![\"python\u4e2d\u5982\u4f55\u4f7f\u7528csv\"](\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25075013\/3f359417-72be-4163-b876-83522127de25.webp\")
<\/p>\n<\/p>\n
\u5728Python\u4e2d\u4f7f\u7528CSV\u6587\u4ef6\u65f6\uff0c\u4e3b\u8981\u4f9d\u8d56\u4e8e\u5185\u7f6e\u7684 \u5728Python\u4e2d\u8bfb\u53d6CSV\u6587\u4ef6\uff0c\u53ef\u4ee5\u4f7f\u7528 with open('example.csv', 'r', newline='', encoding='utf-8') as csvfile:<\/p>\n csvreader = csv.reader(csvfile)<\/p>\n # \u8bfb\u53d6\u6587\u4ef6\u5934<\/p>\n header = next(csvreader)<\/p>\n print(f'Header: {header}')<\/p>\n # \u8bfb\u53d6\u6570\u636e\u884c<\/p>\n for row in csvreader:<\/p>\n print(row)<\/p>\n <\/code><\/pre>\n<\/p>\n \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c \u4f7f\u7528 data = [<\/p>\n ['Name', 'Age', 'City'],<\/p>\n ['Alice', 30, 'New York'],<\/p>\n ['Bob', 25, 'Los Angeles'],<\/p>\n ['Charlie', 35, 'Chicago']<\/p>\n ]<\/p>\n with open('output.csv', 'w', newline='', encoding='utf-8') as csvfile:<\/p>\n csvwriter = csv.writer(csvfile)<\/p>\n # \u5199\u5165\u6570\u636e<\/p>\n csvwriter.writerows(data)<\/p>\n <\/code><\/pre>\n<\/p>\n \u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6570\u636e\u4ee5\u5217\u8868\u7684\u5f62\u5f0f\u51c6\u5907\uff0c\u7136\u540e\u901a\u8fc7 CSV\u6587\u4ef6\u4e2d\u53ef\u80fd\u5305\u542b\u9017\u53f7\u3001\u6362\u884c\u7b26\u7b49\u7279\u6b8a\u5b57\u7b26\uff0c\u8fd9\u4e9b\u5b57\u7b26\u9700\u8981\u5728\u8bfb\u53d6\u548c\u5199\u5165\u65f6\u8fdb\u884c\u5904\u7406\u3002 data = [<\/p>\n ['Name', 'Age', 'City'],<\/p>\n ['Alice', 30, 'New York, USA'],<\/p>\n ['Bob', 25, 'Los Angeles, USA']<\/p>\n ]<\/p>\n with open('output.csv', 'w', newline='', encoding='utf-8') as csvfile:<\/p>\n csvwriter = csv.writer(csvfile, quoting=csv.QUOTE_MINIMAL)<\/p>\n csvwriter.writerows(data)<\/p>\n <\/code><\/pre>\n<\/p>\n \u5728\u8fd9\u91cc\uff0c \u5728\u8bfb\u53d6CSV\u6587\u4ef6\u65f6\uff0c\u6570\u636e\u901a\u5e38\u4ee5\u5b57\u7b26\u4e32\u5f62\u5f0f\u8bfb\u53d6\u3002\u5982\u679c\u9700\u8981\u7279\u5b9a\u7684\u6570\u636e\u683c\u5f0f\uff08\u5982\u6574\u6570\u3001\u6d6e\u70b9\u6570\u7b49\uff09\uff0c\u5219\u9700\u8981\u8fdb\u884c\u8f6c\u6362\u3002<\/p>\n<\/p>\n with open('example.csv', 'r', newline='', encoding='utf-8') as csvfile:<\/p>\n csvreader = csv.reader(csvfile)<\/p>\n header = next(csvreader)<\/p>\n for row in csvreader:<\/p>\n name = row[0]<\/p>\n age = int(row[1]) # \u8f6c\u6362\u4e3a\u6574\u6570<\/p>\n city = row[2]<\/p>\n print(f'Name: {name}, Age: {age}, City: {city}')<\/p>\n <\/code><\/pre>\n<\/p>\n \u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u901a\u8fc7 \u4f7f\u7528 df = pd.read_csv('example.csv')<\/p>\n print(df.head())<\/p>\n <\/code><\/pre>\n<\/p>\n data = {<\/p>\n 'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n 'Age': [30, 25, 35],<\/p>\n 'City': ['New York', 'Los Angeles', 'Chicago']<\/p>\n }<\/p>\n df = pd.DataFrame(data)<\/p>\n df.to_csv('output.csv', index=False)<\/p>\n <\/code><\/pre>\n<\/p>\n df = pd.read_csv('example.csv')<\/p>\n filtered_df = df[df['Age'] > 30]<\/p>\n print(filtered_df)<\/p>\n grouped_df = df.groupby('City').mean()<\/p>\n print(grouped_df)<\/p>\n <\/code><\/pre>\n<\/p>\n \u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c \u5bf9\u4e8e\u975e\u5e38\u5927\u7684CSV\u6587\u4ef6\uff0c\u9010\u884c\u8bfb\u53d6\u53ef\u4ee5\u907f\u514d\u5185\u5b58\u4e0d\u8db3\u7684\u95ee\u9898\u3002\u53ef\u4ee5\u7ed3\u5408 chunk_size = 10000<\/p>\n for chunk in pd.read_csv('large_file.csv', chunksize=chunk_size):<\/p>\n # \u5bf9\u6bcf\u4e2a\u5757\u8fdb\u884c\u5904\u7406<\/p>\n print(chunk.head())<\/p>\n <\/code><\/pre>\n<\/p>\n \u867d\u7136CSV\u6587\u4ef6\u901a\u5e38\u7528\u9017\u53f7\u5206\u9694\uff0c\u4f46\u4e5f\u53ef\u80fd\u4f7f\u7528\u5176\u4ed6\u5206\u9694\u7b26\uff08\u5982\u5236\u8868\u7b26\u3001\u5206\u53f7\u7b49\uff09\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u53ef\u4ee5\u5728\u8bfb\u53d6\u6216\u5199\u5165\u65f6\u6307\u5b9a\u5206\u9694\u7b26\u3002<\/p>\n<\/p>\n df = pd.read_csv('example.tsv', sep='\\t')<\/p>\n print(df.head())<\/p>\n <\/code><\/pre>\n<\/p>\n \u5728 CSV\u6587\u4ef6\u4e2d\u53ef\u80fd\u5305\u542b\u7f3a\u5931\u503c\uff0c df = pd.read_csv('example.csv')<\/p>\n df.fillna(value={'Age': df['Age'].mean()}, inplace=True)<\/p>\n print(df)<\/p>\n <\/code><\/pre>\n<\/p>\n CSV\u6587\u4ef6\u662f\u4e00\u79cd\u8f7b\u91cf\u7ea7\u7684\u6570\u636e\u5b58\u50a8\u683c\u5f0f\uff0c\u5e38\u7528\u4e8e\u5e94\u7528\u4e4b\u95f4\u7684\u6570\u636e\u4ea4\u6362\u3002\u5b83\u7b80\u5355\u6613\u8bfb\uff0c\u51e0\u4e4e\u6240\u6709\u6570\u636e\u5206\u6790\u5de5\u5177\u90fd\u652f\u6301CSV\u683c\u5f0f\u3002<\/p>\n<\/p>\n \u901a\u8fc7 import matplotlib.pyplot as plt<\/p>\n df = pd.read_csv('example.csv')<\/p>\n df['Age'].hist()<\/p>\n plt.xlabel('Age')<\/p>\n plt.ylabel('Frequency')<\/p>\n