{"id":2649,"date":"2025-08-07T07:25:46","date_gmt":"2025-08-06T23:25:46","guid":{"rendered":"https:\/\/www.ddosidc.com\/wp\/?p=2649"},"modified":"2025-08-07T07:25:46","modified_gmt":"2025-08-06T23:25:46","slug":"%e6%80%8e%e4%b9%88%e7%94%a8python%e5%a4%84%e7%90%86excel%e6%95%b0%e6%8d%ae%e4%bb%a5%e6%8f%90%e5%8d%87%e6%95%88%e7%8e%87%e5%92%8c%e5%87%86%e7%a1%ae%e6%80%a7","status":"publish","type":"post","link":"https:\/\/www.ddosidc.com\/wp\/2649.html","title":{"rendered":"\u600e\u4e48\u7528Python\u5904\u7406Excel\u6570\u636e\u4ee5\u63d0\u5347\u6548\u7387\u548c\u51c6\u786e\u6027"},"content":{"rendered":"

\"\u600e\u4e48\u7528Python\u5904\u7406Excel\u6570\u636e\u4ee5\u63d0\u5347\u6548\u7387\u548c\u51c6\u786e\u6027\"<\/p>\n

1. \u600e\u4e48\u7528Python\u5904\u7406Excel\u6570\u636e<\/h3>\n<\/p>\n

Python\u5904\u7406Excel\u6570\u636e\u76f8\u5bf9\u7b80\u5355\uff0c\u4e3b\u8981\u4f9d\u9760\u4e00\u4e9b\u5f3a\u5927\u7684\u5e93\uff0c\u5982Pandas\u548cOpenPyXL\u3002\u8fd9\u4e9b\u5e93\u53ef\u4ee5\u8ba9\u4f60\u8f7b\u677e\u8bfb\u53d6\u3001\u4fee\u6539\u548c\u4fdd\u5b58Excel\u6587\u4ef6\u3002\u4f7f\u7528Pandas\u5e93\uff0c\u4f60\u53ef\u4ee5\u52a0\u8f7dExcel\u6570\u636e\u4e3aDataFrame\uff0c\u5e76\u8fdb\u884c\u5404\u79cd\u6570\u636e\u64cd\u4f5c\uff0c\u4f8b\u5982\u8fc7\u6ee4\u3001\u5206\u7ec4\u548c\u805a\u5408\uff0c\u800cOpenPyXL\u4e3b\u8981\u7528\u4e8e\u76f4\u63a5\u64cd\u4f5cExcel\u6587\u4ef6\u7684\u5355\u5143\u683c\u3002\u9009\u62e9\u4f7f\u7528\u54ea\u4e2a\u5e93\u53d6\u51b3\u4e8e\u5177\u4f53\u9700\u6c42\uff0c\u6bd4\u5982Pandas\u9002\u5408\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\uff0c\u800cOpenPyXL\u66f4\u9002\u5408\u5bf9Excel\u683c\u5f0f\u53ca\u7c7b\u578b\u7684\u63a7\u5236\u3002<\/p>\n<\/p>\n

\n

2. \u6570\u636e\u52a0\u8f7d<\/h3>\n<\/p>\n

\u9996\u5148\uff0c\u4f60\u9700\u8981\u5b89\u88c5\u76f8\u5e94\u7684\u5e93\uff0c\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u8f7b\u677e\u5b8c\u6210\u3002\u4ee5\u4e0b\u662f\u5b89\u88c5Pandas\u548cOpenPyXL\u7684\u547d\u4ee4\uff1a<\/p>\n

