{"id":1151443,"date":"2025-01-13T17:13:38","date_gmt":"2025-01-13T09:13:38","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1151443.html"},"modified":"2025-01-13T17:13:41","modified_gmt":"2025-01-13T09:13:41","slug":"python%e5%a6%82%e4%bd%95%e8%ae%be%e7%bd%ae%e8%a1%a8%e6%a0%bc%e8%be%b9%e6%a1%86","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1151443.html","title":{"rendered":"python\u5982\u4f55\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846"},"content":{"rendered":"

\"python\u5982\u4f55\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846\"<\/p>\n

\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846\uff0c\u5305\u62ec\u4f7f\u7528Pandas\u3001Matplotlib\u3001Openpyxl\u7b49\u5e93<\/strong>\u3002\u5176\u4e2d\uff0cPandas\u548cMatplotlib\u5e93\u5e38\u7528\u4e8e\u6570\u636e\u5904\u7406\u548c\u53ef\u89c6\u5316\uff0c\u800cOpenpyxl\u5e93\u5219\u7528\u4e8e\u64cd\u4f5cExcel\u6587\u4ef6\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63a2\u8ba8\u5982\u4f55\u4f7f\u7528\u8fd9\u4e9b\u5e93\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846\uff0c\u5e76\u4ee5Pandas\u548cOpenpyxl\u4e3a\u4f8b\u8fdb\u884c\u8be6\u7ec6\u8bf4\u660e\u3002<\/p>\n<\/p>\n

\u4e00\u3001PANDAS\u5e93\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846<\/p>\n

Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u5b83\u53ef\u4ee5\u65b9\u4fbf\u5730\u8bfb\u53d6\u3001\u5904\u7406\u548c\u8f93\u51fa\u5404\u79cd\u683c\u5f0f\u7684\u6570\u636e\u3002\u5728Pandas\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7Styler<\/code>\u5bf9\u8c61\u6765\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846\u3002<\/p>\n<\/p>\n

1\u3001\u521b\u5efaDataFrame\u548cStyler<\/h3>\n<\/p>\n

\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u4e00\u4e2aDataFrame\u5bf9\u8c61\uff0c\u5e76\u901a\u8fc7Styler<\/code>\u5bf9\u8c61\u6765\u8bbe\u7f6e\u8868\u683c\u6837\u5f0f\u3002<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
\u521b\u5efaDataFrame\u5bf9\u8c61<\/strong><\/h2>\n
df = pd.DataFrame({<\/p>\n
    'A': [1, 2, 3],<\/p>\n
    'B': [4, 5, 6],<\/p>\n
    'C': [7, 8, 9]<\/p>\n
})<\/p>\n
\u83b7\u53d6Styler\u5bf9\u8c61<\/strong><\/h2>\n
styler = df.style<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846<\/h3>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u901a\u8fc7Styler<\/code>\u5bf9\u8c61\u7684set_table_styles<\/code>\u65b9\u6cd5\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846\u3002<\/p>\n<\/p>\n
# \u8bbe\u7f6e\u8868\u683c\u8fb9\u6846<\/p>\n
styler.set_table_styles(<\/p>\n
    [{'selector': 'th',<\/p>\n
      'props': [('border', '1px solid black')]},<\/p>\n
     {'selector': 'td',<\/p>\n
      'props': [('border', '1px solid black')]}]<\/p>\n
)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u663e\u793a\u8868\u683c<\/h3>\n<\/p>\n
\u6700\u540e\uff0c\u901a\u8fc7Jupyter Notebook\u663e\u793a\u5e26\u6709\u8fb9\u6846\u7684\u8868\u683c\u3002<\/p>\n<\/p>\n
styler<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001MATPLOTLIB\u5e93\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846<\/p>\n