plt.title('Age Distribution')<\/p>\n plt.show()<\/p>\n <\/code><\/pre>\n<\/p>\n \u7531\u4e8eCSV\u6587\u4ef6\u7684\u7b80\u5355\u6027\u548c\u53ef\u8bfb\u6027\uff0c\u5b83\u4e5f\u5e38\u7528\u4e8e\u6570\u636e\u5907\u4efd\u548c\u65e5\u5fd7\u8bb0\u5f55\uff0c\u7279\u522b\u662f\u5728\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u5ba1\u8ba1\u548c\u56de\u6eaf\u65f6\u3002<\/p>\n<\/p>\n \u5728Python\u4e2d\u4f7f\u7528CSV\u6587\u4ef6\uff0c\u65e0\u8bba\u662f\u901a\u8fc7\u5185\u7f6e\u7684 \u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6CSV\u6587\u4ef6\uff1f<\/strong> \u8fd9\u79cd\u65b9\u5f0f\u80fd\u591f\u8f7b\u677e\u5904\u7406CSV\u6587\u4ef6\u4e2d\u7684\u6570\u636e\uff0c\u60a8\u53ef\u4ee5\u6839\u636e\u9700\u8981\u5bf9\u5176\u8fdb\u884c\u8fdb\u4e00\u6b65\u5904\u7406\u3002<\/p>\n \u5982\u4f55\u5728Python\u4e2d\u5199\u5165CSV\u6587\u4ef6\uff1f<\/strong> \u8fd9\u6837\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a\u65b0\u7684CSV\u6587\u4ef6\uff0c\u5e76\u5c06\u6307\u5b9a\u7684\u6570\u636e\u5199\u5165\u5176\u4e2d\u3002<\/p>\n \u5982\u4f55\u5904\u7406\u5e26\u6709\u6807\u9898\u7684CSV\u6587\u4ef6\uff1f<\/strong> \u8fd9\u79cd\u65b9\u5f0f\u4fbf\u4e8e\u5904\u7406\u590d\u6742\u7684\u6570\u636e\u7ed3\u6784\uff0c\u4f7f\u4ee3\u7801\u66f4\u52a0\u6e05\u6670\u6613\u8bfb\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u4f7f\u7528CSV\u6587\u4ef6\u65f6\uff0c\u4e3b\u8981\u4f9d\u8d56\u4e8e\u5185\u7f6e\u7684csv\u6a21\u5757\u3002\u8981\u4f7f\u7528CSV\u6587\u4ef6\uff0c\u53ef\u4ee5\u901a\u8fc7\u5bfc\u5165csv\u6a21\u5757\u3001\u8bfb\u53d6C […]","protected":false},"author":3,"featured_media":1000415,"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\/1000400"}],"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=1000400"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1000400\/revisions"}],"predecessor-version":[{"id":1000417,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1000400\/revisions\/1000417"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1000415"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1000400"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1000400"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1000400"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}csv<\/code>\u6a21\u5757\u3002\u8981\u4f7f\u7528CSV\u6587\u4ef6\uff0c\u53ef\u4ee5\u901a\u8fc7\u5bfc\u5165csv\u6a21\u5757\u3001\u8bfb\u53d6CSV\u6587\u4ef6\u3001\u5199\u5165