{"id":84339,"date":"2026-07-26T11:42:31","date_gmt":"2026-07-26T03:42:31","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/84339.html"},"modified":"2026-07-26T11:42:31","modified_gmt":"2026-07-26T03:42:31","slug":"pandas-dataframe-%e5%b8%b8%e7%94%a8%e6%96%b9%e6%b3%95%e5%85%a8%e6%b1%87%e6%80%bb%ef%bc%88%e5%85%a5%e9%97%a8%e5%ae%9e%e6%93%8d%e5%8d%9a%e6%96%87%ef%bc%89","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/84339.html","title":{"rendered":"Pandas DataFrame \u5e38\u7528\u65b9\u6cd5\u5168\u6c47\u603b\uff08\u5165\u95e8\u5b9e\u64cd\u535a\u6587\uff09"},"content":{"rendered":"

\u524d\u8a00<\/h2>\n

\u4f7f\u7528 pandas \u505a\u6570\u636e\u5206\u6790，\u9664\u4e86 DataFrame \u57fa\u7840\u521b\u5efa\u3001\u7d22\u5f15\u53d6\u503c，\u7edd\u5927\u591a\u6570\u5de5\u4f5c\u90fd\u4f9d\u8d56\u5404\u7c7b\u5185\u7f6e\u65b9\u6cd5：\u67e5\u770b\u5934\u5c3e\u3001\u5217\u7b5b\u9009\u3001\u5e03\u5c14\u8fc7\u6ee4\u3001\u7edf\u8ba1\u8ba1\u7b97\u3001\u53bb\u91cd\u3001\u6392\u5e8f\u3001\u968f\u673a\u62bd\u6837\u7b49\u3002\u672c\u7bc7\u57fa\u4e8e\u5b8c\u6574\u53ef\u8fd0\u884c\u4ee3\u7801，\u5206\u95e8\u522b\u7c7b\u8bb2\u89e3\u9ad8\u9891\u65b9\u6cd5，\u9002\u914d\u6570\u636e\u5206\u6790\u65e5\u5e38\u4f7f\u7528\u3002<\/p>\n

\u63d0\u524d\u56fa\u5b9a\u6f14\u793a\u6570\u636e\u96c6，\u5168\u6587\u6240\u6709\u6848\u4f8b\u57fa\u4e8e\u8fd9\u4efd\u8868\u683c\u8fd0\u884c：<\/p>\n

import pandas as pd<\/p>\n

df = pd.DataFrame({
\n "name":["tom","tom","jack","alice","bob","allen"],
\n "age":[15,15,15,20,26,30],
\n "score":[60.5,60.5,80,30.6,70,83.5]
\n},
\nindex=['a','b','c','d','e','f'], # \u81ea\u5b9a\u4e49\u884c\u6807\u7b7e
\ncolumns=["name","score","age"]) # \u81ea\u5b9a\u4e49\u5217\u987a\u5e8f<\/p>\n

\u4e00\u3001\u67e5\u770b\u6570\u636e\u5934\u5c3e：head () \/tail ()<\/h3>\n

\u53ea\u770b\u5c40\u90e8\u884c，\u4e0d\u7528\u6253\u5370\u5168\u8868，\u9002\u5408\u5feb\u901f\u9884\u89c8\u6570\u636e\u3002<\/p>\n

  • df.head(n)：\u67e5\u770b\u524d n \u884c，\u4e0d\u4f20\u53c2\u9ed8\u8ba4\u5c55\u793a\u524d 5 \u884c<\/li>\n
  • df.tail(n)：\u67e5\u770b\u6700\u540e n \u884c，\u4e0d\u4f20\u53c2\u9ed8\u8ba4\u5c55\u793a\u6700\u540e 5 \u884c<\/li>\n

    # \u67e5\u770b\u524d3\u884c
    \nprint("head\u524d3\u884c：\\\\n",df.head(3))
    \n# \u67e5\u770b\u540e3\u884c
    \nprint("tail\u540e3\u884c：\\\\n",df.tail(3))<\/p>\n

    # \u9ed8\u8ba45\u884c
    \nprint("\u9ed8\u8ba4\u524d5\u884c：",df.head())
    \nprint("\u9ed8\u8ba4\u540e5\u884c：",df.tail())<\/p>\n

