{"id":1080015,"date":"2025-01-08T12:26:14","date_gmt":"2025-01-08T04:26:14","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1080015.html"},"modified":"2025-01-08T12:26:18","modified_gmt":"2025-01-08T04:26:18","slug":"%e5%9c%a8python%e4%b8%ad-%e5%a6%82%e4%bd%95%e8%af%bb%e5%8f%96%e6%96%87%e4%bb%b6%e7%9a%84%e5%88%97-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1080015.html","title":{"rendered":"\u5728python\u4e2d \u5982\u4f55\u8bfb\u53d6\u6587\u4ef6\u7684\u5217"},"content":{"rendered":"

\"\u5728python\u4e2d<\/p>\n

\u5728Python\u4e2d\uff0c\u8bfb\u53d6\u6587\u4ef6\u7684\u5217\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\uff0c\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u7684csv<\/code>\u6a21\u5757\u3001pandas<\/code>\u5e93\u4ee5\u53canumpy<\/code>\u5e93\u3002\u8fd9\u4e9b\u65b9\u6cd5\u5404\u6709\u4f18\u7f3a\u70b9\uff0c\u5177\u4f53\u9009\u62e9\u53d6\u51b3\u4e8e\u6587\u4ef6\u7684\u683c\u5f0f\u548c\u6570\u636e\u5904\u7406\u9700\u6c42\u3002\u5e38\u89c1\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528csv\u6a21\u5757\u8bfb\u53d6CSV\u6587\u4ef6\u3001\u4f7f\u7528pandas\u5e93\u8bfb\u53d6CSV\u6216Excel\u6587\u4ef6\u3001\u4f7f\u7528numpy\u5e93\u8bfb\u53d6\u6570\u636e\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5176\u4e2d\u4e00\u79cd\u65b9\u6cd5\uff1a\u4f7f\u7528pandas\u5e93\u8bfb\u53d6\u6587\u4ef6\u7684\u5217\u3002<\/strong><\/p>\n<\/p>\n

\u4f7f\u7528pandas\u5e93\u8bfb\u53d6\u6587\u4ef6\u7684\u5217<\/strong>\uff1apandas\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u5e93\uff0c\u80fd\u591f\u8f7b\u677e\u8bfb\u53d6\u548c\u64cd\u4f5c\u6570\u636e\u3002\u5b83\u652f\u6301\u591a\u79cd\u6587\u4ef6\u683c\u5f0f\uff0c\u5305\u62ecCSV\u3001Excel\u3001JSON\u7b49\u3002\u4f7f\u7528pandas\u8bfb\u53d6\u6587\u4ef6\u7684\u5217\u975e\u5e38\u7b80\u5355\uff0c\u4e0b\u9762\u662f\u4e00\u4e2a\u8be6\u7ec6\u7684\u793a\u4f8b\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528pandas\u8bfb\u53d6CSV\u6587\u4ef6\u7684\u5217<\/h3>\n<\/p>\n

