{"id":1077842,"date":"2025-01-08T12:06:02","date_gmt":"2025-01-08T04:06:02","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1077842.html"},"modified":"2025-01-08T12:06:04","modified_gmt":"2025-01-08T04:06:04","slug":"python%e4%b8%ad%e5%a6%82%e4%bd%95%e5%b0%86%e6%95%a3%e7%82%b9%e8%bf%9e%e7%ba%bf-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1077842.html","title":{"rendered":"python\u4e2d\u5982\u4f55\u5c06\u6563\u70b9\u8fde\u7ebf"},"content":{"rendered":"

\"python\u4e2d\u5982\u4f55\u5c06\u6563\u70b9\u8fde\u7ebf\"<\/p>\n

\u5728Python\u4e2d\uff0c\u5c06\u6563\u70b9\u8fde\u7ebf\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u4e3b\u8981\u5305\u62ec\u4f7f\u7528Matplotlib\u3001Seaborn\u3001Plotly\u7b49\u5e93\u6765\u5b9e\u73b0\u3002Matplotlib\u662f\u6700\u5e38\u7528\u7684\u5e93\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u9002\u5408\u5404\u79cd\u7c7b\u578b\u7684\u6570\u636e\u53ef\u89c6\u5316\u9700\u6c42\u3002<\/strong><\/p>\n<\/p>\n

\u4f7f\u7528Matplotlib\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf\u662f\u6700\u5e38\u89c1\u7684\u505a\u6cd5\u4e4b\u4e00\u3002\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5\u5e76\u5bfc\u5165Matplotlib\u5e93\uff0c\u7136\u540e\u751f\u6210\u6570\u636e\u5e76\u7ed8\u5236\u6563\u70b9\u56fe\uff0c\u6700\u540e\u901a\u8fc7\u6dfb\u52a0\u7ebf\u6761\u5b9e\u73b0\u8fde\u7ebf\u6548\u679c\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Matplotlib\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf<\/h3>\n<\/p>\n

Matplotlib\u662f\u4e00\u4e2a\u5f3a\u5927\u7684Python\u7ed8\u56fe\u5e93\uff0c\u9002\u7528\u4e8e2D\u56fe\u5f62\u7684\u7ed8\u5236\u3002\u4ee5\u4e0b\u6b65\u9aa4\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u4f7f\u7528Matplotlib\u5c06\u6563\u70b9\u8fde\u7ebf\u3002<\/p>\n<\/p>\n

1. \u5b89\u88c5\u4e0e\u5bfc\u5165Matplotlib\u5e93<\/h4>\n<\/p>\n

\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86Matplotlib\u5e93\u3002\u5982\u679c\u5c1a\u672a\u5b89\u88c5\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
\u63a5\u4e0b\u6765\uff0c\u5728\u4f60\u7684Python\u811a\u672c\u6216Jupyter Notebook\u4e2d\u5bfc\u5165\u8be5\u5e93\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import numpy as np<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u751f\u6210\u6570\u636e<\/h4>\n<\/p>\n
\u4e3a\u4e86\u7ed8\u5236\u6563\u70b9\u56fe\uff0c\u6211\u4eec\u9700\u8981\u4e00\u4e9b\u6570\u636e\u3002\u8fd9\u91cc\u6211\u4eec\u4f7f\u7528NumPy\u6765\u751f\u6210\u4e00\u4e9b\u968f\u673a\u6570\u636e\uff1a<\/p>\n<\/p>\n
# \u751f\u6210\u968f\u673a\u6570\u636e<\/p>\n
x = np.linspace(0, 10, 100)<\/p>\n
y = np.sin(x)<\/p>\n
\u6216\u8005\u4f7f\u7528\u5b9e\u9645\u6570\u636e<\/strong><\/h2>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf<\/h4>\n<\/p>\n
\u4f7f\u7528Matplotlib\u7684scatter<\/code>\u51fd\u6570\u7ed8\u5236\u6563\u70b9\u56fe\uff0c\u4f7f\u7528plot<\/code>\u51fd\u6570\u7ed8\u5236\u8fde\u7ebf\uff1a<\/p>\n<\/p>\n
plt.scatter(x, y, label='Scatter Points')<\/p>\n
plt.plot(x, y, label='Line Connection', color='r')<\/p>\n