    \u5c0f\u6280\u5de7：\u53ef\u4ee5\u94fe\u5f0f\u642d\u914d\u5217\u7b5b\u9009，\u5148\u9009\u5217\u518d\u53d6\u5934\u5c3e，\u7cbe\u7b80\u6570\u636e： df[['name','score']].head(3) \u53ea\u770b\u59d3\u540d\u3001\u5206\u6570\u7684\u524d\u4e09\u884c<\/p>\n

    \u4e8c\u3001\u5355\u5217 \/ \u591a\u5217\u83b7\u53d6，\u642d\u914d\u5934\u5c3e\u4f7f\u7528<\/h3>\n

    1. \u5355\u5217 3 \u79cd\u5199\u6cd5\u533a\u522b<\/h4>\n

    \u8868\u683c<\/p>\n\n\u5199\u6cd5\u8fd4\u56de\u7c7b\u578b\u7279\u70b9<\/tr>\n\n\n\n\n
    df['name']<\/td>\nSeries \u4e00\u7ef4<\/td>\n\u5e38\u7528，\u9002\u5408\u5355\u72ec\u8ba1\u7b97<\/td>\n<\/tr>\n
    df.name<\/td>\nSeries \u4e00\u7ef4<\/td>\n\u5217\u540d\u65e0\u7a7a\u683c \/ \u7279\u6b8a\u5b57\u7b26\u624d\u80fd\u7528<\/td>\n<\/tr>\n
    df[['name']]<\/td>\nDataFrame \u4e8c\u7ef4<\/td>\n\u4fdd\u7559\u8868\u683c\u683c\u5f0f，\u63a8\u8350\u4f5c\u56fe\u3001\u591a\u5217\u7edf\u4e00\u5199\u6cd5<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    2. \u591a\u5217\u83b7\u53d6<\/h4>\n

    \u591a\u5217\u5fc5\u987b\u7528\u5217\u8868\u5305\u88f9\u5217\u540d：df[['\u52171','\u52172']]<\/p>\n

    # \u53d6name\u3001score\u4e24\u5217
    \nprint(df[['name','score']])
    \n# \u4e24\u5217+\u524d3\u884c
    \nprint(df[['name','score']].head(3))
    \n# \u5355\u5217age+\u6700\u540e3\u884c
    \nprint(df[['age']].tail(3))<\/p>\n

    \u4e09\u3001\u5e03\u5c14\u7d22\u5f15：\u6309\u6761\u4ef6\u7b5b\u9009\u884c（\u6700\u6838\u5fc3\u7b5b\u9009）<\/h3>\n

    \u8bed\u6cd5：df[\u6761\u4ef6\u8868\u8fbe\u5f0f]，\u652f\u6301\u5355\u6761\u4ef6\u3001\u591a\u6761\u4ef6\u7ec4\u5408<\/p>\n

    \u89c4\u5219<\/h4>\n
  • \u591a\u6761\u4ef6\u5fc5\u987b\u7528\u62ec\u53f7\u5305\u88f9\u6bcf\u4e2a\u6761\u4ef6<\/li>\n
  • \u4e14：&；\u6216：|；\u4e0d\u80fd\u7528 and\/or<\/li>\n
  • \u4e24\u79cd\u5199\u6cd5\u7b49\u4ef7：df.score \u548c df['score']<\/li>\n

    # \u5355\u6761\u4ef6：\u5206\u6570\u5927\u4e8e70
    \nprint(df[df.score>70])
    \nprint(df[df['score']>70])<\/p>\n

    # \u591a\u6761\u4ef6：\u5206\u6570\u5927\u4e8e70 \u5e76\u4e14 \u5e74\u9f84\u5c0f\u4e8e30
    \nres = df[(df['score']>70) & (df['age'] < 30)]
    \nprint(res)<\/p>\n

    \u56db\u3001\u5339\u914d\u5224\u65ad\u3001\u7a7a\u503c\u5224\u65ad：isin () \/isna ()<\/h3>\n

    1. isin () \u5224\u65ad\u5355\u5143\u683c\u662f\u5426\u5305\u542b\u6307\u5b9a\u5185\u5bb9<\/h4>\n

    \u7528\u6765\u7b5b\u9009\u5b57\u6bb5\u5728\u67d0\u4e2a\u540d\u5355\u91cc，\u652f\u6301\u591a\u5b57\u6bb5\u5339\u914d<\/p>\n

    # \u6240\u6709\u5355\u5143\u683c\u662f\u5426\u7b49\u4e8ejack
    \nprint(df.isin(['jack']))
    \n# \u5339\u914d jack \u6216\u8005\u6570\u5b5720
    \nprint(df.isin(['jack',20]))<\/p>\n

