{"id":1181442,"date":"2025-01-15T18:51:23","date_gmt":"2025-01-15T10:51:23","guid":{"rendered":""},"modified":"2025-01-15T18:51:26","modified_gmt":"2025-01-15T10:51:26","slug":"%e5%a6%82%e4%bd%95%e5%9c%a8python%e4%b8%ad%e5%bd%a2%e6%88%90%e5%9b%be%e5%bd%a2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1181442.html","title":{"rendered":"\u5982\u4f55\u5728python\u4e2d\u5f62\u6210\u56fe\u5f62"},"content":{"rendered":"

\"\u5982\u4f55\u5728python\u4e2d\u5f62\u6210\u56fe\u5f62\"<\/p>\n

\u5728Python\u4e2d\u5f62\u6210\u56fe\u5f62\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u4e3b\u8981\u5305\u62ec\u4f7f\u7528Matplotlib\u3001Seaborn\u3001Plotly\u3001Bokeh\u7b49\u5e93\u3002<\/strong> \u5176\u4e2d\uff0cMatplotlib<\/strong> \u662f\u6700\u57fa\u7840\u548c\u5e38\u7528\u7684\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u5e7f\u6cdb\u7684\u529f\u80fd\u6765\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u5f62\uff1bSeaborn<\/strong> \u662f\u57fa\u4e8eMatplotlib\u4e4b\u4e0a\u7684\u4e00\u4e2a\u9ad8\u7ea7\u63a5\u53e3\uff0c\u9002\u5408\u8fdb\u884c\u7edf\u8ba1\u56fe\u5f62\u7684\u7ed8\u5236\uff1bPlotly<\/strong> \u53ef\u4ee5\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff0c\u9002\u7528\u4e8eWeb\u5e94\u7528\uff1bBokeh<\/strong> \u4e5f\u4e13\u6ce8\u4e8e\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff0c\u5e76\u4e14\u53ef\u4ee5\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u96c6\u3002\u4ee5\u4e0b\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Matplotlib\u5e93\u6765\u5f62\u6210\u56fe\u5f62\u3002<\/p>\n<\/p>\n

\u4e00\u3001MATPLOTLIB\u5e93\u7684\u4ecb\u7ecd\u548c\u5b89\u88c5<\/h3>\n<\/p>\n

Matplotlib \u662f Python \u4e2d\u6700\u6d41\u884c\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u5b83\u80fd\u591f\u975e\u5e38\u65b9\u4fbf\u5730\u521b\u5efa\u9759\u6001\u3001\u52a8\u6001\u548c\u4ea4\u4e92\u5f0f\u7684\u56fe\u5f62\u3002Matplotlib \u63d0\u4f9b\u4e86\u4e00\u6574\u5957\u7684\u7ed8\u56fe\u51fd\u6570\uff0c\u9002\u7528\u4e8e\u5404\u79cd\u5e38\u89c1\u7684\u56fe\u8868\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u6563\u70b9\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u997c\u56fe\u7b49\u3002<\/p>\n<\/p>\n

1\u3001\u5b89\u88c5Matplotlib<\/h4>\n<\/p>\n

\u53ef\u4ee5\u901a\u8fc7 pip \u547d\u4ee4\u6765\u5b89\u88c5 Matplotlib\uff1a<\/p>\n<\/p>\n

