{"id":1161798,"date":"2025-01-13T19:20:49","date_gmt":"2025-01-13T11:20:49","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1161798.html"},"modified":"2025-01-13T19:20:52","modified_gmt":"2025-01-13T11:20:52","slug":"csv%e6%95%b0%e6%8d%ae%e5%9c%a8python%e5%a6%82%e4%bd%95%e5%af%bc%e5%85%a5","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1161798.html","title":{"rendered":"csv\u6570\u636e\u5728python\u5982\u4f55\u5bfc\u5165"},"content":{"rendered":"

\"csv\u6570\u636e\u5728python\u5982\u4f55\u5bfc\u5165\"<\/p>\n

\u5728Python\u4e2d\u5bfc\u5165CSV\u6570\u636e\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5e38\u7528\u7684\u6709\u4f7f\u7528pandas\u5e93\u3001csv\u5e93\u3001numpy\u5e93\u7b49\u3002<\/strong>\u5176\u4e2d\uff0cpandas\u5e93<\/strong>\u662f\u6700\u5e38\u7528\u4e14\u529f\u80fd\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u56e0\u4e3a\u5b83\u4e0d\u4ec5\u53ef\u4ee5\u8f7b\u677e\u5730\u5bfc\u5165CSV\u6570\u636e\uff0c\u8fd8\u63d0\u4f9b\u4e86\u8bb8\u591a\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u7684\u529f\u80fd\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u63cf\u8ff0\u4f7f\u7528pandas\u5e93\u5bfc\u5165CSV\u6570\u636e\u7684\u6b65\u9aa4\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528pandas\u5e93\u5bfc\u5165CSV\u6570\u636e<\/h3>\n<\/p>\n

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

\u9996\u5148\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5df2\u5b89\u88c5pandas\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. \u5bfc\u5165pandas\u5e93<\/h4>\n<\/p>\n
\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165pandas\u5e93\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u4f7f\u7528read_csv\u65b9\u6cd5\u5bfc\u5165CSV\u6570\u636e<\/h4>\n<\/p>\n
\u4f7f\u7528pandas\u7684read_csv<\/code>\u65b9\u6cd5\u53ef\u4ee5\u8f7b\u677e\u5bfc\u5165CSV\u6570\u636e\uff1a<\/p>\n<\/p>\n
df = pd.read_csv('path_to_your_file.csv')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u91cc\uff0cdf<\/code>\u662f\u4e00\u4e2aDataFrame\u5bf9\u8c61\uff0c\u5b58\u50a8\u4e86CSV\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
4. \u5904\u7406CSV\u6570\u636e<\/h4>\n<\/p>\n
\u5bfc\u5165\u6570\u636e\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528pandas\u63d0\u4f9b\u7684\u5404\u79cd\u65b9\u6cd5\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u3002\u4f8b\u5982\uff0c\u67e5\u770b\u6570\u636e\u7684\u524d\u51e0\u884c\uff1a<\/p>\n<\/p>\n
print(df.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528csv\u5e93\u5bfc\u5165CSV\u6570\u636e<\/h3>\n<\/p>\n
1. \u5bfc\u5165csv\u5e93<\/h4>\n<\/p>\n
\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165csv\u5e93\uff1a<\/p>\n<\/p>\n
import csv<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u6253\u5f00CSV\u6587\u4ef6\u5e76\u8bfb\u53d6\u6570\u636e<\/h4>\n<\/p>\n
\u4f7f\u7528csv\u5e93\u7684reader<\/code>\u65b9\u6cd5\u53ef\u4ee5\u9010\u884c\u8bfb\u53d6CSV\u6570\u636e\uff1a<\/p>\n<\/p>\n
