{"id":946441,"date":"2024-12-26T23:42:20","date_gmt":"2024-12-26T15:42:20","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/946441.html"},"modified":"2024-12-26T23:42:22","modified_gmt":"2024-12-26T15:42:22","slug":"python%e5%a6%82%e4%bd%95%e6%88%aa%e5%8f%96%e5%88%97","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/946441.html","title":{"rendered":"python\u5982\u4f55\u622a\u53d6\u5217"},"content":{"rendered":"

\"python\u5982\u4f55\u622a\u53d6\u5217\"<\/p>\n

\u5728Python\u4e2d\u622a\u53d6\u5217\u7684\u5e38\u89c1\u65b9\u6cd5\u6709\uff1a\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528NumPy\u5e93\u3001\u901a\u8fc7\u5217\u8868\u89e3\u6790\u3002<\/strong>Pandas\u5e93\u662f\u5904\u7406\u6570\u636e\u5206\u6790\u4efb\u52a1\u7684\u5f3a\u5927\u5de5\u5177\uff0c\u5177\u6709\u7b80\u5355\u6613\u7528\u7684\u63a5\u53e3\uff1bNumPy\u5e93\u9002\u5408\u5904\u7406\u6570\u503c\u8ba1\u7b97\u548c\u591a\u7ef4\u6570\u7ec4\u64cd\u4f5c\uff1b\u5217\u8868\u89e3\u6790\u5219\u63d0\u4f9b\u4e86\u4e00\u79cd\u7075\u6d3b\u7684\u65b9\u5f0f\u6765\u64cd\u4f5c\u5217\u8868\u4e2d\u7684\u6570\u636e\u3002\u5728\u8fd9\u91cc\uff0c\u6211\u4eec\u91cd\u70b9\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Pandas\u5e93\u6765\u622a\u53d6\u5217\uff0c\u56e0\u4e3a\u5b83\u662f\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u7684\u6807\u51c6\u5de5\u5177\u4e4b\u4e00\u3002<\/p>\n<\/p>\n

\u8981\u4f7f\u7528Pandas\u5e93\u622a\u53d6\u5217\uff0c\u9996\u5148\u9700\u8981\u786e\u4fdd\u5df2\u5b89\u88c5Pandas\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u5b89\u88c5Pandas\u5e93\uff1a<\/p>\n<\/p>\n

pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u8bfb\u53d6\u6570\u636e\u6587\u4ef6\uff08\u5982CSV\u6587\u4ef6\uff09\uff0c\u5e76\u63d0\u53d6\u6240\u9700\u7684\u5217\u3002\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2aCSV\u6587\u4ef6\u5305\u542b\u591a\u4e2a\u5217\u7684\u6570\u636e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u5b9e\u73b0\u5217\u7684\u622a\u53d6\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
data = pd.read_csv('file.csv')<\/p>\n
\u622a\u53d6\u7279\u5b9a\u5217<\/strong><\/h2>\n
column_data = data['column_name']<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u9762\u7684\u4ee3\u7801\u4e2d\uff0cpd.read_csv('file.csv')<\/code>\u7528\u4e8e\u8bfb\u53d6CSV\u6587\u4ef6\u5e76\u8fd4\u56de\u4e00\u4e2aDataFrame\u5bf9\u8c61\u3002data['column_name']<\/code>\u7528\u4e8e\u4eceDataFrame\u4e2d\u63d0\u53d6\u7279\u5b9a\u5217\u7684\u6570\u636e\uff0c\u5e76\u8fd4\u56de\u4e00\u4e2aSeries\u5bf9\u8c61\u3002<\/p>\n<\/p>\n
\u4e00\u3001\u4f7f\u7528Pandas\u5e93\u622a\u53d6\u5217<\/h3>\n<\/p>\n
1. \u57fa\u672c\u64cd\u4f5c<\/h4>\n<\/p>\n
Pandas\u662fPython\u4e2d\u7528\u4e8e\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u7684\u5f3a\u5927\u5e93\u3002\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u636e\u7ed3\u6784\u548c\u5206\u6790\u5de5\u5177\u3002\u5728Pandas\u4e2d\uff0cDataFrame\u662f\u6700\u5e38\u7528\u7684\u6570\u636e\u7ed3\u6784\uff0c\u5b83\u7c7b\u4f3c\u4e8e\u7535\u5b50\u8868\u683c\u6216SQL\u8868\u683c\u3002\u53ef\u4ee5\u901a\u8fc7\u5217\u540d\u6765\u8bbf\u95eeDataFrame\u4e2d\u7684\u7279\u5b9a\u5217\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u521b\u5efaDataFrame<\/strong><\/h2>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [25, 30, 35],<\/p>\n