<\/p>\r\n
pip install pandas openpyxl<\/p>\r\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u4f60\u53ef\u4ee5\u5f00\u59cb\u52a0\u8f7dExcel\u6587\u4ef6\uff1a<\/p>\n
<\/p>\r\n
import pandas as pd<\/p>\r\n\r\n
# \u52a0\u8f7dExcel\u6587\u4ef6<\/p>\r\n
df = pd.read_excel('your_file.xlsx', sheet_name='Sheet1')<\/p>\r\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u91cc\uff0c\u901a\u8fc7\u6307\u5b9asheet_name\u53c2\u6570\u6765\u9009\u62e9\u4f60\u8981\u5904\u7406\u7684\u5de5\u4f5c\u8868\u3002\u4f60\u8fd8\u53ef\u4ee5\u901a\u8fc7\u53c2\u6570\u63a7\u5236\u52a0\u8f7d\u7684\u6570\u636e\u8303\u56f4\u6216\u6570\u636e\u7c7b\u578b\u3002<\/p>\n<\/p>\n
\n
3. \u6570\u636e\u5904\u7406<\/h3>\n<\/p>\n
\u8f7d\u5165\u6570\u636e\u540e\uff0c\u4f60\u53ef\u4ee5\u6267\u884c\u5404\u79cd\u64cd\u4f5c\u3002\u6bd4\u5982\uff0c\u67e5\u770b\u6570\u636e\u7684\u57fa\u672c\u4fe1\u606f\uff1a<\/p>\n
<\/p>\r\n
print(df.info())<\/p>\r\n
print(df.describe())<\/p>\r\n
<\/code><\/pre>\n<\/p>\n
\u4f60\u53ef\u4ee5\u5feb\u901f\u4e86\u89e3\u5230\u6570\u636e\u7684\u7ed3\u6784\u3001\u7f3a\u5931\u503c\u3001\u6570\u636e\u7c7b\u578b\u7b49\u3002\u5982\u679c\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u6e05\u6d17\uff0c\u6bd4\u5982\u53bb\u9664\u7f3a\u5931\u503c\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n
<\/p>\r\n
df.dropna(inplace=True)<\/p>\r\n
<\/code><\/pre>\n<\/p>\n
\u6b64\u5916\uff0cPandas\u8fd8\u652f\u6301\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u65b9\u6cd5\uff0c\u4f8b\u5982\u6570\u636e\u7b5b\u9009\u3001\u6392\u5e8f\u548c\u5408\u5e76\u7b49\u3002<\/p>\n<\/p>\n
\n
4. \u6570\u636e\u5206\u6790<\/h3>\n<\/p>\n
\u5bf9\u4e8e\u5206\u6790\u6570\u636e\uff0cPandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u3002\u4f8b\u5982\uff0c\u4f60\u53ef\u4ee5\u901a\u8fc7groupby\u65b9\u6cd5\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\u5206\u6790\uff1a<\/p>\n
<\/p>\r\n
grouped_data = df.groupby('column_name').sum()<\/p>\r\n
print(grouped_data)<\/p>\r\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u6837\u53ef\u4ee5\u6839\u636e\u67d0\u5217\u7684\u4e0d\u540c\u503c\u6c47\u603b\u5176\u5b83\u5217\u7684\u6570\u636e\u3002\u4f60\u8fd8\u53ef\u4ee5\u8fdb\u884c\u6570\u636e\u900f\u89c6\u8868\u7684\u751f\u6210\uff0c\u6765\u5bf9\u6570\u636e\u8fdb\u884c\u66f4\u5168\u9762\u7684\u5206\u6790\uff0c\u4f7f\u7528pivot_table\u65b9\u6cd5\uff1a<\/p>\n
<\/p>\r\n
pivot_table = df.pivot_table(index='column1', columns='column2', values='column3', aggfunc='sum')<\/p>\r\n
print(pivot_table)<\/p>\r\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u6837\u7684\u65b9\u5f0f\uff0c\u4f60\u53ef\u4ee5\u8f7b\u677e\u5f97\u51fa\u6570\u636e\u7684\u8d8b\u52bf\u548c\u89c4\u5f8b\u3002<\/p>\n<\/p>\n
\n
5. \u6570\u636e\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
\u53ef\u89c6\u5316\u662f\u4e00\u79cd\u76f4\u89c2\u5c55\u73b0\u6570\u636e\u7684\u65b9\u6cd5\u3002Pandas\u53ef\u4ee5\u4e0eMatplotlib\u548cSeaborn\u7b49\u5e93\u7ed3\u5408\u4f7f\u7528\uff0c\u751f\u6210\u5404\u79cd\u56fe\u8868\u3002\u6bd4\u5982\uff0c\u4f60\u53ef\u4ee5\u7528\u4ee5\u4e0b\u547d\u4ee4\u751f\u6210\u7b80\u5355\u7684\u6298\u7ebf\u56fe\uff1a<\/p>\n
<\/p>\r\n
import matplotlib.pyplot as plt<\/p>\r\n\r\n