with open('path_to_your_file.csv', newline='') as csvfile:<\/p>\n
    csvreader = csv.reader(csvfile)<\/p>\n
    for row in csvreader:<\/p>\n
        print(row)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u5904\u7406CSV\u6570\u636e<\/h4>\n<\/p>\n
\u4f7f\u7528csv\u5e93\u8bfb\u53d6\u6570\u636e\u540e\uff0c\u53ef\u4ee5\u6309\u884c\u5904\u7406\u6570\u636e\u3002\u4f8b\u5982\uff0c\u5c06\u6570\u636e\u5b58\u50a8\u5728\u5217\u8868\u4e2d\uff1a<\/p>\n<\/p>\n
data = []<\/p>\n
with open('path_to_your_file.csv', newline='') as csvfile:<\/p>\n
    csvreader = csv.reader(csvfile)<\/p>\n
    for row in csvreader:<\/p>\n
        data.append(row)<\/p>\n
print(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528numpy\u5e93\u5bfc\u5165CSV\u6570\u636e<\/h3>\n<\/p>\n
1. \u5b89\u88c5numpy\u5e93<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5df2\u5b89\u88c5numpy\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. \u5bfc\u5165numpy\u5e93<\/h4>\n<\/p>\n
\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165numpy\u5e93\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u4f7f\u7528genfromtxt\u65b9\u6cd5\u5bfc\u5165CSV\u6570\u636e<\/h4>\n<\/p>\n
\u4f7f\u7528numpy\u7684genfromtxt<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5bfc\u5165CSV\u6570\u636e\uff1a<\/p>\n<\/p>\n
data = np.genfromtxt('path_to_your_file.csv', delimiter=',')<\/p>\n
print(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u5bfc\u5165CSV\u6570\u636e\u7684\u5e38\u89c1\u95ee\u9898\u53ca\u89e3\u51b3\u65b9\u6cd5<\/h3>\n<\/p>\n
1. \u5904\u7406\u7f3a\u5931\u503c<\/h4>\n<\/p>\n
\u5728\u5b9e\u9645\u6570\u636e\u5904\u7406\u4e2d\uff0cCSV\u6587\u4ef6\u4e2d\u53ef\u80fd\u5305\u542b\u7f3a\u5931\u503c\u3002pandas\u63d0\u4f9b\u4e86\u5904\u7406\u7f3a\u5931\u503c\u7684\u529f\u80fd\uff1a<\/p>\n<\/p>\n
df = pd.read_csv('path_to_your_file.csv', na_values=['NA', 'N\/A', ''])<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u91cc\uff0cna_values<\/code>\u53c2\u6570\u7528\u4e8e\u6307\u5b9a\u54ea\u4e9b\u503c\u5e94\u88ab\u89c6\u4e3a\u7f3a\u5931\u503c\u3002<\/p>\n<\/p>\n
2. \u6307\u5b9a\u5217\u540d<\/h4>\n<\/p>\n
\u6709\u65f6CSV\u6587\u4ef6\u4e2d\u4e0d\u5305\u542b\u5217\u540d\uff0c\u53ef\u4ee5\u5728\u5bfc\u5165\u65f6\u6307\u5b9a\u5217\u540d\uff1a<\/p>\n<\/p>\n
df = pd.read_csv('path_to_your_file.csv', names=['col1', 'col2', 'col3'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u8bfb\u53d6\u5927\u6587\u4ef6<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u975e\u5e38\u5927\u7684CSV\u6587\u4ef6\uff0c\u53ef\u4ee5\u4f7f\u7528chunksize<\/code>\u53c2\u6570\u5206\u5757\u8bfb\u53d6\uff1a<\/p>\n<\/p>\n
chunk_size = 10000<\/p>\n
chunks = pd.read_csv('path_to_your_file.csv', chunksize=chunk_size)<\/p>\n
for chunk in chunks:<\/p>\n