Matplotlib\u662f\u4e00\u4e2a\u7ed8\u56fe\u5e93\uff0c\u5b83\u53ef\u4ee5\u751f\u6210\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5305\u62ec\u8868\u683c\u3002\u5728Matplotlib\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7table<\/code>\u65b9\u6cd5\u521b\u5efa\u8868\u683c\uff0c\u5e76\u8bbe\u7f6e\u5176\u8fb9\u6846\u6837\u5f0f\u3002<\/p>\n<\/p>\n
1\u3001\u521b\u5efa\u8868\u683c<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u4f7f\u7528Matplotlib\u5e93\u521b\u5efa\u4e00\u4e2a\u7b80\u5355\u7684\u8868\u683c\u3002<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u521b\u5efa\u6570\u636e<\/strong><\/h2>\n
data = [['A', 'B', 'C'],<\/p>\n
        [1, 2, 3],<\/p>\n
        [4, 5, 6],<\/p>\n
        [7, 8, 9]]<\/p>\n
\u521b\u5efa\u8868\u683c<\/strong><\/h2>\n
fig, ax = plt.subplots()<\/p>\n
ax.axis('tight')<\/p>\n
ax.axis('off')<\/p>\n
table = ax.table(cellText=data, cellLoc='center', loc='center')<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846<\/h3>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u901a\u8fc7table<\/code>\u5bf9\u8c61\u7684set_fontsize<\/code>\u548cscale<\/code>\u65b9\u6cd5\u8bbe\u7f6e\u8868\u683c\u6837\u5f0f\u3002<\/p>\n<\/p>\n
# \u8bbe\u7f6e\u8868\u683c\u8fb9\u6846<\/p>\n
table.auto_set_font_size(False)<\/p>\n
table.set_fontsize(14)<\/p>\n
table.scale(1.5, 1.5)<\/p>\n
\u8bbe\u7f6e\u5355\u5143\u683c\u8fb9\u6846<\/strong><\/h2>\n
for (i, j), cell in table.get_celld().items():<\/p>\n
    cell.set_edgecolor('black')<\/p>\n
    cell.set_linewidth(2)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u663e\u793a\u8868\u683c<\/h3>\n<\/p>\n
\u6700\u540e\uff0c\u901a\u8fc7Matplotlib\u663e\u793a\u5e26\u6709\u8fb9\u6846\u7684\u8868\u683c\u3002<\/p>\n<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001OPENPYXL\u5e93\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846<\/p>\n
Openpyxl\u662f\u4e00\u4e2a\u7528\u4e8e\u8bfb\u53d6\u548c\u5199\u5165Excel\u6587\u4ef6\u7684\u5e93\u3002\u5728Openpyxl\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u5355\u5143\u683c\u7684\u8fb9\u6846\u6837\u5f0f\u6765\u5b9e\u73b0\u8868\u683c\u8fb9\u6846\u7684\u8bbe\u7f6e\u3002<\/p>\n<\/p>\n
1\u3001\u521b\u5efaExcel\u6587\u4ef6<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u4f7f\u7528Openpyxl\u5e93\u521b\u5efa\u4e00\u4e2aExcel\u6587\u4ef6\uff0c\u5e76\u5411\u5176\u4e2d\u5199\u5165\u6570\u636e\u3002<\/p>\n<\/p>\n
from openpyxl import Workbook<\/p>\n
from openpyxl.styles import Border, Side<\/p>\n
\u521b\u5efaWorkbook\u5bf9\u8c61<\/strong><\/h2>\n
wb = Workbook()<\/p>\n
ws = wb.active<\/p>\n
\u5199\u5165\u6570\u636e<\/strong><\/h2>\n
data = [<\/p>\n
    ['A', 'B', 'C'],<\/p>\n
    [1, 2, 3],<\/p>\n
    [4, 5, 6],<\/p>\n
    [7, 8, 9]<\/p>\n
]<\/p>\n
for row in data:<\/p>\n
    ws.append(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bbe\u7f6e\u5355\u5143\u683c\u8fb9\u6846<\/h3>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u901a\u8fc7\u8bbe\u7f6e\u5355\u5143\u683c\u7684\u8fb9\u6846\u6837\u5f0f\u6765\u5b9e\u73b0\u8868\u683c\u8fb9\u6846\u7684\u8bbe\u7f6e\u3002<\/p>\n<\/p>\n
# \u5b9a\u4e49\u8fb9\u6846\u6837\u5f0f<\/p>\n
thin_border = Border(left=Side(style='thin'),<\/p>\n
