![\"python\u6570\u636e\u5982\u4f55\u53ef\u89c6\u5316\"](\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25202741\/27ba3b98-c6de-4bb6-8ecd-58577fde8be0.webp\")
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\u5728Python\u4e2d\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u7684\u6838\u5fc3\u8981\u70b9\u5305\u62ec\uff1a\u9009\u62e9\u5408\u9002\u7684\u53ef\u89c6\u5316\u5e93\u3001\u7406\u89e3\u6570\u636e\u7684\u7ed3\u6784\u4e0e\u7279\u6027\u3001\u9009\u62e9\u9002\u5f53\u7684\u56fe\u8868\u7c7b\u578b\u3001\u638c\u63e1\u57fa\u672c\u7684\u53ef\u89c6\u5316\u6280\u672f\u3001\u7ed3\u5408\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u5de5\u5177<\/strong>\u3002\u5176\u4e2d\uff0c\u9009\u62e9\u5408\u9002\u7684\u53ef\u89c6\u5316\u5e93\u662f\u975e\u5e38\u5173\u952e\u7684\uff0c\u56e0\u4e3a\u4e0d\u540c\u7684\u5e93\u6709\u4e0d\u540c\u7684\u7279\u6027\u548c\u7528\u9014\u3002\u5e38\u89c1\u7684\u53ef\u89c6\u5316\u5e93\u6709Matplotlib\u3001Seaborn\u3001Plotly\u3001Bokeh\u7b49\u3002\u4e0b\u9762\u6211\u4eec\u5c06\u6df1\u5165\u63a2\u8ba8\u5982\u4f55\u5728Python\u4e2d\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n Python\u4e2d\u6709\u8bb8\u591a\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\u7684\u5e93\uff0c\u6bcf\u4e2a\u5e93\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002<\/p>\n<\/p>\n Matplotlib<\/strong> \u662fPython\u4e2d\u6700\u57fa\u7840\u4e14\u529f\u80fd\u5f3a\u5927\u7684\u53ef\u89c6\u5316\u5e93\uff0c\u9002\u7528\u4e8e\u5404\u79cd\u57fa\u672c\u56fe\u8868\u7684\u7ed8\u5236\u3002\u5b83\u7684\u4e3b\u8981\u7279\u70b9\u662f\uff1a<\/p>\n<\/p>\n x = [1, 2, 3, 4, 5]<\/p>\n y = [1, 4, 9, 16, 25]<\/p>\n plt.plot(x, y)<\/p>\n plt.xlabel('X\u8f74')<\/p>\n plt.ylabel('Y\u8f74')<\/p>\n plt.title('\u7b80\u5355\u6298\u7ebf\u56fe')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n Seaborn<\/strong> \u662f\u57fa\u4e8eMatplotlib\u7684\u9ad8\u7ea7\u53ef\u89c6\u5316\u5e93\uff0c\u9002\u7528\u4e8e\u7edf\u8ba1\u56fe\u8868\u7684\u7ed8\u5236\u3002\u5b83\u7684\u4e3b\u8981\u7279\u70b9\u662f\uff1a<\/p>\n<\/p>\n import matplotlib.pyplot as plt<\/p>\n tips = sns.load_dataset('tips')<\/p>\n sns.scatterplot(x='total_bill', y='tip', data=tips)<\/p>\n plt.title('\u603b\u8d26\u5355\u4e0e\u5c0f\u8d39\u7684\u5173\u7cfb')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n Plotly<\/strong> \u662f\u4e00\u4e2a\u652f\u6301\u4ea4\u4e92\u5f0f\u56fe\u8868\u7684\u5e93\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8eWeb\u5e94\u7528\u548c\u4eea\u8868\u76d8\u3002\u5b83\u7684\u4e3b\u8981\u7279\u70b9\u662f\uff1a<\/p>\n<\/p>\n df = px.data.iris()<\/p>\n fig = px.scatter(df, x='sepal_width', y='sepal_length', color='species')<\/p>\n fig.show()<\/p>\n <\/code><\/pre>\n<\/p>\n Bokeh<\/strong> \u662f\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u5e93\uff0c\u9002\u5408\u7528\u4e8e\u521b\u5efa\u7f51\u7edc\u5e94\u7528\u4e2d\u7684\u52a8\u6001\u56fe\u8868\u3002\u5b83\u7684\u4e3b\u8981\u7279\u70b9\u662f\uff1a<\/p>\n<\/p>\n