{"id":981620,"date":"2024-12-27T07:04:06","date_gmt":"2024-12-26T23:04:06","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/981620.html"},"modified":"2024-12-27T07:04:09","modified_gmt":"2024-12-26T23:04:09","slug":"%e5%a6%82%e4%bd%95%e7%bb%98%e5%88%b6%e6%b2%b3%e6%b5%81%e5%9b%bepython","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/981620.html","title":{"rendered":"\u5982\u4f55\u7ed8\u5236\u6cb3\u6d41\u56fePython"},"content":{"rendered":"

\"\u5982\u4f55\u7ed8\u5236\u6cb3\u6d41\u56fePython\"<\/p>\n

\u4f7f\u7528Python\u7ed8\u5236\u6cb3\u6d41\u56fe\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5b9e\u73b0\uff0c\u4e3b\u8981\u5de5\u5177\u5305\u62ecMatplotlib\u3001Plotly\u3001\u4ee5\u53ca\u7b2c\u4e09\u65b9\u5e93\u5982Sankey\u7b49\u3002\u8fd9\u4e9b\u5de5\u5177\u63d0\u4f9b\u4e86\u4e0d\u540c\u7684\u529f\u80fd\u548c\u7075\u6d3b\u6027\uff0c\u53ef\u4ee5\u6839\u636e\u9700\u8981\u9009\u62e9\u3002Matplotlib\u9002\u5408\u7ed8\u5236\u9759\u6001\u56fe\u5f62\u3001Plotly\u9002\u5408\u4ea4\u4e92\u5f0f\u56fe\u5f62\u3001Sankey\u4e13\u6ce8\u4e8e\u6d41\u7a0b\u56fe\u548c\u6cb3\u6d41\u56fe\u3002\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528Matplotlib\u5e93\u7ed8\u5236\u6cb3\u6d41\u56fe\u7684\u8be6\u7ec6\u6b65\u9aa4\u3002<\/strong><\/p>\n<\/p>\n

\u4e00\u3001\u5b89\u88c5\u4e0e\u5bfc\u5165\u5fc5\u8981\u5e93<\/p>\n<\/p>\n

\u5728\u5f00\u59cb\u7ed8\u5236\u6cb3\u6d41\u56fe\u4e4b\u524d\uff0c\u786e\u4fdd\u5df2\u5b89\u88c5\u5fc5\u8981\u7684Python\u5e93\u3002\u901a\u5e38\uff0cMatplotlib\u548cPandas\u662f\u5e38\u7528\u7684\u5de5\u5177\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install matplotlib pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165\u8fd9\u4e9b\u5e93\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u51c6\u5907\u6570\u636e<\/p>\n<\/p>\n
\u7ed8\u5236\u6cb3\u6d41\u56fe\u7684\u7b2c\u4e00\u6b65\u662f\u51c6\u5907\u6570\u636e\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u6570\u636e\u96c6\uff0c\u5305\u542b\u4e0d\u540c\u6cb3\u6d41\u6bb5\u7684\u6d41\u91cf\u6570\u636e\u3002\u4e3a\u4e86\u7b80\u5355\u8d77\u89c1\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u521b\u5efa\u4e00\u4e2a\u793a\u4f8b\u6570\u636e\u6846\uff1a<\/p>\n<\/p>\n
data = {<\/p>\n
    'Segment': ['A', 'B', 'C', 'D'],<\/p>\n
    'Flow': [100, 150, 200, 250]<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u7ed8\u5236\u57fa\u7840\u6cb3\u6d41\u56fe<\/p>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u4f7f\u7528Matplotlib\u7ed8\u5236\u6cb3\u6d41\u56fe\u3002Matplotlib\u7684\u57fa\u7840\u7ed8\u56fe\u529f\u80fd\u53ef\u4ee5\u5b9e\u73b0\u7b80\u5355\u7684\u6761\u5f62\u56fe\uff0c\u8fd9\u53ef\u4ee5\u7528\u4f5c\u6cb3\u6d41\u56fe\u7684\u57fa\u7840\u3002<\/p>\n<\/p>\n