1\u3001\u5b89\u88c5pandas\u5e93<\/h4>\n<\/p>\n

\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86pandas\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\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
2\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u540d\u4e3adata.csv<\/code>\u7684\u6587\u4ef6\uff0c\u5176\u5185\u5bb9\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
Name, Age, Gender<\/p>\n
Alice, 30, Female<\/p>\n
Bob, 25, Male<\/p>\n
Charlie, 35, Male<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas\u8bfb\u53d6\u8fd9\u4e2a\u6587\u4ef6\u5e76\u63d0\u53d6\u7279\u5b9a\u7684\u5217\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
df = pd.read_csv('data.csv')<\/p>\n
\u6253\u5370\u6574\u4e2a\u6570\u636e\u6846<\/strong><\/h2>\n
print("\u5b8c\u6574\u7684\u6570\u636e\u6846\uff1a")<\/p>\n
print(df)<\/p>\n
\u8bfb\u53d6\u7279\u5b9a\u7684\u5217<\/strong><\/h2>\n
name_column = df['Name']<\/p>\n
age_column = df['Age']<\/p>\n
\u6253\u5370\u7279\u5b9a\u7684\u5217<\/strong><\/h2>\n
print("\\nName\u5217\uff1a")<\/p>\n
print(name_column)<\/p>\n
print("\\nAge\u5217\uff1a")<\/p>\n
print(age_column)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528pandas\u8bfb\u53d6Excel\u6587\u4ef6\u7684\u5217<\/h3>\n<\/p>\n
1\u3001\u5b89\u88c5openpyxl\u5e93<\/h4>\n<\/p>\n
\u5982\u679c\u4f60\u9700\u8981\u8bfb\u53d6Excel\u6587\u4ef6\uff0c\u8fd8\u9700\u8981\u5b89\u88c5openpyxl<\/code>\u5e93\uff1a<\/p>\n<\/p>\n
pip install openpyxl<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bfb\u53d6Excel\u6587\u4ef6<\/h4>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u540d\u4e3adata.xlsx<\/code>\u7684Excel\u6587\u4ef6\uff0c\u5176\u5185\u5bb9\u4e0e\u4e0a\u9762\u7684CSV\u6587\u4ef6\u76f8\u540c\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas\u8bfb\u53d6\u8fd9\u4e2a\u6587\u4ef6\u5e76\u63d0\u53d6\u7279\u5b9a\u7684\u5217\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n
df = pd.read_excel('data.xlsx')<\/p>\n
\u6253\u5370\u6574\u4e2a\u6570\u636e\u6846<\/strong><\/h2>\n
print("\u5b8c\u6574\u7684\u6570\u636e\u6846\uff1a")<\/p>\n
print(df)<\/p>\n
\u8bfb\u53d6\u7279\u5b9a\u7684\u5217<\/strong><\/h2>\n
name_column = df['Name']<\/p>\n
age_column = df['Age']<\/p>\n
\u6253\u5370\u7279\u5b9a\u7684\u5217<\/strong><\/h2>\n
print("\\nName\u5217\uff1a")<\/p>\n
print(name_column)<\/p>\n
print("\\nAge\u5217\uff1a")<\/p>\n
print(age_column)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528numpy\u8bfb\u53d6\u6587\u4ef6\u7684\u5217<\/h3>\n<\/p>\n
numpy\u662f\u4e00\u4e2a\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u5e93\uff0c\u867d\u7136\u5b83\u7684\u4e3b\u8981\u529f\u80fd\u4e0d\u662f\u6570\u636e\u5904\u7406\uff0c\u4f46\u4e5f\u53ef\u4ee5\u8bfb\u53d6\u6587\u4ef6\u5e76\u63d0\u53d6\u5217\u3002<\/p>\n<\/p>\n
1\u3001\u5b89\u88c5numpy\u5e93<\/h4>\n<\/p>\n
\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86numpy\u5e93\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install numpy<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u540d\u4e3adata.csv<\/code>\u7684\u6587\u4ef6\uff0c\u5176\u5185\u5bb9\u4e0e\u4e0a\u9762\u7684CSV\u6587\u4ef6\u76f8\u540c\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528numpy\u8bfb\u53d6\u8fd9\u4e2a\u6587\u4ef6\u5e76\u63d0\u53d6\u7279\u5b9a\u7684\u5217\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
data = np.genfromtxt('data.csv', delimiter=',', dtype=None, encoding='utf-8', skip_header=1)<\/p>\n
\u63d0\u53d6\u7279\u5b9a\u7684\u5217<\/strong><\/h2>\n
name_column = data[:, 0]<\/p>\n
age_column = data[:, 1]<\/p>\n
\u6253\u5370\u7279\u5b9a\u7684\u5217<\/strong><\/h2>\n
print("Name\u5217\uff1a")<\/p>\n
print(name_column)<\/p>\n
print("Age\u5217\uff1a")<\/p>\n