    'City': ['New York', 'Los Angeles', 'Chicago']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
\u622a\u53d6\u5217<\/strong><\/h2>\n
age_column = df['Age']<\/p>\n
print(age_column)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u622a\u53d6\u591a\u5217<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u5c06\u591a\u4e2a\u5217\u540d\u653e\u5165\u5217\u8868\u4e2d\u6765\u622a\u53d6\u591a\u5217\u3002<\/p>\n<\/p>\n
# \u622a\u53d6\u591a\u5217<\/p>\n
subset = df[['Name', 'City']]<\/p>\n
print(subset)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u4f7f\u7528iloc\u548cloc\u65b9\u6cd5<\/h4>\n<\/p>\n
Pandas\u8fd8\u63d0\u4f9b\u4e86iloc<\/code>\u548cloc<\/code>\u65b9\u6cd5\uff0c\u7528\u4e8e\u901a\u8fc7\u7d22\u5f15\u6216\u6807\u7b7e\u6765\u9009\u62e9\u6570\u636e\u3002<\/p>\n<\/p>\n
    \n
  • iloc<\/code>\u57fa\u4e8e\u6574\u6570\u4f4d\u7f6e\u8fdb\u884c\u9009\u62e9\u3002<\/li>\n
  • loc<\/code>\u57fa\u4e8e\u6807\u7b7e\u8fdb\u884c\u9009\u62e9\u3002<\/li>\n<\/ul>\n
    # \u4f7f\u7528iloc\u622a\u53d6\u5217<\/p>\n
    age_column_iloc = df.iloc[:, 1]<\/p>\n
    print(age_column_iloc)<\/p>\n
    \u4f7f\u7528loc\u622a\u53d6\u5217<\/strong><\/h2>\n
    age_column_loc = df.loc[:, 'Age']<\/p>\n
    print(age_column_loc)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e8c\u3001\u4f7f\u7528NumPy\u5e93\u622a\u53d6\u5217<\/h3>\n<\/p>\n
    NumPy\u662fPython\u4e2d\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u57fa\u7840\u5e93\u3002\u5b83\u63d0\u4f9b\u4e86\u5bf9\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\u548c\u5404\u79cd\u6d3e\u751f\u5bf9\u8c61\uff08\u5982\u77e9\u9635\uff09\u7684\u652f\u6301\u3002\u53ef\u4ee5\u4f7f\u7528NumPy\u6570\u7ec4\u7684\u5207\u7247\u529f\u80fd\u6765\u622a\u53d6\u5217\u3002<\/p>\n<\/p>\n
    1. \u57fa\u672c\u64cd\u4f5c<\/h4>\n<\/p>\n
    import numpy as np<\/p>\n
    \u521b\u5efaNumPy\u6570\u7ec4<\/strong><\/h2>\n
    data = np.array([<\/p>\n
        ['Alice', 25, 'New York'],<\/p>\n
        ['Bob', 30, 'Los Angeles'],<\/p>\n
        ['Charlie', 35, 'Chicago']<\/p>\n
    ])<\/p>\n
    \u622a\u53d6\u5217<\/strong><\/h2>\n
    age_column = data[:, 1]<\/p>\n
    print(age_column)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2. \u591a\u5217\u622a\u53d6<\/h4>\n<\/p>\n
    \u53ef\u4ee5\u901a\u8fc7\u63d0\u4f9b\u591a\u4e2a\u7d22\u5f15\u6765\u622a\u53d6\u591a\u5217\u3002<\/p>\n<\/p>\n
    # \u622a\u53d6\u591a\u5217<\/p>\n
    subset = data[:, [0, 2]]<\/p>\n
    print(subset)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e09\u3001\u5217\u8868\u89e3\u6790\u622a\u53d6\u5217<\/h3>\n<\/p>\n
    \u5217\u8868\u89e3\u6790\u662fPython\u4e2d\u975e\u5e38\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u7528\u4e8e\u521b\u5efa\u65b0\u7684\u5217\u8868\u3002\u53ef\u4ee5\u4f7f\u7528\u5217\u8868\u89e3\u6790\u4ece\u5d4c\u5957\u5217\u8868\u4e2d\u622a\u53d6\u7279\u5b9a\u5217\u3002<\/p>\n<\/p>\n