CSV\u6587\u4ef6\u3001\u5904\u7406\u7279\u6b8a\u5b57\u7b26\u548c\u6570\u636e\u683c\u5f0f\u3001\u4f7f\u7528pandas\u5e93\u7b49\u65b9\u6cd5\u6765\u5b9e\u73b0\u3002<\/strong>\u5176\u4e2d\uff0c\u4f7f\u7528csv.reader<\/code>\u548ccsv.writer<\/code>\u8fdb\u884c\u6587\u4ef6\u7684\u8bfb\u5199\u64cd\u4f5c\u662f\u6700\u5e38\u89c1\u548c\u57fa\u672c\u7684\u65b9\u5f0f\uff0cpandas<\/code>\u5e93\u5219\u63d0\u4f9b\u4e86\u66f4\u9ad8\u7ea7\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\u3002\u4ee5\u4e0b\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\u3002<\/p>\n<\/p>\n\u4e00\u3001CSV\u6a21\u5757\u7684\u57fa\u672c\u4f7f\u7528<\/h3>\n<\/p>\n
1. \u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n
csv.reader<\/code>\u3002\u5b83\u80fd\u5c06CSV\u6587\u4ef6\u7684\u6570\u636e\u8bfb\u53d6\u4e3a\u4e00\u4e2a\u53ef\u8fed\u4ee3\u7684\u5bf9\u8c61\uff0c\u6bcf\u6b21\u8fed\u4ee3\u8fd4\u56de\u4e00\u884c\u6570\u636e\u3002<\/p>\n<\/p>\nimport csv<\/p>\n\u6253\u5f00CSV\u6587\u4ef6<\/strong><\/h2>\n
open<\/code>\u51fd\u6570\u7528\u4e8e\u6253\u5f00CSV\u6587\u4ef6\uff0ccsv.reader<\/code>\u5c06\u6587\u4ef6\u5bf9\u8c61\u4f20\u5165\u5e76\u8fd4\u56de\u4e00\u4e2a\u8bfb\u53d6\u5668\u5bf9\u8c61\u3002next(csvreader)<\/code>\u7528\u4e8e\u8bfb\u53d6\u6587\u4ef6\u7684\u7b2c\u4e00\u884c\uff08\u901a\u5e38\u662f\u6587\u4ef6\u5934\uff09\uff0c\u63a5\u4e0b\u6765\u7684\u5faa\u73af\u7528\u4e8e\u8bfb\u53d6\u6bcf\u4e00\u884c\u6570\u636e\u3002<\/p>\n<\/p>\n2. \u5199\u5165CSV\u6587\u4ef6<\/h4>\n<\/p>\n
csv.writer<\/code>\u53ef\u4ee5\u5c06\u6570\u636e\u5199\u5165CSV\u6587\u4ef6\u3002writerow<\/code>\u7528\u4e8e\u5199\u5165\u5355\u884c\u6570\u636e\uff0c\u800cwriterows<\/code>\u53ef\u4ee5\u5199\u5165\u591a\u884c\u6570\u636e\u3002<\/p>\n<\/p>\nimport csv<\/p>\n\u51c6\u5907\u6570\u636e<\/strong><\/h2>\n
\u6253\u5f00CSV\u6587\u4ef6\u4ee5\u5199\u5165<\/strong><\/h2>\n
csv.writer<\/code>\u5c06\u5176\u5199\u5165\u5230\u4e00\u4e2a\u65b0\u7684CSV\u6587\u4ef6\u4e2d\u3002<\/p>\n<\/p>\n\u4e8c\u3001\u5904\u7406CSV\u6587\u4ef6\u4e2d\u7684\u7279\u6b8a\u5b57\u7b26\u548c\u6570\u636e\u683c\u5f0f<\/h3>\n<\/p>\n
1. \u7279\u6b8a\u5b57\u7b26\u5904\u7406<\/h4>\n<\/p>\n
csv<\/code>\u6a21\u5757\u63d0\u4f9b\u4e86quotechar<\/code>\u548cquoting<\/code>\u53c2\u6570\u6765\u5e2e\u52a9\u5904\u7406\u8fd9\u4e9b\u5b57\u7b26\u3002<\/p>\n<\/p>\nimport csv<\/p>\n\u6570\u636e\u4e2d\u5305\u542b\u9017\u53f7<\/strong><\/h2>\n
