{"id":1175769,"date":"2025-01-15T17:36:31","date_gmt":"2025-01-15T09:36:31","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1175769.html"},"modified":"2025-01-15T17:36:34","modified_gmt":"2025-01-15T09:36:34","slug":"python%e8%af%bb%e5%8f%96%e5%a4%a7excel%e5%a6%82%e4%bd%95%e5%ad%98","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1175769.html","title":{"rendered":"python\u8bfb\u53d6\u5927excel\u5982\u4f55\u5b58"},"content":{"rendered":"

\"python\u8bfb\u53d6\u5927excel\u5982\u4f55\u5b58\"<\/p>\n

Python\u8bfb\u53d6\u5927Excel\u6587\u4ef6\u5e76\u8fdb\u884c\u5b58\u50a8\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5e38\u89c1\u7684\u6709\u4f7f\u7528pandas\u5e93\u3001openpyxl\u5e93\u3001xlrd\u5e93\u7b49\u3002<\/strong>\u5176\u4e2d\uff0cpandas\u5e93\u662f\u6700\u5e38\u7528\u4e14\u9ad8\u6548\u7684\u65b9\u5f0f\u3002pandas\u5e93\u4e0d\u4ec5\u53ef\u4ee5\u8bfb\u53d6\u5927Excel\u6587\u4ef6\uff0c\u8fd8\u53ef\u4ee5\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u3002\u4e3a\u4e86\u5904\u7406\u5927\u6587\u4ef6\uff0c\u53ef\u4ee5\u4f7f\u7528\u5206\u5757\u8bfb\u53d6\u3001\u5185\u5b58\u4f18\u5316\u548c\u9ad8\u6548\u5b58\u50a8<\/strong>\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u901a\u8fc7\u8fd9\u4e9b\u65b9\u5f0f\u9ad8\u6548\u8bfb\u53d6\u548c\u5b58\u50a8\u5927Excel\u6587\u4ef6\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Pandas\u8bfb\u53d6\u5927Excel\u6587\u4ef6<\/h3>\n<\/p>\n

1\u3001\u57fa\u672c\u8bfb\u53d6\u65b9\u6cd5<\/h4>\n<\/p>\n

Pandas\u5e93\u63d0\u4f9b\u4e86read_excel<\/code>\u51fd\u6570\u7528\u4e8e\u8bfb\u53d6Excel\u6587\u4ef6\u3002\u5bf9\u4e8e\u5c0f\u6587\u4ef6\uff0c\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
data = pd.read_excel(file_path)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5206\u5757\u8bfb\u53d6<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u5927\u6587\u4ef6\uff0c\u53ef\u4ee5\u4f7f\u7528chunksize<\/code>\u53c2\u6570\u8fdb\u884c\u5206\u5757\u8bfb\u53d6\uff0c\u8fd9\u6837\u53ef\u4ee5\u8282\u7701\u5185\u5b58\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
chunk_size = 10000  # \u6bcf\u6b21\u8bfb\u53d610000\u884c<\/p>\n
chunk_list = []<\/p>\n
for chunk in pd.read_excel(file_path, chunksize=chunk_size):<\/p>\n
    chunk_list.append(chunk)<\/p>\n
data = pd.concat(chunk_list)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u4f7f\u7528\u6307\u5b9a\u5217\u548c\u884c<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7usecols<\/code>\u548cnrows<\/code>\u53c2\u6570\u6765\u6307\u5b9a\u8bfb\u53d6\u7684\u5217\u548c\u884c\uff0c\u4ee5\u51cf\u5c11\u5185\u5b58\u4f7f\u7528\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
data = pd.read_excel(file_path, usecols=['Column1', 'Column2'], nrows=10000)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u5185\u5b58\u4f18\u5316<\/h3>\n<\/p>\n