    1. \u57fa\u672c\u64cd\u4f5c<\/h4>\n<\/p>\n
    # \u521b\u5efa\u5d4c\u5957\u5217\u8868<\/p>\n
    data = [<\/p>\n
        ['Alice', 25, 'New York'],<\/p>\n
        ['Bob', 30, 'Los Angeles'],<\/p>\n
        ['Charlie', 35, 'Chicago']<\/p>\n
    ]<\/p>\n
    \u622a\u53d6\u5217<\/strong><\/h2>\n
    age_column = [row[1] for row in data]<\/p>\n
    print(age_column)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2. \u591a\u5217\u622a\u53d6<\/h4>\n<\/p>\n
    \u53ef\u4ee5\u901a\u8fc7\u8c03\u6574\u5217\u8868\u89e3\u6790\u6765\u622a\u53d6\u591a\u5217\u3002<\/p>\n<\/p>\n
    # \u622a\u53d6\u591a\u5217<\/p>\n
    subset = [[row[0], row[2]] for row in data]<\/p>\n
    print(subset)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u56db\u3001\u4f7f\u7528CSV\u6a21\u5757\u622a\u53d6\u5217<\/h3>\n<\/p>\n
    Python\u7684CSV\u6a21\u5757\u63d0\u4f9b\u4e86\u5bf9CSV\u6587\u4ef6\u7684\u652f\u6301\u3002\u53ef\u4ee5\u4f7f\u7528CSV\u6a21\u5757\u6765\u8bfb\u53d6CSV\u6587\u4ef6\u5e76\u622a\u53d6\u7279\u5b9a\u5217\u3002<\/p>\n<\/p>\n
    1. \u57fa\u672c\u64cd\u4f5c<\/h4>\n<\/p>\n
    import csv<\/p>\n
    \u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n
    with open('file.csv', mode='r') as file:<\/p>\n
        reader = csv.reader(file)<\/p>\n
        header = next(reader)  # \u8bfb\u53d6\u6807\u9898\u884c<\/p>\n
        age_column = [row[1] for row in reader]  # \u5047\u8bbe\u7b2c\u4e8c\u5217\u662f\u5e74\u9f84<\/p>\n
    print(age_column)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2. \u4f7f\u7528DictReader<\/h4>\n<\/p>\n
    CSV\u6a21\u5757\u8fd8\u63d0\u4f9b\u4e86DictReader<\/code>\u7c7b\uff0c\u53ef\u4ee5\u5c06CSV\u6587\u4ef6\u4e2d\u7684\u6bcf\u4e00\u884c\u8bfb\u53d6\u4e3a\u5b57\u5178\u3002<\/p>\n<\/p>\n
    # \u4f7f\u7528DictReader\u8bfb\u53d6CSV\u6587\u4ef6<\/p>\n
    with open('file.csv', mode='r') as file:<\/p>\n
        reader = csv.DictReader(file)<\/p>\n
        age_column = [row['Age'] for row in reader]  # \u5047\u8bbe\u5217\u540d\u4e3a'Age'<\/p>\n
    print(age_column)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
    \u5728Python\u4e2d\uff0c\u6709\u591a\u79cd\u65b9\u6cd5\u53ef\u4ee5\u622a\u53d6\u5217\u3002\u9009\u62e9\u54ea\u79cd\u65b9\u6cd5\u53d6\u51b3\u4e8e\u6570\u636e\u7684\u683c\u5f0f\u548c\u5177\u4f53\u9700\u6c42\u3002Pandas\u662f\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e\u7684\u6700\u4f73\u9009\u62e9\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u529f\u80fd\u3002NumPy\u9002\u7528\u4e8e\u6570\u503c\u8ba1\u7b97\u548c\u591a\u7ef4\u6570\u7ec4\u64cd\u4f5c\uff0c\u800c\u5217\u8868\u89e3\u6790\u63d0\u4f9b\u4e86\u4e00\u79cd\u7b80\u5355\u7684\u65b9\u6cd5\u6765\u64cd\u4f5c\u5c0f\u578b\u6570\u636e\u96c6\u3002CSV\u6a21\u5757\u9002\u7528\u4e8e\u5904\u7406CSV\u6587\u4ef6\uff0c\u7279\u522b\u662f\u5728\u9700\u8981\u9010\u884c\u8bfb\u53d6\u548c\u5904\u7406\u6570\u636e\u65f6\u3002\u5728\u9009\u62e9\u65b9\u6cd5\u65f6\uff0c\u5e94\u8003\u8651\u6570\u636e\u7684\u89c4\u6a21\u3001\u683c\u5f0f\u548c\u4efb\u52a1\u7684\u590d\u6742\u6027\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u5728Python\u4e2d\u622a\u53d6DataFrame\u7684\u7279\u5b9a\u5217\uff1f<\/strong>
