    y1 = [2, 3, 5, 7, 11]<\/p>\n
    y2 = [3, 5, 7, 9, 11]<\/p>\n
    \u521b\u5efa\u56fe\u5f62<\/strong><\/h2>\n
    plt.figure()<\/p>\n
    \u7ed8\u5236\u4e24\u6761\u6298\u7ebf<\/strong><\/h2>\n
    plt.plot(x, y1, label='\u6570\u636e1')<\/p>\n
    plt.plot(x, y2, label='\u6570\u636e2')<\/p>\n
    \u6dfb\u52a0\u56fe\u4f8b<\/strong><\/h2>\n
    plt.legend()<\/p>\n
    \u6dfb\u52a0\u7f51\u683c<\/strong><\/h2>\n
    plt.grid(True)<\/p>\n
    \u6dfb\u52a0\u6807\u7b7e\u548c\u6807\u9898<\/strong><\/h2>\n
    plt.xlabel('X\u8f74')<\/p>\n
    plt.ylabel('Y\u8f74')<\/p>\n
    plt.title('\u56fe\u4f8b\u548c\u7f51\u683c\u793a\u4f8b')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2\u3001\u8c03\u6574\u56fe\u8868\u6837\u5f0f<\/h4>\n<\/p>\n
    \u901a\u8fc7Matplotlib\u7684\u6837\u5f0f\u9009\u9879\uff0c\u53ef\u4ee5\u8f7b\u677e\u6539\u53d8\u56fe\u8868\u7684\u5916\u89c2\u3002<\/p>\n<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u4f7f\u7528\u4e0d\u540c\u7684\u6837\u5f0f<\/strong><\/h2>\n
    plt.style.use('seaborn-darkgrid')<\/p>\n
    \u51c6\u5907\u6570\u636e<\/strong><\/h2>\n
    x = [1, 2, 3, 4, 5]<\/p>\n
    y = [2, 3, 5, 7, 11]<\/p>\n
    \u521b\u5efa\u56fe\u5f62<\/strong><\/h2>\n
    plt.figure()<\/p>\n
    \u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
    plt.plot(x, y)<\/p>\n
    \u6dfb\u52a0\u6807\u7b7e\u548c\u6807\u9898<\/strong><\/h2>\n
    plt.xlabel('X\u8f74')<\/p>\n
    plt.ylabel('Y\u8f74')<\/p>\n
    plt.title('\u6837\u5f0f\u8c03\u6574\u793a\u4f8b')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e94\u3001MATPLOTLIB\u4e0ePANDAS\u7ed3\u5408<\/h3>\n<\/p>\n
    Pandas\u662fPython\u4e2d\u7528\u4e8e\u6570\u636e\u5904\u7406\u7684\u5f3a\u5927\u5de5\u5177\uff0c\u4e0eMatplotlib\u7ed3\u5408\u4f7f\u7528\uff0c\u53ef\u4ee5\u5927\u5927\u7b80\u5316\u7ed8\u56fe\u8fc7\u7a0b\u3002<\/p>\n<\/p>\n
    1\u3001\u4f7f\u7528Pandas\u7ed8\u5236\u56fe\u8868<\/h4>\n<\/p>\n
    Pandas\u63d0\u4f9b\u4e86\u5185\u7f6e\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u53ef\u4ee5\u76f4\u63a5\u4eceDataFrame\u4e2d\u521b\u5efa\u56fe\u8868\u3002<\/p>\n<\/p>\n
    import pandas as pd<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u521b\u5efaDataFrame<\/strong><\/h2>\n
    data = {'Category': ['A', 'B', 'C', 'D'],<\/p>\n
            'Value': [4, 7, 1, 8]}<\/p>\n
    df = pd.DataFrame(data)<\/p>\n
    \u4f7f\u7528Pandas\u7ed8\u5236\u67f1\u72b6\u56fe<\/strong><\/h2>\n
    df.plot(kind='bar', x='Category', y='Value')<\/p>\n
    \u6dfb\u52a0\u6807\u9898<\/strong><\/h2>\n
    plt.title('Pandas\u7ed8\u56fe\u793a\u4f8b')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2\u3001\u7ed3\u5408Pandas\u548cMatplotlib\u8fdb\u884c\u9ad8\u7ea7\u7ed8\u56fe<\/h4>\n<\/p>\n
    \u53ef\u4ee5\u7ed3\u5408Pandas\u7684\u6570\u636e\u5904\u7406\u80fd\u529b\u548cMatplotlib\u7684\u7ed8\u56fe\u80fd\u529b\uff0c\u521b\u5efa\u66f4\u52a0\u590d\u6742\u7684\u56fe\u8868\u3002<\/p>\n<\/p>\n
    import pandas as pd<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u521b\u5efaDataFrame<\/strong><\/h2>\n
    data = {'Month': ['Jan', 'Feb', 'Mar', 'Apr'],<\/p>\n
            'Sales': [200, 220, 250, 275]}<\/p>\n
    df = pd.DataFrame(data)<\/p>\n
    \u8bbe\u7f6e\u7d22\u5f15\u4e3aMonth<\/strong><\/h2>\n
    df.set_index('Month', inplace=True)<\/p>\n