    2. isna () \u5224\u65ad\u7a7a\u503c<\/h4>\n

    \u6807\u8bb0\u8868\u683c\u91cc\u6240\u6709\u7f3a\u5931\u503c NaN，\u4e3a\u7a7a\u8fd4\u56de True，\u975e\u7a7a False<\/p>\n

    print(df.isna())<\/p>\n

    \u914d\u5957\u8865\u5145：notna() \u5224\u65ad\u975e\u7a7a\u3002<\/p>\n

    \u4e94\u3001\u6570\u503c\u7edf\u8ba1\u51fd\u6570：\u5355\u5217\u805a\u5408\u8ba1\u7b97<\/h3>\n

    \u9488\u5bf9\u6570\u503c\u5217（score\u3001age）\u505a\u7edf\u8ba1，\u5168\u90e8\u662f\u5217\u7eb5\u5411\u8ba1\u7b97\u3002<\/p>\n

    \u8868\u683c<\/p>\n\n\u65b9\u6cd5\u4f5c\u7528\u793a\u4f8b<\/tr>\n\n\n\n\n\n\n\n\n\n
    sum()<\/td>\n\u6c42\u548c<\/td>\n\u603b\u5206<\/td>\n<\/tr>\n
    max()<\/td>\n\u6700\u5927\u503c<\/td>\n\u6700\u9ad8\u5206<\/td>\n<\/tr>\n
    min()<\/td>\n\u6700\u5c0f\u503c<\/td>\n\u6700\u4f4e\u5206<\/td>\n<\/tr>\n
    mean()<\/td>\n\u5e73\u5747\u503c<\/td>\n\u5e73\u5747\u5206<\/td>\n<\/tr>\n
    median()<\/td>\n\u4e2d\u4f4d\u6570<\/td>\n\u4e2d\u95f4\u5206，\u4e0d\u53d7\u6781\u7aef\u503c\u5f71\u54cd<\/td>\n<\/tr>\n
    std()<\/td>\n\u6807\u51c6\u5dee<\/td>\n\u6570\u636e\u6ce2\u52a8\u5927\u5c0f<\/td>\n<\/tr>\n
    var()<\/td>\n\u65b9\u5dee<\/td>\n\u79bb\u6563\u7a0b\u5ea6<\/td>\n<\/tr>\n
    quantile(0.25)<\/td>\n\u56db\u5206\u4f4d\u6570<\/td>\n25% \u5206\u4f4d\u6570<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    print("\u5206\u6570\u6c42\u548c：",df['score'].sum())
    \nprint("\u6700\u9ad8\u5206：",df['score'].max())
    \nprint("\u6700\u4f4e\u5206：",df['score'].min())
    \nprint("\u5e73\u5747\u5206：",df.score.mean())
    \nprint("\u4e2d\u4f4d\u6570：",df.score.median())
    \nprint("\u6807\u51c6\u5dee：",df.score.std())
    \nprint("\u65b9\u5dee：",df.score.var())
    \nprint("25%\u5206\u4f4d\u6570：",df.score.quantile(0.25))<\/p>\n

    \u4e00\u952e\u5168\u91cf\u7edf\u8ba1 describe ()<\/h4>\n

    \u65e0\u9700\u9010\u4e2a\u8c03\u7528，\u4e00\u6b21\u6027\u8f93\u51fa：\u8ba1\u6570\u3001\u5747\u503c\u3001\u6700\u503c\u3001\u56db\u5206\u4f4d\u6570，\u6570\u636e\u5206\u6790\u5fc5\u7528：<\/p>\n

    print(df.describe())<\/p>\n

    \u516d\u3001\u8ba1\u6570\u7edf\u8ba1：count () \/value_counts ()<\/h3>\n
  • df.count()：\u7edf\u8ba1\u6bcf\u4e00\u5217\u975e\u7a7a\u6709\u6548\u5355\u5143\u683c\u6570\u91cf<\/li>\n
  • df['\u5217\u540d'].value_counts()：\u7edf\u8ba1\u4e00\u5217\u4e2d\u6bcf\u4e2a\u503c\u51fa\u73b0\u7684\u9891\u6b21（\u7edf\u8ba1\u91cd\u590d\u6b21\u6570\u795e\u5668）<\/li>\n