    process(chunk)  # \u5904\u7406\u6bcf\u4e2a\u5757<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u5728Python\u4e2d\u5bfc\u5165CSV\u6570\u636e\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5176\u4e2d\u4f7f\u7528pandas\u5e93\u662f\u6700\u5e38\u7528\u7684\u65b9\u5f0f\u3002pandas\u5e93\u529f\u80fd\u5f3a\u5927\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u529f\u80fd<\/strong>\uff0c\u9002\u5408\u5927\u591a\u6570\u6570\u636e\u5904\u7406\u9700\u6c42\u3002csv\u5e93\u548cnumpy\u5e93<\/strong>\u4e5f\u63d0\u4f9b\u4e86\u7b80\u5355\u6709\u6548\u7684CSV\u6570\u636e\u5bfc\u5165\u65b9\u6cd5\uff0c\u9002\u5408\u4e0d\u540c\u7684\u5e94\u7528\u573a\u666f\u3002\u901a\u8fc7\u5408\u7406\u9009\u62e9\u548c\u4f7f\u7528\u8fd9\u4e9b\u5de5\u5177\uff0c\u53ef\u4ee5\u9ad8\u6548\u5730\u5bfc\u5165\u548c\u5904\u7406CSV\u6570\u636e\uff0c\u4e3a\u540e\u7eed\u7684\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u6253\u4e0b\u575a\u5b9e\u7684\u57fa\u7840\u3002<\/p>\n<\/p>\n
\u516d\u3001\u5b9e\u6218\u6848\u4f8b<\/h3>\n<\/p>\n
\u4e3a\u4e86\u66f4\u597d\u5730\u7406\u89e3\u5982\u4f55\u5728Python\u4e2d\u5bfc\u5165CSV\u6570\u636e\uff0c\u4e0b\u9762\u901a\u8fc7\u4e00\u4e2a\u5b9e\u6218\u6848\u4f8b\u6765\u8be6\u7ec6\u6f14\u793a\u4f7f\u7528pandas\u5e93\u8fdb\u884cCSV\u6570\u636e\u5bfc\u5165\u548c\u5904\u7406\u7684\u5168\u8fc7\u7a0b\u3002<\/p>\n<\/p>\n
1. \u51c6\u5907\u6570\u636e<\/h4>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u540d\u4e3adata.csv<\/code>\u7684CSV\u6587\u4ef6\uff0c\u5185\u5bb9\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
name,age,city<\/p>\n
Alice,30,New York<\/p>\n
Bob,25,San Francisco<\/p>\n
Charlie,35,Los Angeles<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u5bfc\u5165\u6570\u636e<\/h4>\n<\/p>\n
\u4f7f\u7528pandas\u5e93\u5bfc\u5165\u4e0a\u8ff0CSV\u6587\u4ef6\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u5bfc\u5165CSV\u6570\u636e<\/strong><\/h2>\n
df = pd.read_csv('data.csv')<\/p>\n
\u67e5\u770b\u6570\u636e<\/strong><\/h2>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u6570\u636e\u5904\u7406<\/h4>\n<\/p>\n
\u5bfc\u5165\u6570\u636e\u540e\uff0c\u53ef\u4ee5\u8fdb\u884c\u5404\u79cd\u6570\u636e\u5904\u7406\u64cd\u4f5c\u3002\u4f8b\u5982\uff0c\u8ba1\u7b97\u6bcf\u4e2a\u4eba\u7684\u5e74\u9f84\u5e73\u5747\u503c\uff1a<\/p>\n<\/p>\n
average_age = df['age'].mean()<\/p>\n
print(f"Average age: {average_age}")<\/p>\n
<\/code><\/pre>\n<\/p>\n
4. \u6570\u636e\u5206\u6790<\/h4>\n<\/p>\n
\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u66f4\u591a\u7684\u5206\u6790\u64cd\u4f5c\u3002\u4f8b\u5982\uff0c\u6309\u57ce\u5e02\u5206\u7ec4\u5e76\u8ba1\u7b97\u6bcf\u4e2a\u57ce\u5e02\u7684\u5e73\u5747\u5e74\u9f84\uff1a<\/p>\n<\/p>\n
grouped = df.groupby('city')['age'].mean()<\/p>\n
print(grouped)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u6848\u4f8b\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u4f7f\u7528pandas\u5e93\u5bfc\u5165CSV\u6570\u636e\u540e\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u64cd\u4f5c\u3002\u8fd9\u662f\u56e0\u4e3apandas\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\uff0c\u4f7f\u6570\u636e\u5206\u6790\u53d8\u5f97\u7b80\u5355\u9ad8\u6548<\/strong>\u3002<\/p>\n<\/p>\n
\u4e03\u3001\u8fdb\u9636\u4f7f\u7528<\/h3>\n<\/p>\n