\u5199\u5165CSV\u6587\u4ef6\u65f6\u5904\u7406\u7279\u6b8a\u5b57\u7b26<\/strong><\/h2>\n
quoting=csv.QUOTE_MINIMAL<\/code>\u53c2\u6570\u6307\u793a\u5199\u5165\u5668\u5728\u5fc5\u8981\u65f6\u6dfb\u52a0\u5f15\u53f7\uff0c\u4ee5\u786e\u4fdd\u6570\u636e\u7684\u6b63\u786e\u6027\u3002<\/p>\n<\/p>\n2. \u6570\u636e\u683c\u5f0f\u5904\u7406<\/h4>\n<\/p>\n
import csv<\/p>\n\u6253\u5f00CSV\u6587\u4ef6<\/strong><\/h2>\n
int(row[1])<\/code>\u5c06\u5e74\u9f84\u5b57\u6bb5\u8f6c\u6362\u4e3a\u6574\u6570\u7c7b\u578b\u3002<\/p>\n<\/p>\n\u4e09\u3001\u4f7f\u7528pandas\u5e93\u8fdb\u884cCSV\u6587\u4ef6\u5904\u7406<\/h3>\n<\/p>\n
pandas<\/code>\u5e93\u662fPython\u4e2d\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u5e93\uff0c\u5b83\u53ef\u4ee5\u65b9\u4fbf\u5730\u8bfb\u53d6\u548c\u5199\u5165CSV\u6587\u4ef6\uff0c\u5e76\u63d0\u4f9b\u4e86\u8bb8\u591a\u9ad8\u7ea7\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\u3002<\/p>\n<\/p>\n1. \u8bfb\u53d6CSV\u6587\u4ef6<\/h4>\n<\/p>\n
pandas<\/code>\u8bfb\u53d6CSV\u6587\u4ef6\u53ea\u9700\u4e00\u884c\u4ee3\u7801\u3002read_csv<\/code>\u51fd\u6570\u80fd\u591f\u81ea\u52a8\u5904\u7406\u8bb8\u591a\u6570\u636e\u683c\u5f0f\u95ee\u9898\uff0c\u5e76\u8fd4\u56de\u4e00\u4e2aDataFrame\u5bf9\u8c61\u3002<\/p>\n<\/p>\nimport pandas as pd<\/p>\n\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
\u663e\u793a\u6570\u636e<\/strong><\/h2>\n
df.head()<\/code>\u51fd\u6570\u7528\u4e8e\u663e\u793a\u524d\u51e0\u884c\u6570\u636e\uff0c\u9ed8\u8ba4\u663e\u793a\u524d\u4e94\u884c\u3002<\/p>\n<\/p>\n2. \u5199\u5165CSV\u6587\u4ef6<\/h4>\n<\/p>\n
pandas<\/code>\u4e5f\u53ef\u4ee5\u5c06DataFrame\u5bf9\u8c61\u5199\u5165CSV\u6587\u4ef6\uff0c\u4f7f\u7528to_csv<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5b9e\u73b0\u8fd9\u4e00\u529f\u80fd\u3002<\/p>\n<\/p>\nimport pandas as pd<\/p>\n\u521b\u5efaDataFrame<\/strong><\/h2>\n
\u5199\u5165CSV\u6587\u4ef6<\/strong><\/h2>\n
index=False<\/code>\u53c2\u6570\u7528\u4e8e\u907f\u514d\u5c06\u884c\u7d22\u5f15\u5199\u5165\u6587\u4ef6\u3002<\/p>\n<\/p>\n3. \u6570\u636e\u5904\u7406<\/h4>\n<\/p>\n
pandas<\/code>\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\uff0c\u5982\u6570\u636e\u7b5b\u9009\u3001\u5206\u7ec4\u3001\u805a\u5408\u7b49\u3002<\/p>\n<\/p>\nimport pandas as pd<\/p>\n\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
\u7b5b\u9009\u6570\u636e<\/strong><\/h2>\n
\u6570\u636e\u5206\u7ec4\u548c\u805a\u5408<\/strong><\/h2>\n