    \u4f7f\u7528Pandas\u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
    df.plot()<\/p>\n
    \u4f7f\u7528Matplotlib\u81ea\u5b9a\u4e49\u56fe\u8868<\/strong><\/h2>\n
    plt.title('\u7ed3\u5408Pandas\u548cMatplotlib\u8fdb\u884c\u9ad8\u7ea7\u7ed8\u56fe')<\/p>\n
    plt.xlabel('\u6708\u4efd')<\/p>\n
    plt.ylabel('\u9500\u552e\u989d')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u516d\u3001SEABORN\u5e93\u7684\u4f7f\u7528<\/h3>\n<\/p>\n
    Seaborn\u662f\u57fa\u4e8eMatplotlib\u6784\u5efa\u7684\u9ad8\u7ea7\u7ed8\u56fe\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u7f8e\u89c2\u548c\u590d\u6742\u7684\u56fe\u8868\u9009\u9879\u3002<\/p>\n<\/p>\n
    1\u3001\u5b89\u88c5\u548c\u5bfc\u5165Seaborn<\/h4>\n<\/p>\n
    \u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5Seaborn\uff1a<\/p>\n<\/p>\n
    pip install seaborn<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u7136\u540e\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165Seaborn\uff1a<\/p>\n<\/p>\n
    import seaborn as sns<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2\u3001\u4f7f\u7528Seaborn\u7ed8\u5236\u56fe\u8868<\/h4>\n<\/p>\n
    Seaborn\u80fd\u591f\u8f7b\u677e\u521b\u5efa\u5e26\u6709\u7edf\u8ba1\u4fe1\u606f\u7684\u56fe\u8868\u3002<\/p>\n<\/p>\n
    import seaborn as sns<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u51c6\u5907\u6570\u636e<\/strong><\/h2>\n
    tips = sns.load_dataset('tips')<\/p>\n
    \u4f7f\u7528Seaborn\u7ed8\u5236\u7bb1\u7ebf\u56fe<\/strong><\/h2>\n
    sns.boxplot(x='day', y='total_bill', data=tips)<\/p>\n
    \u6dfb\u52a0\u6807\u9898<\/strong><\/h2>\n
    plt.title('Seaborn\u7bb1\u7ebf\u56fe\u793a\u4f8b')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e03\u3001PLOTLY\u5e93\u7684\u4f7f\u7528<\/h3>\n<\/p>\n
    Plotly\u662f\u4e00\u4e2a\u7528\u4e8e\u5236\u4f5c\u4ea4\u4e92\u5f0f\u56fe\u8868\u7684\u5e93\uff0c\u7279\u522b\u9002\u5408\u9700\u8981\u5728\u7f51\u9875\u4e2d\u5c55\u793a\u7684\u573a\u5408\u3002<\/p>\n<\/p>\n
    1\u3001\u5b89\u88c5\u548c\u5bfc\u5165Plotly<\/h4>\n<\/p>\n
    \u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5Plotly\uff1a<\/p>\n<\/p>\n
    pip install plotly<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u7136\u540e\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165Plotly\uff1a<\/p>\n<\/p>\n
    import plotly.express as px<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2\u3001\u4f7f\u7528Plotly\u7ed8\u5236\u4ea4\u4e92\u5f0f\u56fe\u8868<\/h4>\n<\/p>\n
    Plotly\u4f7f\u5f97\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u8868\u53d8\u5f97\u7b80\u5355\u3002<\/p>\n<\/p>\n
    import plotly.express as px<\/p>\n
    \u51c6\u5907\u6570\u636e<\/strong><\/h2>\n
    df = px.data.iris()<\/p>\n
    \u4f7f\u7528Plotly\u7ed8\u5236\u6563\u70b9\u56fe<\/strong><\/h2>\n
    fig = px.scatter(df, x='sepal_width', y='sepal_length', color='species')<\/p>\n
    \u663e\u793a\u56fe\u8868<\/strong><\/h2>\n
    fig.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u901a\u8fc7\u4ee5\u4e0a\u5185\u5bb9\uff0c\u53ef\u4ee5\u770b\u51faPython\u63d0\u4f9b\u4e86\u591a\u79cd\u5f3a\u5927\u7684\u5de5\u5177\u6765\u5236\u4f5c\u56fe\u8868\u3002\u65e0\u8bba\u662f\u7b80\u5355\u7684\u9759\u6001\u56fe\u8868\u8fd8\u662f\u590d\u6742\u7684\u4ea4\u4e92\u5f0f\u56fe\u8868\uff0cPython\u90fd\u80fd\u901a\u8fc7\u4e30\u5bcc\u7684\u5e93\u652f\u6301\u6765\u5b9e\u73b0\u3002\u8fd9\u4f7f\u5f97Python\u6210\u4e3a\u6570\u636e\u53ef\u89c6\u5316\u9886\u57df\u7684\u4e00\u4e2a\u91cd\u8981\u5de5\u5177\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u4f7f\u7528Python\u5e93\u7ed8\u5236\u56fe\u8868\uff1f<\/strong>