plt.figure(figsize=(10, 6))<\/p>\n
plt.bar(df['Segment'], df['Flow'], color='blue')<\/p>\n
plt.xlabel('River Segment')<\/p>\n
plt.ylabel('Flow (cubic meters per second)')<\/p>\n
plt.title('River Flow by Segment')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4e30\u5bcc\u6cb3\u6d41\u56fe\u7684\u7ec6\u8282<\/p>\n<\/p>\n
\u4e3a\u4e86\u8ba9\u6cb3\u6d41\u56fe\u66f4\u5177\u8868\u73b0\u529b\uff0c\u53ef\u4ee5\u6dfb\u52a0\u4e00\u4e9b\u7ec6\u8282\uff0c\u6bd4\u5982\u4e0d\u540c\u989c\u8272\u7684\u586b\u5145\u3001\u6e10\u53d8\u6548\u679c\u7b49\u3002\u53ef\u4ee5\u901a\u8fc7\u8c03\u6574Matplotlib\u7684\u53c2\u6570\u548c\u6837\u5f0f\u6765\u5b9e\u73b0\uff1a<\/p>\n<\/p>\n
colors = ['#69b3a2', '#404080', '#e0e0e0', '#ffcccb']<\/p>\n
plt.bar(df['Segment'], df['Flow'], color=colors)<\/p>\n
plt.xlabel('River Segment')<\/p>\n
plt.ylabel('Flow (cubic meters per second)')<\/p>\n
plt.title('River Flow by Segment with Colors')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u6dfb\u52a0\u6ce8\u91ca\u548c\u6807\u7b7e<\/p>\n<\/p>\n
\u4e3a\u4e86\u66f4\u597d\u5730\u89e3\u91ca\u56fe\u4e2d\u7684\u4fe1\u606f\uff0c\u53ef\u4ee5\u5728\u56fe\u4e0a\u6dfb\u52a0\u6ce8\u91ca\u548c\u6807\u7b7e\u3002\u8fd9\u6837\u53ef\u4ee5\u63d0\u9ad8\u56fe\u8868\u7684\u53ef\u8bfb\u6027\u548c\u4fe1\u606f\u4f20\u8fbe\u6548\u7387\u3002<\/p>\n<\/p>\n
plt.figure(figsize=(10, 6))<\/p>\n
bars = plt.bar(df['Segment'], df['Flow'], color=colors)<\/p>\n
plt.xlabel('River Segment')<\/p>\n
plt.ylabel('Flow (cubic meters per second)')<\/p>\n
plt.title('Annotated River Flow by Segment')<\/p>\n
\u6dfb\u52a0\u6570\u636e\u6807\u7b7e<\/strong><\/h2>\n
for bar in bars:<\/p>\n
    yval = bar.get_height()<\/p>\n
    plt.text(bar.get_x() + bar.get_width()\/2, yval, round(yval, 2), va='bottom') <\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u4f7f\u7528Plotly\u7ed8\u5236\u4ea4\u4e92\u5f0f\u6cb3\u6d41\u56fe<\/p>\n<\/p>\n
\u5982\u679c\u5e0c\u671b\u521b\u5efa\u4ea4\u4e92\u5f0f\u6cb3\u6d41\u56fe\uff0c\u53ef\u4ee5\u4f7f\u7528Plotly\u5e93\u3002Plotly\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u4ea4\u4e92\u529f\u80fd\u548c\u7f8e\u89c2\u7684\u56fe\u5f62\u3002<\/p>\n<\/p>\n
\u9996\u5148\uff0c\u5b89\u88c5Plotly\uff1a<\/p>\n<\/p>\n
pip install plotly<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u4f7f\u7528Plotly\u7ed8\u5236\u56fe\u5f62\uff1a<\/p>\n<\/p>\n
import plotly.express as px<\/p>\n