plt.xlabel('X-axis')<\/p>\n
plt.ylabel('Y-axis')<\/p>\n
plt.title('Scatter Plot with Line Connection')<\/p>\n
plt.legend()<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528Seaborn\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf<\/h3>\n<\/p>\n
Seaborn\u662f\u57fa\u4e8eMatplotlib\u7684\u9ad8\u7ea7\u63a5\u53e3\uff0c\u63d0\u4f9b\u4e86\u66f4\u7f8e\u89c2\u7684\u56fe\u5f62\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Seaborn\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n
1. \u5b89\u88c5\u4e0e\u5bfc\u5165Seaborn\u5e93<\/h4>\n<\/p>\n
\u5982\u679c\u5c1a\u672a\u5b89\u88c5Seaborn\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install seaborn<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u5728\u4f60\u7684Python\u811a\u672c\u6216Jupyter Notebook\u4e2d\u5bfc\u5165\u8be5\u5e93\uff1a<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import numpy as np<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u751f\u6210\u6570\u636e<\/h4>\n<\/p>\n
\u4e0e\u4e4b\u524d\u76f8\u540c\uff0c\u6211\u4eec\u4f7f\u7528NumPy\u751f\u6210\u4e00\u4e9b\u968f\u673a\u6570\u636e\uff1a<\/p>\n<\/p>\n
# \u751f\u6210\u968f\u673a\u6570\u636e<\/p>\n
x = np.linspace(0, 10, 100)<\/p>\n
y = np.sin(x)<\/p>\n
\u6216\u8005\u4f7f\u7528\u5b9e\u9645\u6570\u636e<\/strong><\/h2>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf<\/h4>\n<\/p>\n
\u4f7f\u7528Seaborn\u7684scatterplot<\/code>\u51fd\u6570\u7ed8\u5236\u6563\u70b9\u56fe\uff0c\u4f7f\u7528lineplot<\/code>\u51fd\u6570\u7ed8\u5236\u8fde\u7ebf\uff1a<\/p>\n<\/p>\n
sns.scatterplot(x=x, y=y, label='Scatter Points')<\/p>\n
sns.lineplot(x=x, y=y, label='Line Connection', color='r')<\/p>\n
plt.xlabel('X-axis')<\/p>\n
plt.ylabel('Y-axis')<\/p>\n
plt.title('Scatter Plot with Line Connection using Seaborn')<\/p>\n
plt.legend()<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Plotly\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf<\/h3>\n<\/p>\n
Plotly\u662f\u4e00\u4e2a\u4ea4\u4e92\u5f0f\u7ed8\u56fe\u5e93\uff0c\u9002\u7528\u4e8e\u521b\u5efa\u9ad8\u5ea6\u4e92\u52a8\u7684\u56fe\u5f62\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Plotly\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf\u7684\u65b9\u6cd5\uff1a<\/p>\n<\/p>\n
1. \u5b89\u88c5\u4e0e\u5bfc\u5165Plotly\u5e93<\/h4>\n<\/p>\n
\u5982\u679c\u5c1a\u672a\u5b89\u88c5Plotly\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install plotly<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u5728\u4f60\u7684Python\u811a\u672c\u6216Jupyter Notebook\u4e2d\u5bfc\u5165\u8be5\u5e93\uff1a<\/p>\n<\/p>\n
import plotly.graph_objects as go<\/p>\n
import numpy as np<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u751f\u6210\u6570\u636e<\/h4>\n<\/p>\n
\u4e0e\u4e4b\u524d\u76f8\u540c\uff0c\u6211\u4eec\u4f7f\u7528NumPy\u751f\u6210\u4e00\u4e9b\u968f\u673a\u6570\u636e\uff1a<\/p>\n<\/p>\n
# \u751f\u6210\u968f\u673a\u6570\u636e<\/p>\n
x = np.linspace(0, 10, 100)<\/p>\n
y = np.sin(x)<\/p>\n
\u6216\u8005\u4f7f\u7528\u5b9e\u9645\u6570\u636e<\/strong><\/h2>\n
x = [1, 2, 3, 4, 5]<\/p>\n