    # \u5404\u5217\u6709\u6548\u6570\u636e\u884c\u6570
    \nprint("\u6bcf\u4e00\u5217\u975e\u7f3a\u5931\u503c\u4e2a\u6570：\\\\n",df.count())
    \n# \u5168\u8868\u884c\u91cd\u590d\u9891\u6b21
    \nprint("\u5168\u8868\u91cd\u590d\u9891\u6b21：\\\\n",df.value_counts())
    \n# \u5e38\u7528：\u7edf\u8ba1\u6bcf\u4e2a\u5e74\u9f84\u51fa\u73b0\u591a\u5c11\u6b21
    \nprint(df['age'].value_counts())<\/p>\n

    \u4e03\u3001\u91cd\u590d\u503c\u5904\u7406：duplicated () \/drop_duplicates ()<\/h3>\n
  • duplicated()：\u6807\u8bb0\u91cd\u590d\u884c，\u91cd\u590d\u8fd4\u56de True，\u9ed8\u8ba4\u6574\u884c\u5b8c\u5168\u4e00\u81f4\u624d\u7b97\u91cd\u590d；\u53ef\u6307\u5b9a\u5217\u5224\u65ad\u91cd\u590d<\/li>\n
  • drop_duplicates()：\u76f4\u63a5\u5220\u9664\u91cd\u590d\u884c，\u8fd4\u56de\u53bb\u91cd\u540e\u7684\u65b0\u8868\u683c<\/li>\n

    # \u5224\u65ad\u6574\u884c\u662f\u5426\u91cd\u590d
    \nprint("\u662f\u5426\u6574\u884c\u91cd\u590d：\\\\n",df.duplicated())
    \n# \u53ea\u6839\u636eage\u5217\u5224\u65ad\u91cd\u590d，\u5e74\u9f84\u76f8\u540c\u5373\u5224\u5b9a\u91cd\u590d
    \nprint("age\u5217\u91cd\u590d\u5224\u65ad：\\\\n",df.duplicated(subset='age'))
    \n# \u5220\u9664\u6240\u6709\u91cd\u590d\u884c
    \nprint("\u53bb\u91cd\u540e\u6570\u636e：\\\\n",df.drop_duplicates())<\/p>\n

    \u516b\u3001\u968f\u673a\u62bd\u6837 sample ()<\/h3>\n

    \u4ece\u8868\u683c\u968f\u673a\u62bd\u53d6\u82e5\u5e72\u884c，\u505a\u6570\u636e\u968f\u673a\u91c7\u6837，\u652f\u6301\u62bd 1 \u884c\u3001\u591a\u884c\u3002<\/p>\n

    # \u9ed8\u8ba4\u968f\u673a\u62bd1\u884c
    \nprint("\u968f\u673a\u62bd1\u884c：\\\\n",df.sample())
    \n# \u968f\u673a\u62bd3\u884c
    \nprint("\u968f\u673a\u62bd3\u884c：\\\\n",df.sample(3))<\/p>\n

    \u4e5d\u3001\u6570\u636e\u6392\u5e8f：sort_index \/sort_values\/nlargest<\/h3>\n

    1. sort_index：\u6309\u7167\u884c\u7d22\u5f15\u6807\u7b7e\u6392\u5e8f<\/h4>\n

    ascending=False \u5012\u5e8f，True \u6b63\u5e8f<\/p>\n

    # \u884c\u7d22\u5f15a~f\u5012\u5e8f\u6392\u5217
    \nprint("\u7d22\u5f15\u964d\u5e8f：\\\\n",df.sort_index(ascending=False))<\/p>\n

    2. sort_values：\u6309\u5217\u7684\u503c\u6392\u5e8f（\u6700\u5e38\u7528）<\/h4>\n

    \u652f\u6301\u591a\u5217\u8054\u5408\u6392\u5e8f，\u53ef\u4ee5\u7ed9\u4e0d\u540c\u5217\u8bbe\u7f6e\u4e0d\u540c\u5347\u964d\u5e8f\u89c4\u5219<\/p>\n

    # \u5148\u6309score\u5347\u5e8f，\u5206\u6570\u76f8\u540c\u5219age\u964d\u5e8f
    \ndf_sorted = df.sort_values(by=['score','age'],ascending=[True,False])
    \nprint("\u591a\u5217\u6df7\u5408\u6392\u5e8f：\\\\n",df_sorted)<\/p>\n

    3. nlargest \/nsmallest：\u5feb\u901f\u53d6\u6700\u503c\u524d N \u884c<\/h4>\n

    \u4e0d\u7528\u6392\u5e8f\u518d head，\u4e00\u6b65\u62ff\u5230\u5206\u6570\u6700\u9ad8 2 \u6761<\/p>\n