    Python\u6709\u591a\u4e2a\u5f3a\u5927\u7684\u5e93\u53ef\u7528\u4e8e\u7ed8\u5236\u56fe\u8868\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684\u662fMatplotlib\u3001Seaborn\u548cPlotly\u3002Matplotlib\u662f\u57fa\u7840\u5e93\uff0c\u9002\u5408\u521b\u5efa\u9759\u6001\u56fe\u8868\uff1bSeaborn\u5728Matplotlib\u7684\u57fa\u7840\u4e0a\u63d0\u4f9b\u4e86\u66f4\u7f8e\u89c2\u7684\u7edf\u8ba1\u56fe\u8868\uff1b\u800cPlotly\u5219\u9002\u5408\u5236\u4f5c\u4ea4\u4e92\u5f0f\u56fe\u8868\u3002\u6839\u636e\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528\u7b80\u5355\u7684\u4ee3\u7801\u5feb\u901f\u751f\u6210\u5404\u79cd\u56fe\u8868\u3002<\/p>\n
    Python\u7ed8\u5236\u56fe\u8868\u7684\u57fa\u672c\u6b65\u9aa4\u662f\u4ec0\u4e48\uff1f<\/strong>
    \u7ed8\u5236\u56fe\u8868\u7684\u57fa\u672c\u6b65\u9aa4\u901a\u5e38\u5305\u62ec\uff1a\u5bfc\u5165\u6240\u9700\u7684\u5e93\u3001\u51c6\u5907\u6570\u636e\u3001\u9009\u62e9\u56fe\u8868\u7c7b\u578b\u3001\u521b\u5efa\u56fe\u8868\u5bf9\u8c61\u5e76\u7ed8\u5236\u3001\u6700\u540e\u663e\u793a\u56fe\u8868\u3002\u4ee5Matplotlib\u4e3a\u4f8b\uff0c\u901a\u5e38\u4f1a\u5148\u4f7f\u7528import matplotlib.pyplot as plt<\/code>\u5bfc\u5165\u5e93\uff0c\u63a5\u7740\u4f7f\u7528plt.plot()<\/code>\u7b49\u51fd\u6570\u7ed8\u5236\u6240\u9700\u56fe\u8868\uff0c\u6700\u540e\u8c03\u7528plt.show()<\/code>\u5c55\u793a\u7ed3\u679c\u3002<\/p>\n
    \u5982\u4f55\u5728Python\u4e2d\u7f8e\u5316\u56fe\u8868\uff1f<\/strong>
    \u7f8e\u5316\u56fe\u8868\u53ef\u4ee5\u901a\u8fc7\u8c03\u6574\u56fe\u8868\u7684\u6837\u5f0f\u3001\u989c\u8272\u3001\u5b57\u4f53\u548c\u6807\u7b7e\u7b49\u6765\u5b9e\u73b0\u3002\u4f7f\u7528Matplotlib\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7plt.style.use()<\/code>\u9009\u62e9\u4e0d\u540c\u7684\u9884\u8bbe\u6837\u5f0f\uff0c\u4f7f\u7528plt.title()<\/code>\u3001plt.xlabel()<\/code>\u548cplt.ylabel()<\/code>\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e\u3002\u6b64\u5916\uff0cSeaborn\u63d0\u4f9b\u4e86\u66f4\u9ad8\u7ea7\u7684\u7f8e\u5316\u529f\u80fd\uff0c\u5982\u914d\u8272\u65b9\u6848\u548c\u4e3b\u9898\u8bbe\u7f6e\uff0c\u4f7f\u5f97\u56fe\u8868\u66f4\u52a0\u5438\u5f15\u4eba\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u5236\u4f5c\u56fe\u8868\u7684\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u5229\u7528Seaborn\u5e93\u3001\u901a\u8fc7Plotly\u5e93\u3001\u5229\u7528 […]","protected":false},"author":3,"featured_media":978616,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/978611"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=978611"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/978611\/revisions"}],"predecessor-version":[{"id":978617,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/978611\/revisions\/978617"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/978616"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=978611"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=978611"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=978611"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}