df[df['Age'] > 30]<\/code>\u7528\u4e8e\u7b5b\u9009\u5e74\u9f84\u5927\u4e8e30\u7684\u6570\u636e\uff0cgroupby('City').mean()<\/code>\u7528\u4e8e\u6309\u57ce\u5e02\u5206\u7ec4\u5e76\u8ba1\u7b97\u5e73\u5747\u503c\u3002<\/p>\n<\/p>\n\u56db\u3001CSV\u6587\u4ef6\u7684\u9ad8\u7ea7\u64cd\u4f5c<\/h3>\n<\/p>\n
1. \u5904\u7406\u5927\u6587\u4ef6<\/h4>\n<\/p>\n
pandas<\/code>\u7684chunksize<\/code>\u53c2\u6570\u5b9e\u73b0\u5206\u5757\u8bfb\u53d6\u3002<\/p>\n<\/p>\nimport pandas as pd<\/p>\n\u5206\u5757\u8bfb\u53d6\u5927\u6587\u4ef6<\/strong><\/h2>\n
chunksize<\/code>\u53c2\u6570\u6307\u5b9a\u6bcf\u5757\u7684\u884c\u6570\uff0c\u901a\u8fc7\u8fed\u4ee3\u6bcf\u4e2a\u5757\u53ef\u4ee5\u9010\u5757\u5904\u7406\u5927\u6587\u4ef6\u3002<\/p>\n<\/p>\n2. \u5904\u7406\u591a\u79cd\u5206\u9694\u7b26<\/h4>\n<\/p>\n
import pandas as pd<\/p>\n\u8bfb\u53d6\u4f7f\u7528\u5236\u8868\u7b26\u5206\u9694\u7684\u6587\u4ef6<\/strong><\/h2>\n
read_csv<\/code>\u51fd\u6570\u4e2d\u901a\u8fc7sep<\/code>\u53c2\u6570\u6307\u5b9a\u5206\u9694\u7b26\uff0c\u8fd9\u91cc\u4f7f\u7528\u5236\u8868\u7b26\\t<\/code>\u3002<\/p>\n<\/p>\n3. \u5904\u7406\u7f3a\u5931\u503c<\/h4>\n<\/p>\n
pandas<\/code>\u63d0\u4f9b\u4e86\u65b9\u4fbf\u7684\u5904\u7406\u65b9\u6cd5\u3002<\/p>\n<\/p>\nimport pandas as pd<\/p>\n\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
\u5904\u7406\u7f3a\u5931\u503c<\/strong><\/h2>\n
fillna<\/code>\u65b9\u6cd5\u7528\u4e8e\u7528\u6307\u5b9a\u503c\u66ff\u6362\u7f3a\u5931\u503c\u3002\u5728\u8fd9\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u7f3a\u5931\u7684\u5e74\u9f84\u88ab\u66ff\u6362\u4e3a\u5e73\u5747\u5e74\u9f84\u3002<\/p>\n<\/p>\n\u4e94\u3001CSV\u6587\u4ef6\u7684\u5e94\u7528\u573a\u666f<\/h3>\n<\/p>\n
1. \u6570\u636e\u5b58\u50a8\u4e0e\u4ea4\u6362<\/h4>\n<\/p>\n
2. \u6570\u636e\u5206\u6790\u4e0e\u53ef\u89c6\u5316<\/h4>\n<\/p>\n
pandas<\/code>\u5904\u7406CSV\u6587\u4ef6\uff0c\u53ef\u4ee5\u8fdb\u884c\u590d\u6742\u7684\u6570\u636e\u5206\u6790\uff0c\u5e76\u7ed3\u5408\u53ef\u89c6\u5316\u5de5\u5177\uff08\u5982matplotlib<\/code>\u3001seaborn<\/code>\uff09\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\nimport pandas as pd<\/p>\n\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
\u7b80\u5355\u7684\u6570\u636e\u53ef\u89c6\u5316<\/strong><\/h2>\n
3. \u6570\u636e\u5907\u4efd\u4e0e\u65e5\u5fd7\u8bb0\u5f55<\/h4>\n<\/p>\n
\u603b\u7ed3<\/h3>\n<\/p>\n