\u9664\u4e86\u57fa\u672c\u7684\u5bfc\u5165\u548c\u5904\u7406\u64cd\u4f5c\u5916\uff0cpandas\u5e93\u8fd8\u63d0\u4f9b\u4e86\u8bb8\u591a\u9ad8\u7ea7\u529f\u80fd\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
1. \u8bfb\u53d6\u7279\u5b9a\u5217<\/h4>\n<\/p>\n
\u5982\u679c\u53ea\u9700\u8981\u8bfb\u53d6CSV\u6587\u4ef6\u4e2d\u7684\u7279\u5b9a\u5217\uff0c\u53ef\u4ee5\u4f7f\u7528usecols<\/code>\u53c2\u6570\uff1a<\/p>\n<\/p>\n
df = pd.read_csv('data.csv', usecols=['name', 'city'])<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u8bbe\u7f6e\u7d22\u5f15\u5217<\/h4>\n<\/p>\n
\u53ef\u4ee5\u5728\u5bfc\u5165\u6570\u636e\u65f6\u5c06\u67d0\u4e00\u5217\u8bbe\u7f6e\u4e3a\u7d22\u5f15\u5217\uff1a<\/p>\n<\/p>\n
df = pd.read_csv('data.csv', index_col='name')<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u5904\u7406\u65e5\u671f\u6570\u636e<\/h4>\n<\/p>\n
\u5982\u679cCSV\u6587\u4ef6\u4e2d\u5305\u542b\u65e5\u671f\u6570\u636e\uff0c\u53ef\u4ee5\u5728\u5bfc\u5165\u65f6\u8fdb\u884c\u65e5\u671f\u89e3\u6790\uff1a<\/p>\n<\/p>\n
df = pd.read_csv('data.csv', parse_dates=['date'])<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
4. \u9ad8\u6548\u8bfb\u53d6\u5927\u6587\u4ef6<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u975e\u5e38\u5927\u7684CSV\u6587\u4ef6\uff0c\u53ef\u4ee5\u4f7f\u7528dask<\/code>\u5e93\u8fdb\u884c\u5e76\u884c\u8bfb\u53d6\u548c\u5904\u7406\uff1a<\/p>\n<\/p>\n
import dask.dataframe as dd<\/p>\n
\u4f7f\u7528dask\u8bfb\u53d6\u5927\u6587\u4ef6<\/strong><\/h2>\n
df = dd.read_csv('large_data.csv')<\/p>\n
print(df.head())<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516b\u3001\u603b\u7ed3\u548c\u5c55\u671b<\/h3>\n<\/p>\n
\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u6211\u4eec\u8be6\u7ec6\u8ba8\u8bba\u4e86\u5728Python\u4e2d\u5bfc\u5165CSV\u6570\u636e\u7684\u591a\u79cd\u65b9\u6cd5\uff0c\u91cd\u70b9\u4ecb\u7ecd\u4e86\u4f7f\u7528pandas\u5e93\u7684\u5177\u4f53\u64cd\u4f5c\u6b65\u9aa4\u548c\u9ad8\u7ea7\u529f\u80fd\u3002pandas\u5e93\u662f\u6570\u636e\u79d1\u5b66\u548c\u6570\u636e\u5206\u6790\u4e2d\u7684\u91cd\u8981\u5de5\u5177<\/strong>\uff0c\u5176\u5f3a\u5927\u7684\u529f\u80fd\u548c\u7b80\u6d01\u7684\u63a5\u53e3\u4f7f\u5f97\u6570\u636e\u5904\u7406\u53d8\u5f97\u7b80\u5355\u9ad8\u6548\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\u5de5\u5177\uff0c\u53ef\u4ee5\u5927\u5927\u63d0\u9ad8\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u7684\u6548\u7387\u3002\u672a\u6765\uff0c\u968f\u7740\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60<\/a>\u7684\u53d1\u5c55\uff0c\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u5de5\u5177\u5c06\u4e0d\u65ad\u8fdb\u6b65\u548c\u5b8c\u5584<\/strong>\uff0c\u6211\u4eec\u9700\u8981\u4e0d\u65ad\u5b66\u4e60\u548c\u638c\u63e1\u65b0\u7684\u6280\u672f\u548c\u65b9\u6cd5\uff0c\u4ee5\u5e94\u5bf9\u65e5\u76ca\u590d\u6742\u7684\u6570\u636e\u5904\u7406\u9700\u6c42\u3002<\/p>\n<\/p>\n
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