{"id":1053269,"date":"2024-12-31T14:32:30","date_gmt":"2024-12-31T06:32:30","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1053269.html"},"modified":"2024-12-31T14:32:32","modified_gmt":"2024-12-31T06:32:32","slug":"python%e5%a6%82%e4%bd%95%e4%bb%8ecsv%e6%96%87%e4%bb%b6%e4%b8%ad%e7%ad%9b%e9%80%89%e6%95%b0%e6%8d%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1053269.html","title":{"rendered":"python\u5982\u4f55\u4ececsv\u6587\u4ef6\u4e2d\u7b5b\u9009\u6570\u636e"},"content":{"rendered":"

\"python\u5982\u4f55\u4ececsv\u6587\u4ef6\u4e2d\u7b5b\u9009\u6570\u636e\"<\/p>\n

\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\u4eceCSV\u6587\u4ef6\u4e2d\u7b5b\u9009\u6570\u636e\u3002\u5e38\u7528\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528pandas\u5e93\u3001csv\u6a21\u5757\u3001numpy\u5e93<\/strong>\u3002\u5176\u4e2d\uff0cpandas\u5e93\u662f\u6700\u5e38\u7528\u548c\u6700\u5f3a\u5927\u7684\u5de5\u5177\u4e4b\u4e00\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u975e\u5e38\u65b9\u4fbf\u7684\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u529f\u80fd\u3002\u4e0b\u9762\u6211\u4eec\u5c06\u91cd\u70b9\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528pandas\u5e93\u4eceCSV\u6587\u4ef6\u4e2d\u7b5b\u9009\u6570\u636e<\/strong>\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/h3>\n<\/p>\n

\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u8bfb\u53d6CSV\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u3002pandas\u5e93\u63d0\u4f9b\u4e86\u4e00\u4e2a\u975e\u5e38\u65b9\u4fbf\u7684\u51fd\u6570read_csv()<\/code>\u6765\u8bfb\u53d6CSV\u6587\u4ef6\u3002\u4ee5\u4e0b\u662f\u793a\u4f8b\u4ee3\u7801\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
<\/code><\/pre>\n<\/p>\n
read_csv()<\/code>\u51fd\u6570\u4f1a\u5c06CSV\u6587\u4ef6\u4e2d\u7684\u6570\u636e\u8bfb\u53d6\u5230\u4e00\u4e2aDataFrame\u5bf9\u8c61\u4e2d\uff0cDataFrame\u662fpandas\u5e93\u4e2d\u7528\u4e8e\u5b58\u50a8\u548c\u64cd\u4f5c\u8868\u683c\u6570\u636e\u7684\u4e3b\u8981\u6570\u636e\u7ed3\u6784\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u6309\u6761\u4ef6\u7b5b\u9009\u6570\u636e<\/h3>\n<\/p>\n
1\u3001\u5355\u4e2a\u6761\u4ef6\u7b5b\u9009<\/h4>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5305\u542b\u5458\u5de5\u4fe1\u606f\u7684CSV\u6587\u4ef6\uff0c\u6587\u4ef6\u4e2d\u6709\u4e00\u4e2a\u5217\u540d\u4e3a\u201cAge\u201d\uff0c\u6211\u4eec\u5e0c\u671b\u7b5b\u9009\u51fa\u5e74\u9f84\u5927\u4e8e30\u5c81\u7684\u5458\u5de5\u3002\u53ef\u4ee5\u4f7f\u7528\u5e03\u5c14\u7d22\u5f15\u6765\u5b9e\u73b0\uff1a<\/p>\n<\/p>\n
# \u7b5b\u9009\u5e74\u9f84\u5927\u4e8e30\u5c81\u7684\u5458\u5de5<\/p>\n
filtered_df = df[df['Age'] > 30]<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u591a\u4e2a\u6761\u4ef6\u7b5b\u9009<\/h4>\n<\/p>\n