    # \u53d6score\u3001age\u7efc\u5408\u6700\u5927\u76842\u884c
    \nprint(df.nlargest(2,columns=['score','age']))
    \n# \u914d\u5957：nsmallest\u53d6\u6700\u5c0fN\u884c
    \ndf.nsmallest(2,columns="score")<\/p>\n

    \u5341\u3001\u5b8c\u6574\u914d\u5957\u7ec3\u4e60\u4ee3\u7801<\/h3>\n

    import pandas as pd<\/p>\n

    df = pd.DataFrame({
    \n "name":["tom","tom","jack","alice","bob","allen"],
    \n "age":[15,15,15,20,26,30],
    \n "score":[60.5,60.5,80,30.6,70,83.5]
    \n},
    \nindex=['a','b','c','d','e','f'],
    \ncolumns=["name","score","age"])<\/p>\n

    # \u5934\u5c3e\u67e5\u770b
    \nprint("head\u524d3\u884c：\\\\n",df.head(3))
    \nprint("tail\u540e3\u884c：\\\\n",df.tail(3))<\/p>\n

    # \u5217\u9009\u53d6
    \nprint("\\\\n\u5355\u5217\u4e09\u79cd\u5199\u6cd5")
    \nprint(df['name'])
    \nprint(df.name)
    \nprint(df[['name']])
    \nprint("\\\\n\u591a\u5217+\u5934\u5c3e",df[['name','score']].head(3))<\/p>\n

    # \u5e03\u5c14\u7b5b\u9009
    \nprint("\\\\n\u5206\u6570\u5927\u4e8e70",df[df.score>70])
    \nprint("\\\\n\u5206\u6570>70\u4e14\u5e74\u9f84<30",df[(df.score>70)&(df.age<30)])<\/p>\n

    # \u5339\u914d\u3001\u7a7a\u503c
    \nprint("\\\\nisin\u5339\u914djack",df.isin(["jack"]))
    \nprint("\\\\n\u7a7a\u503c\u5224\u65ad",df.isna())<\/p>\n

    # \u7edf\u8ba1\u6307\u6807
    \nprint("\\\\n\u603b\u5206",df['score'].sum())
    \nprint("\u5e73\u5747\u5206",df.score.mean())
    \nprint(df.describe())<\/p>\n

    # \u8ba1\u6570\u4e0e\u53bb\u91cd
    \nprint("\\\\n\u6709\u6548\u884c\u6570",df.count())
    \nprint("\\\\n\u91cd\u590d\u5224\u65ad",df.duplicated())
    \nprint("\\\\n\u53bb\u91cd",df.drop_duplicates())<\/p>\n

    # \u62bd\u6837
    \nprint("\\\\n\u968f\u673a\u62bd\u6837",df.sample(2))<\/p>\n

    # \u6392\u5e8f
    \nprint("\\\\n\u7d22\u5f15\u5012\u5e8f",df.sort_index(ascending=False))
    \nprint("\\\\n\u591a\u5217\u6392\u5e8f",df.sort_values(by=["score"],ascending=True))
    \nprint("\\\\n\u5206\u6570\u6700\u9ad82\u884c",df.nlargest(2,"score"))<\/p>\n

    \u5341\u4e00\u3001\u65b0\u624b\u4f7f\u7528\u603b\u7ed3<\/h3>\n
  • \u9884\u89c8\u6570\u636e：head\/tail；\u9009\u5217\u7528[]，\u591a\u5217\u5fc5\u987b\u5957\u5217\u8868；<\/li>\n
  • \u7cbe\u51c6\u7b5b\u9009\u4f18\u5148\u7528\u5e03\u5c14\u7d22\u5f15，\u591a\u6761\u4ef6\u8bb0\u4f4f\u62ec\u53f7 +&\/|；<\/li>\n
  • \u505a\u7edf\u8ba1：\u5355\u5217\u7528 sum\/mean \u7b49，\u5168\u8868\u4e00\u952e\u7528describe；<\/li>\n
  • \u91cd\u590d\u6e05\u7406：duplicated\u67e5\u91cd\u590d，drop_duplicates\u5220\u91cd\u590d；<\/li>\n
  • \u6392\u5e8f\u5206\u4e24\u7c7b：\u6309\u7d22\u5f15 sort_index，\u6309\u5b57\u6bb5 sort_values；\u53d6\u6781\u503c\u7528 nlargest；<\/li>\n
  • \u968f\u673a\u62ff\u6570\u636e\u76f4\u63a5 sample，\u9002\u5408\u62bd\u6837\u6d4b\u8bd5\u3002<\/li>\n","protected":false},"excerpt":{"rendered":"