from bokeh.io import output_notebook<\/p>\n output_notebook()<\/p>\n p = figure(title="\u7b80\u5355\u6298\u7ebf\u56fe", x_axis_label='X\u8f74', y_axis_label='Y\u8f74')<\/p>\n p.line([1, 2, 3, 4, 5], [1, 4, 9, 16, 25], legend_label="\u6298\u7ebf", line_width=2)<\/p>\n show(p)<\/p>\n <\/code><\/pre>\n<\/p>\n \u5728\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u4e4b\u524d\uff0c\u7406\u89e3\u6570\u636e\u7684\u7ed3\u6784\u4e0e\u7279\u6027\u662f\u81f3\u5173\u91cd\u8981\u7684\u3002\u8fd9\u5305\u62ec\u6570\u636e\u7684\u7c7b\u578b\u3001\u5206\u5e03\u3001\u76f8\u5173\u6027\u7b49\u65b9\u9762\u3002<\/p>\n<\/p>\n \u6570\u636e\u7c7b\u578b\u51b3\u5b9a\u4e86\u6211\u4eec\u5e94\u8be5\u5982\u4f55\u5bf9\u6570\u636e\u8fdb\u884c\u5904\u7406\u548c\u5c55\u793a\u3002\u5e38\u89c1\u7684\u6570\u636e\u7c7b\u578b\u5305\u62ec\u6570\u503c\u578b\u3001\u5206\u7c7b\u578b\u548c\u65f6\u95f4\u5e8f\u5217\u578b\u3002<\/p>\n<\/p>\n \u4e86\u89e3\u6570\u636e\u7684\u5206\u5e03\u60c5\u51b5\u6709\u52a9\u4e8e\u9009\u62e9\u5408\u9002\u7684\u53ef\u89c6\u5316\u65b9\u6cd5\u3002\u5e38\u89c1\u7684\u5206\u5e03\u7c7b\u578b\u6709\u6b63\u6001\u5206\u5e03\u3001\u5747\u5300\u5206\u5e03\u3001\u6307\u6570\u5206\u5e03\u7b49\u3002<\/p>\n<\/p>\n \u6570\u636e\u4e4b\u95f4\u7684\u76f8\u5173\u6027\u53ef\u4ee5\u901a\u8fc7\u6563\u70b9\u56fe\u3001\u70ed\u529b\u56fe\u7b49\u8fdb\u884c\u5c55\u793a\u3002<\/p>\n<\/p>\n \u9009\u62e9\u9002\u5f53\u7684\u56fe\u8868\u7c7b\u578b\u662f\u6570\u636e\u53ef\u89c6\u5316\u7684\u5173\u952e\u6b65\u9aa4\u3002\u4e0d\u540c\u7684\u56fe\u8868\u7c7b\u578b\u9002\u7528\u4e8e\u4e0d\u540c\u7684\u6570\u636e\u548c\u5c55\u793a\u76ee\u7684\u3002<\/p>\n<\/p>\n \u6298\u7ebf\u56fe<\/strong> \u9002\u7528\u4e8e\u5c55\u793a\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u6216\u8fde\u7eed\u53d8\u5316\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n x = [1, 2, 3, 4, 5]<\/p>\n y = [1, 4, 9, 16, 25]<\/p>\n plt.plot(x, y)<\/p>\n plt.xlabel('X\u8f74')<\/p>\n plt.ylabel('Y\u8f74')<\/p>\n plt.title('\u6298\u7ebf\u56fe')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n \u67f1\u72b6\u56fe<\/strong> \u9002\u7528\u4e8e\u5c55\u793a\u5206\u7c7b\u6570\u636e\u7684\u6bd4\u8f83\u3002<\/p>\n<\/p>\n categories = ['A', 'B', 'C', 'D', 'E']<\/p>\n values = [5, 7, 3, 8, 4]<\/p>\n plt.bar(categories, values)<\/p>\n plt.xlabel('\u7c7b\u522b')<\/p>\n plt.ylabel('\u503c')<\/p>\n plt.title('\u67f1\u72b6\u56fe')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n \u6563\u70b9\u56fe<\/strong> \u9002\u7528\u4e8e\u5c55\u793a\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/p>\n<\/p>\n x = [1, 2, 3, 4, 5]<\/p>\n y = [1, 4, 9, 16, 25]<\/p>\n plt.scatter(x, y)<\/p>\n plt.xlabel('X\u8f74')<\/p>\n plt.ylabel('Y\u8f74')<\/p>\n plt.title('\u6563\u70b9\u56fe')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n \u997c\u56fe<\/strong> \u9002\u7528\u4e8e\u5c55\u793a\u5206\u7c7b\u6570\u636e\u7684\u6bd4\u4f8b\u3002<\/p>\n<\/p>\n labels = ['A', 'B', 'C', 'D']<\/p>\n sizes = [15, 30, 45, 