                     right=Side(style='thin'),<\/p>\n
                     top=Side(style='thin'),<\/p>\n
                     bottom=Side(style='thin'))<\/p>\n
\u8bbe\u7f6e\u5355\u5143\u683c\u8fb9\u6846<\/strong><\/h2>\n
for row in ws.iter_rows(min_row=1, max_row=4, min_col=1, max_col=3):<\/p>\n
    for cell in row:<\/p>\n
        cell.border = thin_border<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u4fdd\u5b58Excel\u6587\u4ef6<\/h3>\n<\/p>\n
\u6700\u540e\uff0c\u5c06\u5e26\u6709\u8fb9\u6846\u7684\u8868\u683c\u4fdd\u5b58\u5230Excel\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n
wb.save('table_with_borders.xlsx')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u8be6\u7ec6\u793a\u4f8b<\/p>\n<\/p>\n
\u4f7f\u7528Pandas\u548cMatplotlib\u7ed8\u5236\u5e26\u6709\u8fb9\u6846\u7684\u8868\u683c<\/h3>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528Pandas\u548cMatplotlib\u7ed3\u5408\u7ed8\u5236\u5e26\u6709\u8fb9\u6846\u7684\u8868\u683c\u7684\u8be6\u7ec6\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u521b\u5efaDataFrame\u5bf9\u8c61<\/strong><\/h2>\n
df = pd.DataFrame({<\/p>\n
    'A': [1, 2, 3],<\/p>\n
    'B': [4, 5, 6],<\/p>\n
    'C': [7, 8, 9]<\/p>\n
})<\/p>\n
\u83b7\u53d6Styler\u5bf9\u8c61<\/strong><\/h2>\n
styler = df.style<\/p>\n
\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846<\/strong><\/h2>\n
styler.set_table_styles(<\/p>\n
    [{'selector': 'th',<\/p>\n
      'props': [('border', '1px solid black')]},<\/p>\n
     {'selector': 'td',<\/p>\n
      'props': [('border', '1px solid black')]}]<\/p>\n
)<\/p>\n
\u663e\u793a\u5e26\u6709\u8fb9\u6846\u7684\u8868\u683c<\/strong><\/h2>\n
styler<\/p>\n
\u4f7f\u7528Matplotlib\u7ed8\u5236\u5e26\u6709\u8fb9\u6846\u7684\u8868\u683c<\/strong><\/h2>\n
fig, ax = plt.subplots()<\/p>\n
ax.axis('tight')<\/p>\n
ax.axis('off')<\/p>\n
table = ax.table(cellText=df.values, colLabels=df.columns, cellLoc='center', loc='center')<\/p>\n
\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846<\/strong><\/h2>\n
table.auto_set_font_size(False)<\/p>\n
table.set_fontsize(14)<\/p>\n
table.scale(1.5, 1.5)<\/p>\n
\u8bbe\u7f6e\u5355\u5143\u683c\u8fb9\u6846<\/strong><\/h2>\n
for (i, j), cell in table.get_celld().items():<\/p>\n
    cell.set_edgecolor('black')<\/p>\n
    cell.set_linewidth(2)<\/p>\n
\u663e\u793a\u5e26\u6709\u8fb9\u6846\u7684\u8868\u683c<\/strong><\/h2>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528Openpyxl\u64cd\u4f5cExcel\u6587\u4ef6\u4e2d\u7684\u8868\u683c\u8fb9\u6846<\/h3>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u4f7f\u7528Openpyxl\u64cd\u4f5cExcel\u6587\u4ef6\u4e2d\u7684\u8868\u683c\u8fb9\u6846\u7684\u8be6\u7ec6\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from openpyxl import Workbook<\/p>\n
from openpyxl.styles import Border, Side<\/p>\n
\u521b\u5efaWorkbook\u5bf9\u8c61<\/strong><\/h2>\n
wb = Workbook()<\/p>\n
ws = wb.active<\/p>\n
\u5199\u5165\u6570\u636e<\/strong><\/h2>\n
data = [<\/p>\n
    ['A', 'B', 'C'],<\/p>\n
    [1, 2, 3],<\/p>\n
    [4, 5, 6],<\/p>\n
    [7, 8, 9]<\/p>\n
]<\/p>\n
for row in data:<\/p>\n