fig = px.bar(df, x='Segment', y='Flow', title='Interactive River Flow by Segment')<\/p>\n
fig.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u4f7f\u7528Sankey\u5e93\u7ed8\u5236\u590d\u6742\u6cb3\u6d41\u56fe<\/p>\n<\/p>\n
\u5bf9\u4e8e\u590d\u6742\u7684\u6cb3\u6d41\u56fe\uff08\u4f8b\u5982\u8868\u793a\u6d41\u52a8\u8fc7\u7a0b\u7684\u56fe\u8868\uff09\uff0cSankey\u5e93\u662f\u4e00\u4e2a\u7406\u60f3\u7684\u9009\u62e9\u3002Sankey\u56fe\u53ef\u4ee5\u6709\u6548\u5730\u663e\u793a\u591a\u4e2a\u6e90\u548c\u76ee\u6807\u4e4b\u95f4\u7684\u6d41\u52a8\u5173\u7cfb\u3002<\/p>\n<\/p>\n
\u5b89\u88c5Sankey\u5e93\uff1a<\/p>\n<\/p>\n
pip install plotly<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7ed8\u5236Sankey\u56fe\uff1a<\/p>\n<\/p>\n
import plotly.graph_objects as go<\/p>\n
fig = go.Figure(go.Sankey(<\/p>\n
    node=dict(<\/p>\n
        pad=15,<\/p>\n
        thickness=20,<\/p>\n
        line=dict(color="black", width=0.5),<\/p>\n
        label=["Source 1", "Source 2", "Target 1", "Target 2"],<\/p>\n
    ),<\/p>\n
    link=dict(<\/p>\n
        source=[0, 1, 0, 2, 3, 3],<\/p>\n
        target=[2, 3, 3, 4, 4, 5],<\/p>\n
        value=[8, 4, 2, 8, 4, 2]<\/p>\n
    )<\/p>\n
))<\/p>\n
fig.update_layout(title_text="Sankey Diagram Example", font_size=10)<\/p>\n
fig.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528Python\u7ed8\u5236\u7b80\u5355\u5230\u590d\u6742\u7684\u6cb3\u6d41\u56fe\u3002\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u548c\u5e93\uff0c\u80fd\u591f\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u5c55\u793a\u6570\u636e\u7684\u6d41\u52a8\u548c\u5206\u5e03\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u83b7\u53d6\u6cb3\u6d41\u56fe\u7684\u6570\u636e\u6e90\uff1f<\/strong>
\u5728\u7ed8\u5236\u6cb3\u6d41\u56fe\u4e4b\u524d\uff0c\u9700\u8981\u83b7\u53d6\u76f8\u5173\u7684\u6570\u636e\u6e90\u3002\u53ef\u4ee5\u4f7f\u7528\u516c\u5f00\u7684\u5730\u7406\u4fe1\u606f\u7cfb\u7edf\uff08GIS\uff09\u6570\u636e\uff0c\u6216\u901a\u8fc7API\u4ece\u653f\u5e9c\u548c\u73af\u5883\u673a\u6784\u83b7\u53d6\u6cb3\u6d41\u6570\u636e\u3002\u5e38\u89c1\u7684\u6570\u636e\u6e90\u5305\u62ecOpenStreetMap\u3001USGS\uff08\u7f8e\u56fd\u5730\u8d28\u8c03\u67e5\u5c40\uff09\u548c\u5404\u56fd\u7684\u5730\u7406\u4fe1\u606f\u670d\u52a1\u5e73\u53f0\u3002\u8fd9\u4e9b\u6570\u636e\u901a\u5e38\u4ee5CSV\u3001GeoJSON\u6216Shapefile\u683c\u5f0f\u63d0\u4f9b\uff0c\u9002\u5408\u540e\u7eed\u5904\u7406\u3002<\/p>\n
\u6709\u54ea\u4e9bPython\u5e93\u53ef\u4ee5\u5e2e\u52a9\u7ed8\u5236\u6cb3\u6d41\u56fe\uff1f<\/strong>