1\u3001\u6570\u636e\u7c7b\u578b\u8f6c\u6362<\/h4>\n<\/p>\n
\u5c06\u6570\u636e\u8f6c\u6362\u4e3a\u5408\u9002\u7684\u7c7b\u578b\u53ef\u4ee5\u5927\u5927\u51cf\u5c11\u5185\u5b58\u5360\u7528\u3002\u4f8b\u5982\uff0c\u5c06\u6d6e\u70b9\u6570\u8f6c\u6362\u4e3a\u6574\u6570\uff0c\u5c06\u5b57\u7b26\u4e32\u8f6c\u6362\u4e3a\u7c7b\u522b\u7b49\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
data = pd.read_excel(file_path)<\/p>\n
data['Column1'] = data['Column1'].astype('category')<\/p>\n
data['Column2'] = data['Column2'].astype('int32')<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528dtypes\u53c2\u6570<\/h4>\n<\/p>\n
\u5728\u8bfb\u53d6\u65f6\u76f4\u63a5\u6307\u5b9a\u6570\u636e\u7c7b\u578b\uff0c\u4ee5\u51cf\u5c11\u5185\u5b58\u4f7f\u7528\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
dtypes = {'Column1': 'category', 'Column2': 'int32'}<\/p>\n
data = pd.read_excel(file_path, dtype=dtypes)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u5b58\u50a8\u6570\u636e<\/h3>\n<\/p>\n
1\u3001\u5b58\u50a8\u4e3aCSV\u6587\u4ef6<\/h4>\n<\/p>\n
\u5c06\u8bfb\u53d6\u7684Excel\u6587\u4ef6\u5b58\u50a8\u4e3aCSV\u6587\u4ef6\uff0c\u8fd9\u662f\u6700\u5e38\u89c1\u7684\u5b58\u50a8\u65b9\u5f0f\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
data = pd.read_excel(file_path)<\/p>\n
data.to_csv('output_file.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5b58\u50a8\u4e3aHDF5\u6587\u4ef6<\/h4>\n<\/p>\n
HDF5\u662f\u4e00\u79cd\u9ad8\u6548\u7684\u6587\u4ef6\u683c\u5f0f\uff0c\u7279\u522b\u9002\u7528\u4e8e\u5b58\u50a8\u5927\u89c4\u6a21\u6570\u636e\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
data = pd.read_excel(file_path)<\/p>\n
data.to_hdf('output_file.h5', key='df', mode='w')<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u5b58\u50a8\u4e3aParquet\u6587\u4ef6<\/h4>\n<\/p>\n
Parquet\u662f\u4e00\u79cd\u4e13\u4e3a\u5927\u6570\u636e\u5b58\u50a8\u8bbe\u8ba1\u7684\u5217\u5f0f\u5b58\u50a8\u683c\u5f0f\uff0c\u8bfb\u53d6\u548c\u5199\u5165\u901f\u5ea6\u90fd\u5f88\u5feb\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
data = pd.read_excel(file_path)<\/p>\n
data.to_parquet('output_file.parquet')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528Openpyxl\u8bfb\u53d6\u548c\u5b58\u50a8<\/h3>\n<\/p>\n
Openpyxl\u662f\u53e6\u4e00\u4e2a\u5e38\u7528\u7684Excel\u5904\u7406\u5e93\uff0c\u9002\u7528\u4e8e\u5904\u7406.xlsx\u683c\u5f0f\u7684Excel\u6587\u4ef6\u3002<\/p>\n<\/p>\n
1\u3001\u8bfb\u53d6Excel\u6587\u4ef6<\/h4>\n<\/p>\n
from openpyxl import load_workbook<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
wb = load_workbook(file_path)<\/p>\n
sheet = wb.active<\/p>\n
data = []<\/p>\n
for row in sheet.iter_rows(values_only=True):<\/p>\n
    data.append(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u5199\u5165Excel\u6587\u4ef6<\/h4>\n<\/p>\n
from openpyxl import Workbook<\/p>\n
data = [<\/p>\n