    \u524d\u8a00\u4f7f\u7528 pandas \u505a\u6570\u636e\u5206\u6790，\u9664\u4e86 DataFrame \u57fa\u7840\u521b\u5efa\u3001\u7d22\u5f15\u53d6\u503c，\u7edd\u5927\u591a\u6570\u5de5\u4f5c\u90fd\u4f9d\u8d56\u5404\u7c7b\u5185\u7f6e\u65b9\u6cd5：\u67e5\u770b\u5934\u5c3e\u3001\u5217\u7b5b\u9009\u3001\u5e03\u5c14\u8fc7\u6ee4\u3001\u7edf\u8ba1\u8ba1\u7b97\u3001\u53bb\u91cd\u3001\u6392\u5e8f\u3001\u968f\u673a\u62bd\u6837\u7b49\u3002\u672c\u7bc7\u57fa\u4e8e\u5b8c\u6574\u53ef\u8fd0\u884c\u4ee3\u7801，\u5206\u95e8\u522b\u7c7b\u8bb2\u89e3\u9ad8\u9891\u65b9\u6cd5，\u9002\u914d\u6570\u636e\u5206\u6790\u65e5\u5e38\u4f7f\u7528\u3002\u63d0\u524d\u56fa\u5b9a\u6f14\u793a\u6570\u636e\u96c6，\u5168\u6587\u6240\u6709\u6848\u4f8b\u57fa\u4e8e\u8fd9\u4efd\u8868\u683c\u8fd0\u884c：import pandas as pddf pd.DataFrame({\\”name\\”:<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[81,190],"topic":[],"class_list":["post-84339","post","type-post","status-publish","format-standard","hentry","category-server","tag-python","tag-190"],"yoast_head":"\nPandas DataFrame \u5e38\u7528\u65b9\u6cd5\u5168\u6c47\u603b\uff08\u5165\u95e8\u5b9e\u64cd\u535a\u6587\uff09 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/84339.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas DataFrame \u5e38\u7528\u65b9\u6cd5\u5168\u6c47\u603b\uff08\u5165\u95e8\u5b9e\u64cd\u535a\u6587\uff09 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"og:description\" content=\"\u524d\u8a00\u4f7f\u7528 pandas \u505a\u6570\u636e\u5206\u6790，\u9664\u4e86 DataFrame \u57fa\u7840\u521b\u5efa\u3001\u7d22\u5f15\u53d6\u503c，\u7edd\u5927\u591a\u6570\u5de5\u4f5c\u90fd\u4f9d\u8d56\u5404\u7c7b\u5185\u7f6e\u65b9\u6cd5：\u67e5\u770b\u5934\u5c3e\u3001\u5217\u7b5b\u9009\u3001\u5e03\u5c14\u8fc7\u6ee4\u3001\u7edf\u8ba1\u8ba1\u7b97\u3001\u53bb\u91cd\u3001\u6392\u5e8f\u3001\u968f\u673a\u62bd\u6837\u7b49\u3002\u672c\u7bc7\u57fa\u4e8e\u5b8c\u6574\u53ef\u8fd0\u884c\u4ee3\u7801，\u5206\u95e8\u522b\u7c7b\u8bb2\u89e3\u9ad8\u9891\u65b9\u6cd5，\u9002\u914d\u6570\u636e\u5206\u6790\u65e5\u5e38\u4f7f\u7528\u3002\u63d0\u524d\u56fa\u5b9a\u6f14\u793a\u6570\u636e\u96c6，\u5168\u6587\u6240\u6709\u6848\u4f8b\u57fa\u4e8e\u8fd9\u4efd\u8868\u683c\u8fd0\u884c：import pandas as pddf pd.DataFrame({"name":\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.wsisp.com\/helps\/84339.html\" \/>\n<meta property=\"og:site_name\" content=\"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"article:published_time\" content=\"2026-07-26T03:42:31+00:00\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u4f5c\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 \u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/84339.html\",\"url\":\"https:\/\/www.wsisp.com\/helps\/84339.html\",\"name\":\"Pandas DataFrame \u5e38\u7528\u65b9\u6cd5\u5168\u6c47\u603b\uff08\u5165\u95e8\u5b9e\u64cd\u535a\u6587\uff09 - 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