\u5982\u679c\u6211\u4eec\u9700\u8981\u57fa\u4e8e\u591a\u4e2a\u6761\u4ef6\u8fdb\u884c\u7b5b\u9009\uff0c\u53ef\u4ee5\u4f7f\u7528\u903b\u8f91\u8fd0\u7b97\u7b26&<\/code>\uff08\u4e0e\uff09\u3001|<\/code>\uff08\u6216\uff09\u7ed3\u5408\u5e03\u5c14\u7d22\u5f15\u3002\u4f8b\u5982\uff0c\u7b5b\u9009\u51fa\u5e74\u9f84\u5927\u4e8e30\u5c81\u4e14\u804c\u4f4d\u4e3a\u201cManager\u201d\u7684\u5458\u5de5\uff1a<\/p>\n<\/p>\n
# \u7b5b\u9009\u5e74\u9f84\u5927\u4e8e30\u5c81\u4e14\u804c\u4f4d\u4e3a\u201cManager\u201d\u7684\u5458\u5de5<\/p>\n
filtered_df = df[(df['Age'] > 30) & (df['Position'] == 'Manager')]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u6309\u5217\u7b5b\u9009\u6570\u636e<\/h3>\n<\/p>\n
\u6709\u65f6\u6211\u4eec\u53ea\u9700\u8981CSV\u6587\u4ef6\u4e2d\u7684\u67d0\u4e9b\u5217\uff0c\u53ef\u4ee5\u4f7f\u7528loc<\/code>\u6216iloc<\/code>\u5c5e\u6027\u6765\u9009\u62e9\u7279\u5b9a\u7684\u5217\u3002<\/p>\n<\/p>\n
1\u3001\u4f7f\u7528loc\u5c5e\u6027\u6309\u5217\u7b5b\u9009<\/h4>\n<\/p>\n
loc<\/code>\u5c5e\u6027\u901a\u8fc7\u6807\u7b7e\u9009\u62e9\u884c\u548c\u5217\u3002\u4f8b\u5982\uff0c\u9009\u62e9\u201cName\u201d\u548c\u201cAge\u201d\u4e24\u5217\uff1a<\/p>\n<\/p>\n
# \u9009\u62e9\u201cName\u201d\u548c\u201cAge\u201d\u4e24\u5217<\/p>\n
selected_columns = df.loc[:, ['Name', 'Age']]<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528iloc\u5c5e\u6027\u6309\u5217\u7b5b\u9009<\/h4>\n<\/p>\n
iloc<\/code>\u5c5e\u6027\u901a\u8fc7\u4f4d\u7f6e\u9009\u62e9\u884c\u548c\u5217\u3002\u4f8b\u5982\uff0c\u9009\u62e9\u7b2c1\u5217\u548c\u7b2c3\u5217\uff1a<\/p>\n<\/p>\n
# \u9009\u62e9\u7b2c1\u5217\u548c\u7b2c3\u5217<\/p>\n
selected_columns = df.iloc[:, [0, 2]]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u6309\u884c\u7b5b\u9009\u6570\u636e<\/h3>\n<\/p>\n
\u6709\u65f6\u6211\u4eec\u9700\u8981\u6309\u884c\u7b5b\u9009\u6570\u636e\uff0c\u4f8b\u5982\uff0c\u6211\u4eec\u5e0c\u671b\u9009\u62e9\u524d10\u884c\u6570\u636e\uff1a<\/p>\n<\/p>\n
# \u9009\u62e9\u524d10\u884c\u6570\u636e<\/p>\n
first_10_rows = df.head(10)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u6309\u7d22\u5f15\u7b5b\u9009\u6570\u636e<\/h3>\n<\/p>\n
\u5982\u679cCSV\u6587\u4ef6\u4e2d\u5305\u542b\u7d22\u5f15\u5217\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u7d22\u5f15\u6765\u7b5b\u9009\u6570\u636e\u3002\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u7684CSV\u6587\u4ef6\u4e2d\u5305\u542b\u4e00\u4e2a\u201cID\u201d\u5217\u4f5c\u4e3a\u7d22\u5f15\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528set_index()<\/code>\u51fd\u6570\u5c06\u5176\u8bbe\u7f6e\u4e3a\u7d22\u5f15\u5217\uff0c\u7136\u540e\u6309\u7d22\u5f15\u7b5b\u9009\u6570\u636e\uff1a<\/p>\n<\/p>\n