    ['Column1', 'Column2'],<\/p>\n
    [1, 2],<\/p>\n
    [3, 4]<\/p>\n
]<\/p>\n
wb = Workbook()<\/p>\n
sheet = wb.active<\/p>\n
for row in data:<\/p>\n
    sheet.append(row)<\/p>\n
wb.save('output_file.xlsx')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u4f7f\u7528xlrd\u8bfb\u53d6Excel\u6587\u4ef6<\/h3>\n<\/p>\n
xlrd\u9002\u7528\u4e8e\u8bfb\u53d6.xls\u683c\u5f0f\u7684Excel\u6587\u4ef6\u3002<\/p>\n<\/p>\n
1\u3001\u8bfb\u53d6Excel\u6587\u4ef6<\/h4>\n<\/p>\n
import xlrd<\/p>\n
file_path = 'large_file.xls'<\/p>\n
wb = xlrd.open_workbook(file_path)<\/p>\n
sheet = wb.sheet_by_index(0)<\/p>\n
data = []<\/p>\n
for row_idx in range(sheet.nrows):<\/p>\n
    row = sheet.row_values(row_idx)<\/p>\n
    data.append(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u63d0\u9ad8\u8bfb\u53d6\u6548\u7387\u7684\u5176\u4ed6\u6280\u5de7<\/h3>\n<\/p>\n
1\u3001\u5e76\u884c\u5904\u7406<\/h4>\n<\/p>\n
\u5229\u7528\u591a\u7ebf\u7a0b\u6216\u591a\u8fdb\u7a0b\u5e76\u884c\u8bfb\u53d6\u548c\u5904\u7406\u6570\u636e\uff0c\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u6548\u7387\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
from multiprocessing import Pool<\/p>\n
def process_chunk(chunk):<\/p>\n
    # \u5bf9\u5206\u5757\u6570\u636e\u8fdb\u884c\u5904\u7406<\/p>\n
    return chunk<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
chunk_size = 10000<\/p>\n
with Pool(processes=4) as pool:<\/p>\n
    results = pool.map(process_chunk, pd.read_excel(file_path, chunksize=chunk_size))<\/p>\n
data = pd.concat(results)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528Dask\u5e93<\/h4>\n<\/p>\n
Dask\u662f\u4e00\u4e2a\u5e76\u884c\u8ba1\u7b97\u5e93\uff0c\u53ef\u4ee5\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u96c6\uff1a<\/p>\n<\/p>\n
import dask.dataframe as dd<\/p>\n
file_path = 'large_file.xlsx'<\/p>\n
data = dd.read_excel(file_path)<\/p>\n
\u8fdb\u884c\u6570\u636e\u5904\u7406<\/strong><\/h2>\n
data = data.compute()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u9ad8\u6548\u5730\u8bfb\u53d6\u548c\u5b58\u50a8\u5927Excel\u6587\u4ef6\u3002\u4f7f\u7528Pandas\u5e93\u8fdb\u884c\u5206\u5757\u8bfb\u53d6\u548c\u5185\u5b58\u4f18\u5316\u3001\u5c06\u6570\u636e\u5b58\u50a8\u4e3a\u9ad8\u6548\u683c\u5f0f\uff08\u5982CSV\u3001HDF5\u3001Parquet\uff09\u3001\u5229\u7528Openpyxl\u548cxlrd\u5e93\u5904\u7406\u4e0d\u540c\u683c\u5f0f\u7684Excel\u6587\u4ef6\u3001\u4ee5\u53ca\u901a\u8fc7\u5e76\u884c\u5904\u7406\u548cDask\u5e93\u8fdb\u4e00\u6b65\u63d0\u9ad8\u6548\u7387<\/strong>\uff0c\u90fd\u662f\u5904\u7406\u5927Excel\u6587\u4ef6\u7684\u6709\u6548\u7b56\u7565\u3002<\/p>\n<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u548c\u5e93\uff0c\u80fd\u591f\u5927\u5927\u63d0\u9ad8\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u548c\u6027\u80fd\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u9ad8\u6548\u8bfb\u53d6\u5927Excel\u6587\u4ef6\u5e76\u8fdb\u884c\u5904\u7406\uff1f<\/strong>