print(age_column)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u5728Python\u4e2d\u8bfb\u53d6\u6587\u4ef6\u7684\u5217\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5<\/strong>\uff0c\u5305\u62ec\u4f7f\u7528csv\u6a21\u5757\u3001pandas\u5e93\u548cnumpy\u5e93\u3002\u5176\u4e2d\uff0cpandas\u5e93\u662f\u6700\u5f3a\u5927\u548c\u6700\u5e38\u7528\u7684\u9009\u62e9<\/strong>\uff0c\u56e0\u4e3a\u5b83\u4e0d\u4ec5\u652f\u6301\u591a\u79cd\u6587\u4ef6\u683c\u5f0f\uff0c\u8fd8\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\u3002\u65e0\u8bba\u662f\u8bfb\u53d6CSV\u6587\u4ef6\u8fd8\u662fExcel\u6587\u4ef6\uff0cpandas\u90fd\u80fd\u8f7b\u677e\u5e94\u5bf9<\/strong>\u3002\u5bf9\u4e8e\u7b80\u5355\u7684\u6587\u4ef6\u8bfb\u53d6\u548c\u5904\u7406\u4efb\u52a1\uff0ccsv\u6a21\u5757\u548cnumpy\u5e93\u4e5f\u662f\u4e0d\u9519\u7684\u9009\u62e9\u3002\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u63d0\u9ad8\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u548c\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6\u7279\u5b9a\u5217\u7684\u6570\u636e\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u8bfb\u53d6\u7279\u5b9a\u5217\u7684\u6570\u636e\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5b9e\u73b0\u3002\u4f7f\u7528Pandas\u5e93\u662f\u6700\u5e38\u89c1\u7684\u65b9\u6cd5\u4e4b\u4e00\u3002\u9996\u5148\uff0c\u60a8\u9700\u8981\u5b89\u88c5Pandas\u5e93\uff0c\u7136\u540e\u53ef\u4ee5\u4f7f\u7528pd.read_csv()<\/code>\u8bfb\u53d6CSV\u6587\u4ef6\uff0c\u5e76\u901a\u8fc7\u6307\u5b9ausecols<\/code>\u53c2\u6570\u6765\u9009\u62e9\u9700\u8981\u7684\u5217\u3002\u793a\u4f8b\u4ee3\u7801\u5982\u4e0b\uff1a  <\/p>\n
import pandas as pd\n\ndata = pd.read_csv('file.csv', usecols=['column1', 'column2'])\nprint(data)\n<\/code><\/pre>\n
\u8fd9\u6837\u5c31\u80fd\u63d0\u53d6\u6307\u5b9a\u7684\u5217\u6570\u636e\uff0c\u60a8\u4e5f\u53ef\u4ee5\u901a\u8fc7\u5176\u4ed6\u683c\u5f0f\u7684\u6587\u4ef6\uff08\u5982Excel\uff09\u4f7f\u7528\u7c7b\u4f3c\u7684\u65b9\u6cd5\u3002<\/p>\n
\u4f7f\u7528Python\u8bfb\u53d6\u6587\u4ef6\u65f6\uff0c\u5982\u4f55\u5904\u7406\u7f3a\u5931\u503c\uff1f<\/strong>
\u5728\u8bfb\u53d6\u6587\u4ef6\u6570\u636e\u65f6\uff0c\u7f3a\u5931\u503c\u662f\u5e38\u89c1\u7684\u95ee\u9898\u3002\u4f7f\u7528Pandas\u65f6\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7fillna()<\/code>\u65b9\u6cd5\u6765\u586b\u5145\u7f3a\u5931\u503c\uff0c\u6216\u8005\u4f7f\u7528dropna()<\/code>\u65b9\u6cd5\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c\u3002\u4f8b\u5982\uff1a  <\/p>\n
data = pd.read_csv('file.csv')\ndata.fillna(0, inplace=True)  # \u75280\u586b\u5145\u7f3a\u5931\u503c\n<\/code><\/pre>\n
\u8fd9\u6837\u53ef\u4ee5\u786e\u4fdd\u6570\u636e\u7684\u5b8c\u6574\u6027\uff0c\u907f\u514d\u56e0\u7f3a\u5931\u503c\u5bfc\u81f4\u7684\u9519\u8bef\u5206\u6790\u3002<\/p>\n
\u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6\u5927\u6587\u4ef6\u800c\u4e0d\u8017\u5c3d\u5185\u5b58\uff1f<\/strong>
\u5904\u7406\u5927\u578b\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u7684chunksize<\/code>\u53c2\u6570\u6765\u5206\u5757\u8bfb\u53d6\u6587\u4ef6\u3002\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u60a8\u53ef\u4ee5\u9010\u5757\u5904\u7406\u6570\u636e\uff0c\u907f\u514d\u4e00\u6b21\u6027\u52a0\u8f7d\u6574\u4e2a\u6587\u4ef6\u800c\u5bfc\u81f4\u5185\u5b58\u6ea2\u51fa\u3002\u4f8b\u5982\uff1a  <\/p>\n
for chunk in pd.read_csv('large_file.csv', chunksize=1000):\n    process(chunk)  # \u81ea\u5b9a\u4e49\u5904\u7406\u51fd\u6570\n<\/code><\/pre>\n
\u8fd9\u79cd\u65b9\u6cd5\u4e0d\u4ec5\u8282\u7701\u5185\u5b58\uff0c\u8fd8\u80fd\u63d0\u9ad8\u5904\u7406\u6548\u7387\uff0c\u9002\u7528\u4e8e\u6570\u636e\u91cf\u8f83\u5927\u7684\u573a\u666f\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u8bfb\u53d6\u6587\u4ef6\u7684\u5217\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\uff0c\u5305\u62ec\u4f7f\u7528\u5185\u7f6e\u7684csv\u6a21\u5757\u3001pandas\u5e93\u4ee5\u53canumpy\u5e93\u3002\u8fd9\u4e9b […]","protected":false},"author":3,"featured_media":1080023,"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\/1080015"}],"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=1080015"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1080015\/revisions"}],"predecessor-version":[{"id":1080025,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1080015\/revisions\/1080025"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1080023"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1080015"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1080015"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1080015"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}