pip install matplotlib<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001MATPLOTLIB\u7684\u57fa\u672c\u4f7f\u7528<\/h3>\n<\/p>\n
1\u3001\u5bfc\u5165\u5e93\u548c\u7b80\u5355\u7ed8\u56fe<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u9700\u8981\u5bfc\u5165 Matplotlib \u5e93\u4e2d\u7684 pyplot \u6a21\u5757\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u7684\u6298\u7ebf\u56fe\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\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.plot(x, y)<\/p>\n
\u8bbe\u7f6e\u6807\u9898<\/strong><\/h2>\n
plt.title('Simple Line Plot')<\/p>\n
\u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bbe\u7f6e\u56fe\u5f62\u7684\u6807\u9898\u548c\u6807\u7b7e<\/h4>\n<\/p>\n
\u5728\u7ed8\u5236\u56fe\u5f62\u65f6\uff0c\u53ef\u4ee5\u8bbe\u7f6e\u6807\u9898\u3001x\u8f74\u548cy\u8f74\u7684\u6807\u7b7e\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u63cf\u8ff0\u56fe\u5f62\uff1a<\/p>\n<\/p>\n
plt.plot(x, y)<\/p>\n
plt.title('Simple Line Plot')<\/p>\n
plt.xlabel('X Axis')<\/p>\n
plt.ylabel('Y Axis')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001MATPLOTLIB\u7684\u9ad8\u7ea7\u4f7f\u7528<\/h3>\n<\/p>\n
1\u3001\u7ed8\u5236\u591a\u6761\u6298\u7ebf<\/h4>\n<\/p>\n
\u53ef\u4ee5\u5728\u540c\u4e00\u4e2a\u56fe\u5f62\u4e2d\u7ed8\u5236\u591a\u6761\u6298\u7ebf\uff0c\u53ea\u9700\u8981\u591a\u6b21\u8c03\u7528 plot<\/code> \u51fd\u6570\uff1a<\/p>\n<\/p>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y1 = [2, 3, 5, 7, 11]<\/p>\n
y2 = [1, 4, 6, 8, 10]<\/p>\n
plt.plot(x, y1, label='Line 1')<\/p>\n
plt.plot(x, y2, label='Line 2')<\/p>\n
plt.title('Multiple Lines')<\/p>\n
plt.xlabel('X Axis')<\/p>\n
plt.ylabel('Y Axis')<\/p>\n
plt.legend()<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7ed8\u5236\u6563\u70b9\u56fe<\/h4>\n<\/p>\n
\u6563\u70b9\u56fe\u53ef\u4ee5\u7528\u6765\u663e\u793a\u6570\u636e\u70b9\u4e4b\u95f4\u7684\u5173\u7cfb\uff0c\u4f7f\u7528 scatter<\/code> \u51fd\u6570\u53ef\u4ee5\u7ed8\u5236\u6563\u70b9\u56fe\uff1a<\/p>\n<\/p>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
plt.scatter(x, y)<\/p>\n
plt.title('Scatter Plot')<\/p>\n
plt.xlabel('X Axis')<\/p>\n
plt.ylabel('Y Axis')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u7ed8\u5236\u67f1\u72b6\u56fe<\/h4>\n<\/p>\n
\u67f1\u72b6\u56fe\u53ef\u4ee5\u7528\u6765\u6bd4\u8f83\u4e0d\u540c\u7c7b\u522b\u7684\u6570\u636e\uff0c\u4f7f\u7528 bar<\/code> \u51fd\u6570\u53ef\u4ee5\u7ed8\u5236\u67f1\u72b6\u56fe\uff1a<\/p>\n<\/p>\n
categories = ['A', 'B', 'C', 'D', 'E']<\/p>\n
values = [5, 7, 3, 4, 6]<\/p>\n
plt.bar(categories, values)<\/p>\n
plt.title('Bar Chart')<\/p>\n
plt.xlabel('Categories')<\/p>\n
plt.ylabel('Values')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001SEABORN\u5e93\u7684\u4ecb\u7ecd\u548c\u4f7f\u7528<\/h3>\n<\/p>\n
Seaborn \u662f\u4e00\u4e2a\u57fa\u4e8e Matplotlib \u7684\u9ad8\u7ea7\u7ed8\u56fe\u5e93\uff0c\u4e13\u4e3a\u7edf\u8ba1\u6570\u636e\u53ef\u89c6\u5316\u800c\u8bbe\u8ba1\u3002\u5b83\u63d0\u4f9b\u4e86\u66f4\u4e3a\u7b80\u6d01\u7684 API \u548c\u66f4\u4e30\u5bcc\u7684\u56fe\u5f62\u6837\u5f0f\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5Seaborn<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7 pip \u547d\u4ee4\u6765\u5b89\u88c5 Seaborn\uff1a<\/p>\n<\/p>\n