y = [2, 3, 5, 7, 11]<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf<\/h4>\n<\/p>\n
\u4f7f\u7528Plotly\u7684Scatter<\/code>\u51fd\u6570\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf\uff1a<\/p>\n<\/p>\n
fig = go.Figure()<\/p>\n
\u6dfb\u52a0\u6563\u70b9\u56fe<\/strong><\/h2>\n
fig.add_trace(go.Scatter(x=x, y=y, mode='markers', name='Scatter Points'))<\/p>\n
\u6dfb\u52a0\u8fde\u7ebf<\/strong><\/h2>\n
fig.add_trace(go.Scatter(x=x, y=y, mode='lines', name='Line Connection', line=dict(color='red')))<\/p>\n
fig.update_layout(title='Scatter Plot with Line Connection using Plotly',<\/p>\n
                  xaxis_title='X-axis',<\/p>\n
                  yaxis_title='Y-axis')<\/p>\n
fig.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528Pandas\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf<\/h3>\n<\/p>\n
Pandas\u5e93\u4e5f\u53ef\u4ee5\u7528\u4e8e\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf\uff0c\u7279\u522b\u662f\u5f53\u6570\u636e\u5b58\u50a8\u5728DataFrame\u4e2d\u65f6\u3002<\/p>\n<\/p>\n
1. \u5b89\u88c5\u4e0e\u5bfc\u5165Pandas\u5e93<\/h4>\n<\/p>\n
\u5982\u679c\u5c1a\u672a\u5b89\u88c5Pandas\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u5728\u4f60\u7684Python\u811a\u672c\u6216Jupyter Notebook\u4e2d\u5bfc\u5165\u8be5\u5e93\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u751f\u6210\u6570\u636e\u5e76\u521b\u5efaDataFrame<\/h4>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Pandas\u521b\u5efa\u4e00\u4e2aDataFrame\u6765\u5b58\u50a8\u6570\u636e\uff1a<\/p>\n<\/p>\n
# \u521b\u5efa\u6570\u636e<\/p>\n
data = {<\/p>\n
    'x': [1, 2, 3, 4, 5],<\/p>\n
    'y': [2, 3, 5, 7, 11]<\/p>\n
}<\/p>\n
\u521b\u5efaDataFrame<\/strong><\/h2>\n
df = pd.DataFrame(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf<\/h4>\n<\/p>\n
\u4f7f\u7528Pandas\u7684plot<\/code>\u51fd\u6570\u7ed8\u5236\u6563\u70b9\u56fe\u5e76\u8fde\u7ebf\uff1a<\/p>\n<\/p>\n
ax = df.plot.scatter(x='x', y='y', label='Scatter Points')<\/p>\n
df.plot.line(x='x', y='y', ax=ax, label='Line Connection', color='r')<\/p>\n
plt.xlabel('X-axis')<\/p>\n
plt.ylabel('Y-axis')<\/p>\n
plt.title('Scatter Plot with Line Connection using Pandas')<\/p>\n
plt.legend()<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u5728Python\u4e2d\uff0c\u5c06\u6563\u70b9\u8fde\u7ebf\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u6700\u5e38\u7528\u7684\u662fMatplotlib\u3002\u6b64\u5916\uff0cSeaborn\u3001Plotly\u548cPandas\u4e5f\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\u3002<\/p>\n<\/p>\n
Matplotlib<\/strong>\uff1a\u9002\u7528\u4e8e\u5927\u591a\u65702D\u7ed8\u56fe\u9700\u6c42\uff0c\u529f\u80fd\u5168\u9762\u3002<\/p>\n<\/p>\n
Seaborn<\/strong>\uff1a\u57fa\u4e8eMatplotlib\uff0c\u63d0\u4f9b\u66f4\u7f8e\u89c2\u7684\u56fe\u5f62\uff0c\u9002\u5408\u7edf\u8ba1\u6570\u636e\u7684\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
Plotly<\/strong>\uff1a\u9002\u7528\u4e8e\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff0c\u80fd\u591f\u521b\u5efa\u9ad8\u5ea6\u4e92\u52a8\u7684\u56fe\u8868\u3002<\/p>\n<\/p>\n