\u5728\u5904\u7406\u5927Excel\u6587\u4ef6\u65f6\uff0c\u4f7f\u7528Python\u7684pandas<\/code>\u5e93\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\u3002\u4f60\u53ef\u4ee5\u5229\u7528read_excel<\/code>\u65b9\u6cd5\u8bfb\u53d6\u6570\u636e\uff0c\u5e76\u901a\u8fc7\u8bbe\u7f6echunksize<\/code>\u53c2\u6570\u6765\u5206\u5757\u8bfb\u53d6\uff0c\u4ee5\u907f\u514d\u5185\u5b58\u6ea2\u51fa\u3002\u8fd9\u6837\u53ef\u4ee5\u9010\u5757\u5904\u7406\u6570\u636e\uff0c\u9002\u7528\u4e8e\u5185\u5b58\u6709\u9650\u7684\u73af\u5883\u3002<\/p>\n
\u6709\u54ea\u4e9b\u5e93\u53ef\u4ee5\u7528\u6765\u5904\u7406\u5927\u578bExcel\u6587\u4ef6\uff1f<\/strong>
\u9664\u4e86pandas<\/code>\uff0copenpyxl<\/code>\u548cxlrd<\/code>\u4e5f\u662f\u5e38\u7528\u7684\u5e93\uff0c\u9002\u5408\u8bfb\u53d6\u548c\u5199\u5165Excel\u6587\u4ef6\u3002dask<\/code>\u5e93\u4e5f\u63d0\u4f9b\u4e86\u5bf9\u5927\u6570\u636e\u96c6\u7684\u652f\u6301\uff0c\u80fd\u591f\u5904\u7406\u8d85\u51fa\u5185\u5b58\u9650\u5236\u7684\u6570\u636e\u3002\u5f53\u9009\u62e9\u5e93\u65f6\uff0c\u8003\u8651\u5230\u6587\u4ef6\u683c\u5f0f\u548c\u6570\u636e\u5904\u7406\u9700\u6c42\u975e\u5e38\u91cd\u8981\u3002<\/p>\n
\u5982\u4f55\u5c06\u5904\u7406\u540e\u7684\u6570\u636e\u4fdd\u5b58\u56deExcel\u6587\u4ef6\u4e2d\uff1f<\/strong>
\u5904\u7406\u5b8c\u6570\u636e\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u7684to_excel<\/code>\u65b9\u6cd5\u5c06\u6570\u636e\u4fdd\u5b58\u5230\u65b0\u7684Excel\u6587\u4ef6\u4e2d\u3002\u786e\u4fdd\u5b89\u88c5\u4e86openpyxl<\/code>\u6216xlsxwriter<\/code>\u5e93\uff0c\u4ee5\u652f\u6301\u5199\u5165Excel\u683c\u5f0f\u3002\u5728\u4fdd\u5b58\u65f6\uff0c\u53ef\u4ee5\u9009\u62e9\u4e0d\u4fdd\u5b58\u7d22\u5f15\u6216\u8bbe\u7f6e\u5de5\u4f5c\u8868\u540d\u79f0\uff0c\u4ee5\u4fbf\u4e8e\u540e\u7eed\u7684\u6570\u636e\u4f7f\u7528\u548c\u7ba1\u7406\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u8bfb\u53d6\u5927Excel\u6587\u4ef6\u5e76\u8fdb\u884c\u5b58\u50a8\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5e38\u89c1\u7684\u6709\u4f7f\u7528pandas\u5e93\u3001openpyxl\u5e93\u3001xlr […]","protected":false},"author":3,"featured_media":1175773,"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\/1175769"}],"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=1175769"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1175769\/revisions"}],"predecessor-version":[{"id":1175774,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1175769\/revisions\/1175774"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1175773"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1175769"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1175769"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1175769"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}