pip install seaborn<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5bfc\u5165\u5e93\u548c\u7b80\u5355\u7ed8\u56fe<\/h4>\n<\/p>\n
\u5bfc\u5165 Seaborn \u5e93\u5e76\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u7684\u6298\u7ebf\u56fe\uff1a<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
sns.lineplot(x=x, y=y)<\/p>\n
plt.title('Simple Line Plot with Seaborn')<\/p>\n
plt.xlabel('X Axis')<\/p>\n
plt.ylabel('Y Axis')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u7ed8\u5236\u7edf\u8ba1\u56fe\u5f62<\/h4>\n<\/p>\n
Seaborn \u63d0\u4f9b\u4e86\u8bb8\u591a\u9ad8\u7ea7\u7edf\u8ba1\u56fe\u5f62\uff0c\u5982\u7bb1\u7ebf\u56fe\u3001\u70ed\u529b\u56fe\u7b49\uff1a<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u751f\u6210\u4e00\u4e9b\u6570\u636e<\/strong><\/h2>\n
data = sns.load_dataset('tips')<\/p>\n
\u7ed8\u5236\u7bb1\u7ebf\u56fe<\/strong><\/h2>\n
sns.boxplot(x='day', y='total_bill', data=data)<\/p>\n
plt.title('Boxplot of Total Bill by Day')<\/p>\n
plt.xlabel('Day')<\/p>\n
plt.ylabel('Total Bill')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001PLOTLY\u5e93\u7684\u4ecb\u7ecd\u548c\u4f7f\u7528<\/h3>\n<\/p>\n
Plotly \u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u7ed8\u56fe\u5e93\uff0c\u4e13\u6ce8\u4e8e\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff0c\u7279\u522b\u9002\u7528\u4e8e Web \u5e94\u7528\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5Plotly<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7 pip \u547d\u4ee4\u6765\u5b89\u88c5 Plotly\uff1a<\/p>\n<\/p>\n
pip install plotly<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5bfc\u5165\u5e93\u548c\u7b80\u5355\u7ed8\u56fe<\/h4>\n<\/p>\n
\u5bfc\u5165 Plotly \u5e93\u5e76\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u7684\u6298\u7ebf\u56fe\uff1a<\/p>\n<\/p>\n
import plotly.graph_objects as go<\/p>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
fig = go.Figure(data=go.Scatter(x=x, y=y, mode='lines'))<\/p>\n
fig.update_layout(title='Simple Line Plot with Plotly',<\/p>\n
                  xaxis_title='X Axis',<\/p>\n
                  yaxis_title='Y Axis')<\/p>\n
fig.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u7ed8\u5236\u4ea4\u4e92\u5f0f\u56fe\u5f62<\/h4>\n<\/p>\n
Plotly \u63d0\u4f9b\u4e86\u8bb8\u591a\u529f\u80fd\u6765\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff1a<\/p>\n<\/p>\n
import plotly.express as px<\/p>\n
\u751f\u6210\u4e00\u4e9b\u6570\u636e<\/strong><\/h2>\n
data = px.data.iris()<\/p>\n
\u7ed8\u5236\u6563\u70b9\u56fe<\/strong><\/h2>\n
fig = px.scatter(data, x='sepal_width', y='sepal_length', color='species')<\/p>\n
fig.update_layout(title='Scatter Plot of Iris Data',<\/p>\n
                  xaxis_title='Sepal Width',<\/p>\n
                  yaxis_title='Sepal Length')<\/p>\n
fig.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001BOKEH\u5e93\u7684\u4ecb\u7ecd\u548c\u4f7f\u7528<\/h3>\n<\/p>\n
Bokeh \u662f\u53e6\u4e00\u4e2a\u4e13\u6ce8\u4e8e\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u5f62\u7684\u5e93\uff0c\u5b83\u80fd\u591f\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u96c6\uff0c\u5e76\u751f\u6210\u9ad8\u6548\u7684 Web \u56fe\u5f62\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5Bokeh<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7 pip \u547d\u4ee4\u6765\u5b89\u88c5 Bokeh\uff1a<\/p>\n<\/p>\n