Pandas<\/strong>\uff1a\u9002\u7528\u4e8e\u6570\u636e\u5b58\u50a8\u5728DataFrame\u4e2d\u7684\u60c5\u51b5\uff0c\u65b9\u4fbf\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u7ed8\u56fe\u3002<\/p>\n<\/p>\n
\u65e0\u8bba\u9009\u62e9\u54ea\u79cd\u5e93\uff0c\u90fd\u53ef\u4ee5\u5b9e\u73b0\u5c06\u6563\u70b9\u8fde\u7ebf\u7684\u6548\u679c\u3002\u901a\u8fc7\u5bf9\u8fd9\u4e9b\u5e93\u7684\u5b66\u4e60\u548c\u5b9e\u8df5\uff0c\u53ef\u4ee5\u66f4\u597d\u5730\u6ee1\u8db3\u6570\u636e\u53ef\u89c6\u5316\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528matplotlib\u7ed8\u5236\u8fde\u7ebf\u7684\u6563\u70b9\u56fe\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u4f7f\u7528matplotlib\u5e93\u53ef\u4ee5\u8f7b\u677e\u7ed8\u5236\u8fde\u7ebf\u7684\u6563\u70b9\u56fe\u3002\u9996\u5148\uff0c\u786e\u4fdd\u5b89\u88c5\u4e86matplotlib\u5e93\u3002\u63a5\u7740\uff0c\u53ef\u4ee5\u4f7f\u7528plt.scatter()<\/code>\u51fd\u6570\u7ed8\u5236\u6563\u70b9\uff0c\u7136\u540e\u4f7f\u7528plt.plot()<\/code>\u51fd\u6570\u5c06\u8fd9\u4e9b\u70b9\u8fde\u63a5\u8d77\u6765\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
import matplotlib.pyplot as plt\n\n# \u793a\u4f8b\u6570\u636e\nx = [1, 2, 3, 4, 5]\ny = [2, 3, 5, 7, 11]\n\n# \u7ed8\u5236\u6563\u70b9\nplt.scatter(x, y)\n\n# \u8fde\u63a5\u6563\u70b9\nplt.plot(x, y)\n\nplt.title("Scatter Plot with Lines")\nplt.xlabel("X-axis")\nplt.ylabel("Y-axis")\nplt.show()\n<\/code><\/pre>\n
\u8fd9\u6837\u5c31\u53ef\u4ee5\u5f97\u5230\u4e00\u4e2a\u5305\u542b\u8fde\u7ebf\u7684\u6563\u70b9\u56fe\u3002<\/p>\n
\u5728\u7ed8\u5236\u6563\u70b9\u56fe\u65f6\uff0c\u5982\u4f55\u81ea\u5b9a\u4e49\u7ebf\u6761\u7684\u6837\u5f0f\u548c\u989c\u8272\uff1f<\/strong>
\u5728\u4f7f\u7528plt.plot()<\/code>\u51fd\u6570\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u53c2\u6570\u81ea\u5b9a\u4e49\u7ebf\u6761\u7684\u6837\u5f0f\u548c\u989c\u8272\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528color<\/code>\u53c2\u6570\u8bbe\u7f6e\u989c\u8272\uff0c\u4f7f\u7528linestyle<\/code>\u53c2\u6570\u8bbe\u7f6e\u7ebf\u6761\u6837\u5f0f\uff08\u5982\u865a\u7ebf\u3001\u70b9\u7ebf\u7b49\uff09\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a  <\/p>\n
plt.plot(x, y, color='red', linestyle='--', linewidth=2)\n<\/code><\/pre>\n
\u8fd9\u5c06\u7ed8\u5236\u4e00\u6761\u7ea2\u8272\u7684\u865a\u7ebf\uff0c\u5bbd\u5ea6\u4e3a2\u4e2a\u50cf\u7d20\u3002<\/p>\n
\u5982\u4f55\u5728\u6563\u70b9\u56fe\u4e2d\u6dfb\u52a0\u6807\u7b7e\u548c\u56fe\u4f8b\uff1f<\/strong>
\u6dfb\u52a0\u6807\u7b7e\u548c\u56fe\u4f8b\u53ef\u4ee5\u5e2e\u52a9\u66f4\u597d\u5730\u7406\u89e3\u56fe\u8868\u3002\u5728\u7ed8\u5236\u6563\u70b9\u548c\u8fde\u7ebf\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528label<\/code>\u53c2\u6570\u4e3a\u6bcf\u4e2a\u7cfb\u5217\u6dfb\u52a0\u6807\u7b7e\u3002\u4f7f\u7528plt.legend()<\/code>\u51fd\u6570\u53ef\u4ee5\u663e\u793a\u56fe\u4f8b\u3002\u4f8b\u5982\uff1a  <\/p>\n
plt.scatter(x, y, label='Data Points')\nplt.plot(x, y, label='Connecting Line', color='red')\nplt.legend()\n<\/code><\/pre>\n
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