csv<\/code>\u6a21\u5757\u8fd8\u662fpandas<\/code>\u5e93\uff0c\u90fd\u80fd\u6709\u6548\u5730\u5904\u7406\u6570\u636e\u6587\u4ef6\u3002\u7406\u89e3\u5982\u4f55\u8bfb\u53d6\u3001\u5199\u5165\u3001\u5904\u7406\u7279\u6b8a\u5b57\u7b26\u3001\u7ba1\u7406\u6570\u636e\u683c\u5f0f\u548c\u5904\u7406\u5927\u6587\u4ef6\u662f\u638c\u63e1CSV\u6587\u4ef6\u64cd\u4f5c\u7684\u5173\u952e\u3002<\/strong>\u968f\u7740\u6570\u636e\u79d1\u5b66\u548c\u5206\u6790\u7684\u5174\u8d77\uff0cCSV\u6587\u4ef6\u5728\u6570\u636e\u5904\u7406\u4e2d\u7684\u5e94\u7528\u5c06\u8d8a\u6765\u8d8a\u5e7f\u6cdb\u3002\u901a\u8fc7\u4e0d\u65ad\u5b9e\u8df5\u548c\u5b66\u4e60\uff0c\u80fd\u591f\u66f4\u9ad8\u6548\u5730\u4f7f\u7528CSV\u6587\u4ef6\u8fdb\u884c\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684csv<\/code>\u6a21\u5757\u6765\u8bfb\u53d6CSV\u6587\u4ef6\u3002\u9996\u5148\uff0c\u60a8\u9700\u8981\u5bfc\u5165\u8be5\u6a21\u5757\uff0c\u7136\u540e\u4f7f\u7528csv.reader()<\/code>\u51fd\u6570\u6253\u5f00\u5e76\u8bfb\u53d6\u6587\u4ef6\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u8bfb\u53d6CSV\u6587\u4ef6\u5e76\u6253\u5370\u6bcf\u4e00\u884c\uff1a<\/p>\nimport csv\n\nwith open('your_file.csv', mode='r') as file:\n reader = csv.reader(file)\n for row in reader:\n print(row)\n<\/code><\/pre>\n
\u60a8\u53ef\u4ee5\u4f7f\u7528csv.writer()<\/code>\u51fd\u6570\u5c06\u6570\u636e\u5199\u5165CSV\u6587\u4ef6\u3002\u9996\u5148\uff0c\u6253\u5f00\u4e00\u4e2a\u6587\u4ef6\u5e76\u8bbe\u7f6e\u4e3a\u5199\u5165\u6a21\u5f0f\uff0c\u7136\u540e\u4f7f\u7528writerow()<\/code>\u6216writerows()<\/code>\u65b9\u6cd5\u5199\u5165\u5355\u884c\u6216\u591a\u884c\u6570\u636e\u3002\u4f8b\u5982\uff1a<\/p>\nimport csv\n\ndata = [['Name', 'Age'], ['Alice', 30], ['Bob', 25]]\n\nwith open('output_file.csv', mode='w', newline='') as file:\n writer = csv.writer(file)\n writer.writerows(data)\n<\/code><\/pre>\n
\u5728\u5904\u7406\u5e26\u6709\u6807\u9898\u7684CSV\u6587\u4ef6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528csv.DictReader()<\/code>\u6765\u7b80\u5316\u6570\u636e\u7684\u8bfb\u53d6\u3002\u8fd9\u4e2a\u65b9\u6cd5\u4f1a\u5c06\u6bcf\u4e00\u884c\u8f6c\u6362\u4e3a\u5b57\u5178\uff0c\u6807\u9898\u884c\u4f1a\u6210\u4e3a\u5b57\u5178\u7684\u952e\u3002\u4f8b\u5982\uff1a<\/p>\nimport csv\n\nwith open('your_file_with_headers.csv', mode='r') as file:\n reader = csv.DictReader(file)\n for row in reader:\n print(row['Name'], row['Age']) # \u8bbf\u95ee\u7279\u5b9a\u5217\n<\/code><\/pre>\n