    \u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u6765\u5904\u7406\u6570\u636e\u3002\u8981\u622a\u53d6DataFrame\u7684\u7279\u5b9a\u5217\uff0c\u53ef\u4ee5\u4f7f\u7528\u65b9\u62ec\u53f7\u5e76\u4f20\u5165\u5217\u540d\u5217\u8868\u3002\u4f8b\u5982\uff0c\u5982\u679c\u4f60\u6709\u4e00\u4e2aDataFrame df\uff0c\u5e76\u5e0c\u671b\u622a\u53d6\u5217\u201c\u5217A\u201d\u548c\u201c\u5217B\u201d\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1adf[['\u5217A', '\u5217B']]<\/code>\u3002\u8fd9\u6837\u5c06\u8fd4\u56de\u4e00\u4e2a\u65b0\u7684DataFrame\uff0c\u53ea\u5305\u542b\u6307\u5b9a\u7684\u5217\u3002<\/p>\n
    \u622a\u53d6\u5217\u65f6\u5982\u4f55\u5904\u7406\u7f3a\u5931\u503c\uff1f<\/strong>
    \u5728\u622a\u53d6\u5217\u65f6\uff0c\u5982\u679c\u4f60\u7684\u6570\u636e\u4e2d\u5b58\u5728\u7f3a\u5931\u503c\uff0c\u53ef\u4ee5\u8003\u8651\u4f7f\u7528Pandas\u7684dropna()<\/code>\u65b9\u6cd5\u3002\u8fd9\u5c06\u5e2e\u52a9\u4f60\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c\uff0c\u6216\u8005\u4f7f\u7528fillna()<\/code>\u65b9\u6cd5\u586b\u5145\u7f3a\u5931\u503c\u3002\u8fd9\u6837\u5728\u5206\u6790\u6570\u636e\u65f6\uff0c\u53ef\u4ee5\u786e\u4fdd\u7ed3\u679c\u7684\u51c6\u786e\u6027\u3002<\/p>\n
    \u662f\u5426\u53ef\u4ee5\u901a\u8fc7\u6761\u4ef6\u7b5b\u9009\u622a\u53d6\u5217\uff1f<\/strong>
    \u53ef\u4ee5\u901a\u8fc7\u6761\u4ef6\u7b5b\u9009\u6765\u622a\u53d6\u5217\u3002\u4f8b\u5982\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528\u5e03\u5c14\u7d22\u5f15\u6765\u9009\u62e9\u6ee1\u8db3\u7279\u5b9a\u6761\u4ef6\u7684\u884c\uff0c\u7136\u540e\u518d\u622a\u53d6\u6240\u9700\u7684\u5217\u3002\u5047\u8bbe\u4f60\u60f3\u622a\u53d6\u201c\u5217A\u201d\u548c\u201c\u5217B\u201d\uff0c\u4f46\u53ea\u9009\u62e9\u201c\u5217A\u201d\u5927\u4e8e\u67d0\u4e2a\u503c\u7684\u884c\uff0c\u53ef\u4ee5\u4f7f\u7528\u5982\u4e0b\u4ee3\u7801\uff1adf[df['\u5217A'] > \u67d0\u4e2a\u503c][['\u5217A', '\u5217B']]<\/code>\u3002\u8fd9\u6837\u53ef\u4ee5\u65b9\u4fbf\u5730\u83b7\u53d6\u7b26\u5408\u6761\u4ef6\u7684\u6570\u636e\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\u622a\u53d6\u5217\u7684\u5e38\u89c1\u65b9\u6cd5\u6709\uff1a\u4f7f\u7528Pandas\u5e93\u3001\u4f7f\u7528NumPy\u5e93\u3001\u901a\u8fc7\u5217\u8868\u89e3\u6790\u3002Pandas\u5e93\u662f\u5904\u7406\u6570 […]","protected":false},"author":3,"featured_media":946447,"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\/946441"}],"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=946441"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/946441\/revisions"}],"predecessor-version":[{"id":946448,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/946441\/revisions\/946448"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/946447"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=946441"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=946441"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=946441"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}