pip install bokeh<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5bfc\u5165\u5e93\u548c\u7b80\u5355\u7ed8\u56fe<\/h4>\n<\/p>\n
\u5bfc\u5165 Bokeh \u5e93\u5e76\u7ed8\u5236\u4e00\u4e2a\u7b80\u5355\u7684\u6298\u7ebf\u56fe\uff1a<\/p>\n<\/p>\n
from bokeh.plotting import figure, show<\/p>\n
from bokeh.io import output_notebook<\/p>\n
output_notebook()<\/p>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
p = figure(title='Simple Line Plot with Bokeh', x_axis_label='X Axis', y_axis_label='Y Axis')<\/p>\n
p.line(x, y, legend_label='Line', line_width=2)<\/p>\n
show(p)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u7ed8\u5236\u4ea4\u4e92\u5f0f\u56fe\u5f62<\/h4>\n<\/p>\n
Bokeh \u63d0\u4f9b\u4e86\u8bb8\u591a\u529f\u80fd\u6765\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff1a<\/p>\n<\/p>\n
from bokeh.plotting import figure, show<\/p>\n
from bokeh.io import output_notebook<\/p>\n
from bokeh.models import ColumnDataSource, HoverTool<\/p>\n
output_notebook()<\/p>\n
\u751f\u6210\u4e00\u4e9b\u6570\u636e<\/strong><\/h2>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
source = ColumnDataSource(data=dict(x=x, y=y))<\/p>\n
p = figure(title='Interactive Line Plot with Bokeh', x_axis_label='X Axis', y_axis_label='Y Axis')<\/p>\n
p.line('x', 'y', source=source, legend_label='Line', line_width=2)<\/p>\n
hover = HoverTool()<\/p>\n
hover.tooltips = [("X value", "@x"), ("Y value", "@y")]<\/p>\n
p.add_tools(hover)<\/p>\n
show(p)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u5728Python\u4e2d\u5f62\u6210\u56fe\u5f62\u6709\u591a\u79cd\u65b9\u6cd5\uff0c\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u70b9\u548c\u9002\u7528\u573a\u666f\u3002Matplotlib \u662f\u6700\u57fa\u7840\u548c\u5e38\u7528\u7684\u5e93\uff0c\u9002\u5408\u9759\u6001\u56fe\u5f62\u7684\u7ed8\u5236\uff1bSeaborn \u662f\u57fa\u4e8e Matplotlib \u7684\u9ad8\u7ea7\u63a5\u53e3\uff0c\u9002\u5408\u7edf\u8ba1\u56fe\u5f62\u7684\u7ed8\u5236\uff1bPlotly \u548c Bokeh \u4e13\u6ce8\u4e8e\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff0c\u9002\u7528\u4e8e Web \u5e94\u7528\u3002\u6839\u636e\u5177\u4f53\u7684\u9700\u6c42\uff0c\u9009\u62e9\u5408\u9002\u7684\u5e93\u6765\u8fdb\u884c\u56fe\u5f62\u7684\u7ed8\u5236\uff0c\u53ef\u4ee5\u5927\u5927\u63d0\u9ad8\u6570\u636e\u53ef\u89c6\u5316\u7684\u6548\u7387\u548c\u6548\u679c\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u7ed8\u5236\u7b80\u5355\u7684\u56fe\u5f62\uff1f<\/strong>
Python\u63d0\u4f9b\u4e86\u591a\u4e2a\u5e93\u6765\u7ed8\u5236\u56fe\u5f62\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684\u662fMatplotlib\u3002\u4f7f\u7528Matplotlib\uff0c\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u8c03\u7528\u7b80\u5355\u7684\u51fd\u6570\u6765\u7ed8\u5236\u6298\u7ebf\u56fe\u3001\u6563\u70b9\u56fe\u548c\u67f1\u72b6\u56fe\u7b49\u3002\u9996\u5148\uff0c\u5b89\u88c5Matplotlib\u5e93\uff0c\u7136\u540e\u901a\u8fc7\u5bfc\u5165\u8be5\u5e93\u5e76\u4f7f\u7528plt.plot()<\/code>\u7b49\u51fd\u6570\u6765\u521b\u5efa\u6240\u9700\u7684\u56fe\u5f62\u3002\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u56fe\u5f62\u7684\u6807\u9898\u3001\u6807\u7b7e\u548c\u6837\u5f0f\u6765\u589e\u5f3a\u53ef\u89c6\u5316\u6548\u679c\u3002<\/p>\n
\u6709\u54ea\u4e9bPython\u5e93\u9002\u5408\u7ed8\u5236\u590d\u6742\u56fe\u5f62\uff1f<\/strong>
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