df.plot(x='date_column', y='value_column')<\/p>\r\n
plt.title('Data Trend')<\/p>\r\n
plt.show()<\/p>\r\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528\u8fd9\u4e9b\u5e93\uff0c\u80fd\u66f4\u597d\u5730\u5e2e\u52a9\u4f60\u7406\u89e3\u6570\u636e\u5e76\u4f20\u8fbe\u4fe1\u606f\u3002<\/p>\n<\/p>\n
\n
6. \u56fe\u8868\u4e0e\u683c\u5f0f\u5904\u7406<\/h3>\n<\/p>\n
\u5982\u679c\u4f60\u9700\u8981\u751f\u6210\u590d\u6742\u56fe\u8868\uff0cOpenPyXL\u53ef\u4ee5\u5e2e\u52a9\u4f60\u5bf9Excel\u6587\u4ef6\u8fdb\u884c\u66f4\u6df1\u5165\u7684\u683c\u5f0f\u5904\u7406\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u521b\u5efa\u56fe\u8868\uff1a<\/p>\n
<\/p>\r\n
from openpyxl import Workbook<\/p>\r\n
from openpyxl.chart import BarChart, Reference<\/p>\r\n\r\n
wb = Workbook()<\/p>\r\n
ws = wb.active<\/p>\r\n
# \u5047\u8bbe\u6570\u636e\u5df2\u7ecf\u586b\u5145\u5230\u5de5\u4f5c\u8868<\/p>\r\n
chart = BarChart()<\/p>\r\n
data = Reference(ws, min_col=2, min_row=1, max_col=3, max_row=10)<\/p>\r\n
chart.add_data(data, titles_from_data=True)<\/p>\r\n
ws.add_chart(chart, \"E5\")<\/p>\r\n
wb.save(\"chart_example.xlsx\")<\/p>\r\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u4e2a\u4ee3\u7801\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728Excel\u4e2d\u521b\u5efa\u4e00\u4e2a\u7b80\u5355\u7684\u67f1\u72b6\u56fe\u3002<\/p>\n<\/p>\n
\n
7. \u4e3a\u4ec0\u4e48\u9009\u62e9\u7528Python\u5904\u7406Excel\u6570\u636e<\/h3>\n<\/p>\n
Python\u662f\u5904\u7406Excel\u6570\u636e\u7684\u7406\u60f3\u9009\u62e9\uff0c\u4e3b\u8981\u662f\u56e0\u4e3a\u5176\u529f\u80fd\u5f3a\u5927\u3001\u5b66\u4e60\u66f2\u7ebf\u5e73\u7f13\u4ee5\u53ca\u4e30\u5bcc\u7684\u793e\u533a\u652f\u6301\u3002Pandas\u548cOpenPyXL\u7b49\u5e93\uff0c\u8ba9\u6570\u636e\u79d1\u5b66\u5bb6\u548c\u5206\u6790\u5e08\u80fd\u591f\u5feb\u901f\u3001\u6709\u6548\u5730\u5904\u7406\u5927\u91cf\u6570\u636e\u3002\u6b64\u5916\uff0cPython\u7684\u7075\u6d3b\u6027\u4f7f\u5176\u53ef\u4ee5\u4e0e\u5176\u4ed6\u6280\u672f\u65e0\u7f1d\u96c6\u6210\uff0c\u63d0\u9ad8\u4e86\u5de5\u4f5c\u6548\u7387\u3002\u5c24\u5176\u5728\u6570\u636e\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60\u9886\u57df\uff0cPython\u4f7f\u7528\u5e7f\u6cdb\uff0c\u80fd\u591f\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u9884\u5904\u7406\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n
\n
8. \u54ea\u4e2a\u5e93\u6bd4\u8f83\u597d\uff1f<\/h3>\n<\/p>\n
\u5728\u9009\u62e9\u5e93\u65f6\uff0cPandas<\/b>\u548cOpenPyXL<\/b>\u5404\u6709\u4f18\u52a3\u3002Pandas\u66f4\u9002\u5408\u9700\u8981\u8fdb\u884c\u5927\u91cf\u6570\u636e\u5904\u7406\u7684\u573a\u666f\uff0c\u5982\u679c\u8981\u8fdb\u884c\u590d\u6742\u7684\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\uff0cPandas\u65e0\u7591\u662f\u9996\u9009\u3002\u800c\u5982\u679c\u4f60\u7684\u4efb\u52a1\u662f\u9488\u5bf9Excel\u6587\u4ef6\u672c\u8eab\u7684\u683c\u5f0f\u3001\u6837\u5f0f\u8fdb\u884c\u64cd\u4f5c\uff0cOpenPyXL\u4f1a\u66f4\u5408\u9002\u3002\u9009\u62e9\u54ea\u4e2a\u5e93\u53d6\u51b3\u4e8e\u4f60\u7684\u5177\u4f53\u9700\u6c42\u548c\u9879\u76ee\u76ee\u6807\u3002<\/p>\n<\/p>\n
\n
9. \u5982\u4f55\u5f00\u59cb\u5b66\u4e60Python\u6570\u636e\u5904\u7406\uff1f<\/h3>\n<\/p>\n