# \u5c06\u201cID\u201d\u5217\u8bbe\u7f6e\u4e3a\u7d22\u5f15<\/p>\n
df.set_index('ID', inplace=True)<\/p>\n
\u6839\u636e\u7d22\u5f15\u7b5b\u9009\u6570\u636e<\/strong><\/h2>\n
filtered_df = df.loc[1:5]  # \u9009\u62e9ID\u4ece1\u52305\u7684\u6570\u636e<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u5904\u7406\u7f3a\u5931\u503c<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u5de5\u4f5c\u4e2d\uff0cCSV\u6587\u4ef6\u4e2d\u53ef\u80fd\u5305\u542b\u7f3a\u5931\u503c\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528pandas\u5e93\u4e2d\u7684dropna()<\/code>\u51fd\u6570\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c\uff0c\u6216\u4f7f\u7528fillna()<\/code>\u51fd\u6570\u586b\u5145\u7f3a\u5931\u503c\u3002\u4f8b\u5982\uff0c\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c\uff1a<\/p>\n<\/p>\n
# \u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c<\/p>\n
cleaned_df = df.dropna()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6216\u8005\u586b\u5145\u7f3a\u5931\u503c\uff1a<\/p>\n<\/p>\n
# \u7528\u5e73\u5747\u503c\u586b\u5145\u7f3a\u5931\u503c<\/p>\n
df['Age'].fillna(df['Age'].mean(), inplace=True)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u4f7f\u7528pandas\u5e93\u4eceCSV\u6587\u4ef6\u4e2d\u7b5b\u9009\u6570\u636e\u3002pandas\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u529f\u80fd\uff0c\u4f7f\u5f97\u6570\u636e\u7b5b\u9009\u53d8\u5f97\u975e\u5e38\u7b80\u5355\u548c\u9ad8\u6548<\/strong>\u3002\u65e0\u8bba\u662f\u6309\u6761\u4ef6\u7b5b\u9009\u3001\u6309\u5217\u7b5b\u9009\u3001\u6309\u884c\u7b5b\u9009\u8fd8\u662f\u5904\u7406\u7f3a\u5931\u503c\uff0cpandas\u90fd\u80fd\u6ee1\u8db3\u6211\u4eec\u7684\u9700\u6c42\u3002<\/p>\n<\/p>\n
\u6b64\u5916\uff0cpandas\u5e93\u8fd8\u652f\u6301\u8bb8\u591a\u5176\u4ed6\u9ad8\u7ea7\u6570\u636e\u64cd\u4f5c\uff0c\u5982\u6570\u636e\u5206\u7ec4\u3001\u6570\u636e\u5408\u5e76\u3001\u6570\u636e\u900f\u89c6\u8868\u7b49\u3002\u5728\u5b9e\u9645\u5de5\u4f5c\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\u7075\u6d3b\u4f7f\u7528\u8fd9\u4e9b\u529f\u80fd\uff0c\u63d0\u9ad8\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n
\u5e0c\u671b\u901a\u8fc7\u672c\u6587\u7684\u4ecb\u7ecd\uff0c\u5927\u5bb6\u80fd\u591f\u66f4\u597d\u5730\u638c\u63e1\u5982\u4f55\u4f7f\u7528pandas\u5e93\u4eceCSV\u6587\u4ef6\u4e2d\u7b5b\u9009\u6570\u636e\uff0c\u5e76\u5728\u5b9e\u9645\u5de5\u4f5c\u4e2d\u5e94\u7528\u8fd9\u4e9b\u6280\u5de7\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u8bfb\u53d6CSV\u6587\u4ef6\u4e2d\u7684\u6570\u636e\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5185\u7f6e\u7684csv<\/code>\u6a21\u5757\u6216pandas<\/code>\u5e93\u6765\u8bfb\u53d6CSV\u6587\u4ef6\u3002\u4f7f\u7528pandas<\/code>\u5e93\u7684\u65b9\u5f0f\u66f4\u4e3a\u7b80\u5355\u548c\u9ad8\u6548\u3002\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5pandas<\/code>\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u547d\u4ee4pip install pandas<\/code>\u8fdb\u884c\u5b89\u88c5\u3002\u8bfb\u53d6CSV\u6587\u4ef6\u7684\u57fa\u672c\u8bed\u6cd5\u5982\u4e0b\uff1a  <\/p>\n