\u7ed8\u5236\u6cb3\u6d41\u56fe\u53ef\u4ee5\u4f7f\u7528\u591a\u4e2aPython\u5e93\uff0c\u4f8b\u5982Matplotlib\u3001Seaborn\u548cPlotly\u7b49\u3002\u8fd9\u4e9b\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u4f7f\u5f97\u6570\u636e\u53ef\u89c6\u5316\u66f4\u52a0\u76f4\u89c2\u3002\u5bf9\u4e8e\u5730\u7406\u6570\u636e\uff0cGeopandas\u548cFolium\u662f\u975e\u5e38\u6709\u7528\u7684\u5de5\u5177\uff0c\u80fd\u591f\u5904\u7406\u5730\u7406\u4fe1\u606f\u5e76\u751f\u6210\u6f02\u4eae\u7684\u5730\u56fe\u3002\u6b64\u5916\uff0cBasemap\u4e5f\u662f\u4e00\u4e2a\u7ecf\u5178\u7684\u9009\u62e9\uff0c\u4f46\u5b83\u7684\u4f7f\u7528\u9010\u6e10\u88ab\u5176\u4ed6\u5e93\u53d6\u4ee3\u3002<\/p>\n
\u6cb3\u6d41\u56fe\u7ed8\u5236\u8fc7\u7a0b\u4e2d\u5e38\u89c1\u7684\u95ee\u9898\u53ca\u89e3\u51b3\u65b9\u6cd5\u6709\u54ea\u4e9b\uff1f<\/strong>
\u5728\u7ed8\u5236\u6cb3\u6d41\u56fe\u7684\u8fc7\u7a0b\u4e2d\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u6570\u636e\u683c\u5f0f\u4e0d\u517c\u5bb9\u3001\u7ed8\u5236\u6548\u679c\u4e0d\u7406\u60f3\u7b49\u95ee\u9898\u3002\u786e\u4fdd\u6570\u636e\u6e05\u6d17\u548c\u9884\u5904\u7406\u5de5\u4f5c\u5230\u4f4d\u662f\u5173\u952e\uff0c\u4f7f\u7528Pandas\u5e93\u6765\u5904\u7406\u6570\u636e\u53ef\u4ee5\u6709\u6548\u51cf\u5c11\u8fd9\u4e9b\u95ee\u9898\u3002\u6b64\u5916\uff0c\u9009\u62e9\u5408\u9002\u7684\u7ed8\u56fe\u53c2\u6570\u548c\u6837\u5f0f\u4e5f\u662f\u91cd\u8981\u7684\u4e00\u73af\u3002\u5982\u679c\u9047\u5230\u7ed8\u56fe\u7ed3\u679c\u4e0d\u5982\u9884\u671f\uff0c\u53ef\u4ee5\u5c1d\u8bd5\u8c03\u6574\u989c\u8272\u3001\u7ebf\u5bbd\u4ee5\u53ca\u56fe\u4f8b\u8bbe\u7f6e\uff0c\u4ee5\u63d0\u5347\u53ef\u8bfb\u6027\u548c\u7f8e\u89c2\u5ea6\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u4f7f\u7528Python\u7ed8\u5236\u6cb3\u6d41\u56fe\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5b9e\u73b0\uff0c\u4e3b\u8981\u5de5\u5177\u5305\u62ecMatplotlib\u3001Plotly\u3001\u4ee5\u53ca\u7b2c\u4e09\u65b9\u5e93\u5982 […]","protected":false},"author":3,"featured_media":981630,"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\/981620"}],"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=981620"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/981620\/revisions"}],"predecessor-version":[{"id":981633,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/981620\/revisions\/981633"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/981630"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=981620"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=981620"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=981620"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}