10]<\/p>\n plt.pie(sizes, labels=labels, autopct='%1.1f%%')<\/p>\n plt.title('\u997c\u56fe')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n \u638c\u63e1\u57fa\u672c\u7684\u53ef\u89c6\u5316\u6280\u672f\u80fd\u591f\u5e2e\u52a9\u6211\u4eec\u66f4\u597d\u5730\u5c55\u793a\u6570\u636e\u3002<\/p>\n<\/p>\n \u4e3a\u56fe\u8868\u8bbe\u7f6e\u6807\u9898\u548c\u6807\u7b7e\u80fd\u591f\u8ba9\u89c2\u4f17\u66f4\u5bb9\u6613\u7406\u89e3\u56fe\u8868\u7684\u5185\u5bb9\u3002<\/p>\n<\/p>\n x = [1, 2, 3, 4, 5]<\/p>\n y = [1, 4, 9, 16, 25]<\/p>\n plt.plot(x, y)<\/p>\n plt.xlabel('X\u8f74')<\/p>\n plt.ylabel('Y\u8f74')<\/p>\n plt.title('\u6298\u7ebf\u56fe')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n \u56fe\u4f8b\u80fd\u591f\u5e2e\u52a9\u89c2\u4f17\u7406\u89e3\u56fe\u8868\u4e2d\u4e0d\u540c\u5143\u7d20\u7684\u542b\u4e49\u3002<\/p>\n<\/p>\n x = [1, 2, 3, 4, 5]<\/p>\n y1 = [1, 4, 9, 16, 25]<\/p>\n y2 = [2, 3, 4, 5, 6]<\/p>\n plt.plot(x, y1, label='\u6570\u636e1')<\/p>\n plt.plot(x, y2, label='\u6570\u636e2')<\/p>\n plt.xlabel('X\u8f74')<\/p>\n plt.ylabel('Y\u8f74')<\/p>\n plt.title('\u6298\u7ebf\u56fe')<\/p>\n plt.legend()<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n \u8bbe\u7f6e\u56fe\u8868\u6837\u5f0f\u80fd\u591f\u63d0\u9ad8\u56fe\u8868\u7684\u7f8e\u89c2\u6027\u548c\u53ef\u8bfb\u6027\u3002<\/p>\n<\/p>\n x = [1, 2, 3, 4, 5]<\/p>\n y = [1, 4, 9, 16, 25]<\/p>\n plt.plot(x, y, 'o-', color='red') # \u4f7f\u7528\u7ea2\u8272\u5706\u70b9\u7ebf<\/p>\n plt.xlabel('X\u8f74')<\/p>\n plt.ylabel('Y\u8f74')<\/p>\n plt.title('\u6298\u7ebf\u56fe')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n \u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u5de5\u5177\u80fd\u591f\u63d0\u4f9b\u66f4\u4e30\u5bcc\u7684\u7528\u6237\u4f53\u9a8c\uff0c\u9002\u7528\u4e8e\u6570\u636e\u5206\u6790\u548c\u5c55\u793a\u3002<\/p>\n<\/p>\n Plotly \u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u5e93\uff0c\u80fd\u591f\u521b\u5efa\u4e30\u5bcc\u7684\u4ea4\u4e92\u5f0f\u56fe\u8868\u3002<\/p>\n<\/p>\n df = px.data.iris()<\/p>\n fig = px.scatter(df, x='sepal_width', y='sepal_length', color='species')<\/p>\n fig.show()<\/p>\n <\/code><\/pre>\n<\/p>\n Bokeh \u662f\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u5e93\uff0c\u80fd\u591f\u521b\u5efa\u52a8\u6001\u56fe\u8868\u3002<\/p>\n<\/p>\n from bokeh.io import output_notebook<\/p>\n output_notebook()<\/p>\n p = figure(title="\u7b80\u5355\u6298\u7ebf\u56fe", x_axis_label='X\u8f74', y_axis_label='Y\u8f74')<\/p>\n p.line([1, 2, 3, 4, 5], [1, 4, 9, 16, 25], legend_label="\u6298\u7ebf", line_width=2)<\/p>\n show(p)<\/p>\n <\/code><\/pre>\n<\/p>\n Dash \u662f\u4e00\u4e2a\u57fa\u4e8ePlotly\u7684Web\u5e94\u7528\u6846\u67b6\uff0c\u80fd\u591f\u521b\u5efa\u4ea4\u4e92\u5f0f\u4eea\u8868\u76d8\u3002<\/p>\n<\/p>\n import dash_core_components as dcc<\/p>\n import dash_html_components as html<\/p>\n import plotly.express as px<\/p>\n app = dash.Dash(__name__)<\/p>\n df = px.data.iris()<\/p>\n app.layout = html.Div(children=[<\/p>\n html.H1(children='\u4ea4\u4e92\u5f0f\u4eea\u8868\u76d8'),<\/p>\n dcc.Graph(<\/p>\n id='example-graph',<\/p>\n figure=px.scatter(df, x='sepal_width', y='sepal_length', color='species')<\/p>\n )<\/p>\n ])<\/p>\n\u4e00\u3001\u9009\u62e9\u5408\u9002\u7684\u53ef\u89c6\u5316\u5e93<\/strong><\/h2>\n