import pandas as pd\n\ndata = pd.read_csv('\u6587\u4ef6\u8def\u5f84.csv')\n<\/code><\/pre>\n
\u8fd9\u5c06\u8fd4\u56de\u4e00\u4e2aDataFrame\u5bf9\u8c61\uff0c\u5305\u542bCSV\u6587\u4ef6\u4e2d\u7684\u6240\u6709\u6570\u636e\u3002<\/p>\n
\u5728\u7b5b\u9009\u6570\u636e\u65f6\uff0c\u5982\u4f55\u9009\u62e9\u7279\u5b9a\u7684\u5217\uff1f<\/strong>
\u4f7f\u7528pandas<\/code>\u5e93\u53ef\u4ee5\u65b9\u4fbf\u5730\u9009\u62e9\u7279\u5b9a\u7684\u5217\u3002\u5047\u8bbe\u4f60\u53ea\u60f3\u8981\u540d\u4e3a\u201cColumn1\u201d\u548c\u201cColumn2\u201d\u7684\u5217\uff0c\u53ef\u4ee5\u8fd9\u6837\u505a\uff1a  <\/p>\n
filtered_data = data[['Column1', 'Column2']]\n<\/code><\/pre>\n
\u8fd9\u5c06\u8fd4\u56de\u4e00\u4e2a\u65b0\u7684DataFrame\uff0c\u4ec5\u5305\u542b\u4f60\u6307\u5b9a\u7684\u5217\u3002<\/p>\n
\u5982\u4f55\u6839\u636e\u6761\u4ef6\u7b5b\u9009CSV\u6587\u4ef6\u4e2d\u7684\u884c\uff1f<\/strong>
\u53ef\u4ee5\u901a\u8fc7\u5e03\u5c14\u7d22\u5f15\u6765\u7b5b\u9009\u6ee1\u8db3\u7279\u5b9a\u6761\u4ef6\u7684\u884c\u3002\u4f8b\u5982\uff0c\u5982\u679c\u4f60\u5e0c\u671b\u7b5b\u9009\u51fa\u201cColumn1\u201d\u4e2d\u503c\u5927\u4e8e50\u7684\u6240\u6709\u884c\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a  <\/p>\n
filtered_data = data[data['Column1'] > 50]\n<\/code><\/pre>\n
\u8fd9\u6837\uff0cfiltered_data<\/code>\u5c06\u53ea\u5305\u542b\u201cColumn1\u201d\u4e2d\u5927\u4e8e50\u7684\u884c\uff0c\u65b9\u4fbf\u8fdb\u884c\u540e\u7eed\u7684\u6570\u636e\u5206\u6790\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\u4eceCSV\u6587\u4ef6\u4e2d\u7b5b\u9009\u6570\u636e\u3002\u5e38\u7528\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528pandas\u5e93\u3001csv\u6a21\u5757\u3001num […]","protected":false},"author":3,"featured_media":1053276,"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\/1053269"}],"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=1053269"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1053269\/revisions"}],"predecessor-version":[{"id":1053281,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1053269\/revisions\/1053281"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1053276"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1053269"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1053269"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1053269"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}