\u5bf9\u65b0\u624b\u6765\u8bf4\uff0c\u5b66\u4e60Python\u6570\u636e\u5904\u7406<\/b>\u7684\u6700\u4f73\u65b9\u5f0f\u662f\u901a\u8fc7\u5b9e\u8df5\u3002\u4f60\u53ef\u4ee5\u4ece\u7b80\u5355\u7684\u64cd\u4f5c\u5f00\u59cb\uff0c\u4f8b\u5982\u8bfb\u53d6Excel\u6587\u4ef6\u5e76\u6253\u5370\u6570\u636e\uff0c\u7136\u540e\u9010\u6b65\u5c1d\u8bd5\u6dfb\u52a0\u6570\u636e\u6e05\u6d17\u3001\u5206\u6790\u548c\u53ef\u89c6\u5316\u7b49\u529f\u80fd\u3002\u5728\u7f51\u4e0a\u6709\u8bb8\u591a\u514d\u8d39\u7684\u6559\u7a0b\u548c\u793a\u4f8b\u4ee3\u7801\uff0c\u53ef\u4ee5\u5e2e\u52a9\u4f60\u5feb\u901f\u5165\u95e8\u3002\u4e0d\u59a8\u627e\u4e9b\u5b9e\u9645\u7684\u6570\u636e\u96c6\uff0c\u8fdb\u884c\u5206\u6790\u7ec3\u4e60\uff0c\u4ee5\u63d0\u9ad8\u4f60\u7684\u6280\u80fd\u548c\u719f\u6089\u5ea6\u3002<\/p>\n<\/p>\n
\n
10. \u5982\u4f55\u63d0\u5347\u5904\u7406Excel\u6570\u636e\u7684\u6548\u7387\uff1f<\/h3>\n<\/p>\n
\u8981\u63d0\u5347\u548c\u4f18\u5316\u5904\u7406Excel\u6570\u636e\u7684\u6548\u7387<\/b>\uff0c\u53ef\u4ee5\u8003\u8651\u4ee5\u4e0b\u51e0\u70b9\uff1a\u9996\u5148\uff0c\u5c3d\u91cf\u51cf\u5c11\u4e0d\u5fc5\u8981\u7684\u6570\u636e\u64cd\u4f5c\uff1b\u5176\u6b21\uff0c\u4f7f\u7528Pandas\u7684\u5411\u91cf\u5316\u64cd\u4f5c\u800c\u4e0d\u662f\u5faa\u73af\u6765\u5904\u7406\u6570\u636e\uff1b\u6700\u540e\uff0c\u5b9a\u671f\u5ba1\u89c6\u548c\u4f18\u5316\u4f60\u7684\u4ee3\u7801\u903b\u8f91\uff0c\u786e\u4fdd\u4f60\u6b63\u5728\u4f7f\u7528\u6700\u6709\u6548\u7684\u5904\u7406\u65b9\u6cd5\u3002\u4f8b\u5982\uff0c\u4f7f\u7528\u94fe\u5f0f\u64cd\u4f5c\u800c\u4e0d\u662f\u591a\u6b65\u5904\u7406\uff0c\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u548c\u6267\u884c\u6548\u7387\u3002<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"
1. \u600e\u4e48\u7528Python\u5904\u7406Excel\u6570\u636e Python\u5904\u7406Excel\u6570\u636e\u76f8\u5bf9\u7b80\u5355\uff0c\u4e3b\u8981\u4f9d\u9760\u4e00\u4e9b\u5f3a\u5927\u7684\u5e93\uff0c\u5982Pandas\u548cOpenPyXL\u3002\u8fd9\u4e9b\u5e93\u53ef\u4ee5\u8ba9\u4f60\u8f7b\u677e\u8bfb\u53d6\u3001\u4fee\u6539\u548c\u4fdd\u5b58Excel\u6587\u4ef6\u3002\u4f7f\u7528Pandas\u5e93\uff0c\u4f60\u53ef\u4ee5\u52a0\u8f7dExcel\u6570\u636e\u4e3aDa…<\/p>\n","protected":false},"author":1,"featured_media":2650,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"topic":[],"class_list":["post-2649","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-baike"],"_links":{"self":[{"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/posts\/2649","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/comments?post=2649"}],"version-history":[{"count":1,"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/posts\/2649\/revisions"}],"predecessor-version":[{"id":2652,"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/posts\/2649\/revisions\/2652"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/media\/2650"}],"wp:attachment":[{"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/media?parent=2649"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/categories?post=2649"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/tags?post=2649"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/www.ddosidc.com\/wp\/wp-json\/wp\/v2\/topic?post=2649"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}