1\u3001Matplotlib<\/h3>\n<\/p>\n
\n
import matplotlib.pyplot as plt<\/p>\n\u7b80\u5355\u7684\u6298\u7ebf\u56fe<\/strong><\/h2>\n
2\u3001Seaborn<\/h3>\n<\/p>\n
\n
import seaborn as sns<\/p>\n\u7ed8\u5236\u6563\u70b9\u56fe<\/strong><\/h2>\n
3\u3001Plotly<\/h3>\n<\/p>\n
\n
import plotly.express as px<\/p>\n\u7ed8\u5236\u4ea4\u4e92\u5f0f\u6563\u70b9\u56fe<\/strong><\/h2>\n
4\u3001Bokeh<\/h3>\n<\/p>\n
\n
from bokeh.plotting import figure, show<\/p>\n\u521b\u5efa\u7b80\u5355\u7684\u6298\u7ebf\u56fe<\/strong><\/h2>\n
\u4e8c\u3001\u7406\u89e3\u6570\u636e\u7684\u7ed3\u6784\u4e0e\u7279\u6027<\/strong><\/h2>\n
1\u3001\u6570\u636e\u7c7b\u578b<\/h3>\n<\/p>\n
\n
2\u3001\u6570\u636e\u5206\u5e03<\/h3>\n<\/p>\n
\n
3\u3001\u6570\u636e\u76f8\u5173\u6027<\/h3>\n<\/p>\n
\n
\u4e09\u3001\u9009\u62e9\u9002\u5f53\u7684\u56fe\u8868\u7c7b\u578b<\/strong><\/h2>\n
1\u3001\u6298\u7ebf\u56fe<\/h3>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n\u7ed8\u5236\u7b80\u5355\u7684\u6298\u7ebf\u56fe<\/strong><\/h2>\n
2\u3001\u67f1\u72b6\u56fe<\/h3>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n\u7ed8\u5236\u7b80\u5355\u7684\u67f1\u72b6\u56fe<\/strong><\/h2>\n
3\u3001\u6563\u70b9\u56fe<\/h3>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n\u7ed8\u5236\u7b80\u5355\u7684\u6563\u70b9\u56fe<\/strong><\/h2>\n
4\u3001\u997c\u56fe<\/h3>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n\u7ed8\u5236\u7b80\u5355\u7684\u997c\u56fe<\/strong><\/h2>\n
\u56db\u3001\u638c\u63e1\u57fa\u672c\u7684\u53ef\u89c6\u5316\u6280\u672f<\/strong><\/h2>\n
1\u3001\u8bbe\u7f6e\u56fe\u8868\u6807\u9898\u548c\u6807\u7b7e<\/h3>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n2\u3001\u6dfb\u52a0\u56fe\u4f8b<\/h3>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n3\u3001\u8bbe\u7f6e\u56fe\u8868\u6837\u5f0f<\/h3>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n\u4e94\u3001\u7ed3\u5408\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316\u5de5\u5177<\/strong><\/h2>\n
1\u3001\u4f7f\u7528Plotly\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u8868<\/h3>\n<\/p>\n
import plotly.express as px<\/p>\n\u521b\u5efa\u4ea4\u4e92\u5f0f\u6563\u70b9\u56fe<\/strong><\/h2>\n
2\u3001\u4f7f\u7528Bokeh\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u8868<\/h3>\n<\/p>\n
from bokeh.plotting import figure, show<\/p>\n\u521b\u5efa\u7b80\u5355\u7684\u6298\u7ebf\u56fe<\/strong><\/h2>\n
3\u3001\u4f7f\u7528Dash\u521b\u5efa\u4ea4\u4e92\u5f0f\u4eea\u8868\u76d8<\/h3>\n<\/p>\n
import dash<\/p>\n\u521b\u5efaDash\u5e94\u7528<\/strong><\/h2>\n
\u52a0\u8f7d\u6570\u636e<\/strong><\/h2>\n
\u5b9a\u4e49\u5e03\u5c40<\/strong><\/h2>\n
\u8fd0\u884c\u5e94\u7528<\/strong><\/h2>\n