    ws.append(row)<\/p>\n
\u5b9a\u4e49\u8fb9\u6846\u6837\u5f0f<\/strong><\/h2>\n
thin_border = Border(left=Side(style='thin'),<\/p>\n
                     right=Side(style='thin'),<\/p>\n
                     top=Side(style='thin'),<\/p>\n
                     bottom=Side(style='thin'))<\/p>\n
\u8bbe\u7f6e\u5355\u5143\u683c\u8fb9\u6846<\/strong><\/h2>\n
for row in ws.iter_rows(min_row=1, max_row=4, min_col=1, max_col=3):<\/p>\n
    for cell in row:<\/p>\n
        cell.border = thin_border<\/p>\n
\u4fdd\u5b58Excel\u6587\u4ef6<\/strong><\/h2>\n
wb.save('table_with_borders.xlsx')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u65b9\u5f0f\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u4e2d\u4f7f\u7528\u4e0d\u540c\u7684\u5e93\u6765\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846\uff0c\u4ee5\u6ee1\u8db3\u4e0d\u540c\u7684\u5e94\u7528\u9700\u6c42\u3002\u65e0\u8bba\u662f\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u53ef\u89c6\u5316\uff0c\u8fd8\u662f\u64cd\u4f5cExcel\u6587\u4ef6\uff0cPandas\u3001Matplotlib\u548cOpenpyxl\u5e93\u90fd\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u6765\u5b9e\u73b0\u8fd9\u4e9b\u64cd\u4f5c\u3002\u5e0c\u671b\u901a\u8fc7\u8fd9\u4e9b\u793a\u4f8b\uff0c\u60a8\u80fd\u591f\u66f4\u597d\u5730\u7406\u89e3\u5982\u4f55\u5728Python\u4e2d\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846\uff0c\u5e76\u5e94\u7528\u5230\u5b9e\u9645\u9879\u76ee\u4e2d\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528Pandas\u8bbe\u7f6e\u8868\u683c\u8fb9\u6846\uff1f<\/strong>
\u5728\u4f7f\u7528Pandas\u5e93\u5904\u7406\u6570\u636e\u5e76\u8f93\u51fa\u4e3a\u8868\u683c\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528Styler<\/code>\u5bf9\u8c61\u7684set_table_styles<\/code>\u65b9\u6cd5\u6765\u8bbe\u7f6e\u8868\u683c\u7684\u8fb9\u6846\u3002\u60a8\u53ef\u4ee5\u5b9a\u4e49\u6837\u5f0f\u5b57\u5178\uff0c\u6307\u5b9a\u8fb9\u6846\u7684\u989c\u8272\u3001\u5bbd\u5ea6\u548c\u6837\u5f0f\u7b49\u3002\u4f8b\u5982\uff1a<\/p>\n
import pandas as pd\n\ndf = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})\nstyled_df = df.style.set_table_styles(\n    [{'selector': 'table', 'props': [('border', '2px solid black')]}]\n)\nstyled_df\n<\/code><\/pre>\n
\u53ef\u4ee5\u4f7f\u7528\u54ea\u4e9b\u5e93\u6765\u521b\u5efa\u5e26\u8fb9\u6846\u7684\u8868\u683c\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u9664\u4e86Pandas\uff0c\u8fd8\u6709\u5176\u4ed6\u5e93\u53ef\u4ee5\u521b\u5efa\u5e26\u8fb9\u6846\u7684\u8868\u683c\u3002\u4f8b\u5982\uff0cPrettyTable<\/code>\u5e93\u53ef\u4ee5\u8f7b\u677e\u751f\u6210\u5e26\u6709\u8fb9\u6846\u548c\u683c\u5f0f\u5316\u7684\u6587\u672c\u8868\u683c\u3002tabulate<\/code>\u5e93\u540c\u6837\u63d0\u4f9b\u4e86\u591a\u79cd\u683c\u5f0f\u9009\u9879\uff0c\u80fd\u591f\u8f93\u51fa\u6f02\u4eae\u7684\u8868\u683c\u3002\u9009\u62e9\u5408\u9002\u7684\u5e93\u53ef\u4ee5\u6839\u636e\u9879\u76ee\u9700\u6c42\u548c\u8f93\u51fa\u683c\u5f0f\u6765\u51b3\u5b9a\u3002<\/p>\n
\u5982\u4f55\u5728Jupyter Notebook\u4e2d\u663e\u793a\u5e26\u8fb9\u6846\u7684\u8868\u683c\uff1f<\/strong>
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