{"id":1142358,"date":"2025-01-08T22:39:13","date_gmt":"2025-01-08T14:39:13","guid":{"rendered":""},"modified":"2025-01-08T22:39:16","modified_gmt":"2025-01-08T14:39:16","slug":"%e5%9c%a8python%e4%b8%ad%e5%a6%82%e4%bd%95%e8%8e%b7%e6%8a%8a%e6%95%b0%e6%8d%ae%e6%a1%86%e7%9a%84%e4%b8%80%e8%a1%8c","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1142358.html","title":{"rendered":"\u5728python\u4e2d\u5982\u4f55\u83b7\u628a\u6570\u636e\u6846\u7684\u4e00\u884c"},"content":{"rendered":"

\"\u5728python\u4e2d\u5982\u4f55\u83b7\u628a\u6570\u636e\u6846\u7684\u4e00\u884c\"<\/p>\n

\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\u6765\u83b7\u53d6\u6570\u636e\u6846\u7684\u4e00\u884c\uff1a\u4f7f\u7528.loc\u7d22\u5f15\u3001\u4f7f\u7528.iloc\u7d22\u5f15\u3001\u4f7f\u7528at\u7d22\u5f15<\/strong>\u3002\u5176\u4e2d\uff0c.loc\u7d22\u5f15\u662f\u57fa\u4e8e\u6807\u7b7e\u8fdb\u884c\u5b9a\u4f4d\uff0c.iloc\u7d22\u5f15\u662f\u57fa\u4e8e\u6574\u6570\u4f4d\u7f6e\u8fdb\u884c\u5b9a\u4f4d\uff0c.at\u7d22\u5f15\u4e5f\u662f\u57fa\u4e8e\u6807\u7b7e\u8fdb\u884c\u5b9a\u4f4d\uff0c\u4f46\u66f4\u9002\u5408\u7528\u4e8e\u83b7\u53d6\u5355\u4e2a\u5143\u7d20\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u63cf\u8ff0\u5176\u4e2d\u4e00\u79cd\u65b9\u6cd5\uff1a\u4f7f\u7528.loc\u7d22\u5f15\u53ef\u4ee5\u65b9\u4fbf\u5730\u901a\u8fc7\u884c\u6807\u7b7e\u6765\u83b7\u53d6\u6570\u636e\u6846\u7684\u4e00\u884c<\/strong>\u3002\u4f8b\u5982\uff0c\u5982\u679c\u4f60\u7684\u6570\u636e\u6846\u540d\u4e3adf\uff0c\u4e14\u4f60\u60f3\u83b7\u53d6\u6807\u7b7e\u4e3a'index_name'\u7684\u4e00\u884c\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528df.loc['index_name']\u6765\u5b9e\u73b0\u3002\u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u76f4\u89c2\uff0c\u7279\u522b\u9002\u5408\u5904\u7406\u6709\u660e\u786e\u884c\u6807\u7b7e\u7684\u6570\u636e\u6846\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528loc\u7d22\u5f15<\/h2>\n<\/p>\n

.loc\u7d22\u5f15\u662fPandas\u5e93\u4e2d\u975e\u5e38\u5f3a\u5927\u4e14\u5e38\u7528\u7684\u4e00\u4e2a\u529f\u80fd\u3002\u901a\u8fc7.loc\u7d22\u5f15\uff0c\u6211\u4eec\u53ef\u4ee5\u65b9\u4fbf\u5730\u6839\u636e\u884c\u6807\u7b7e\u6765\u83b7\u53d6\u6570\u636e\u6846\u7684\u4e00\u884c\u6216\u591a\u884c\u6570\u636e\u3002\u8fd9\u79cd\u65b9\u6cd5\u7279\u522b\u9002\u5408\u5904\u7406\u6709\u660e\u786e\u6807\u7b7e\u7684\u6570\u636e\u6846\u3002<\/p>\n<\/p>\n

\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u6570\u636e\u6846df\uff0c\u5305\u542b\u4ee5\u4e0b\u6570\u636e\uff1a<\/p>\n<\/p>\n

import pandas as pd<\/p>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [25, 30, 35],<\/p>\n
    'City': ['New York', 'San Francisco', 'Los Angeles']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data, index=['A', 'B', 'C'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u6570\u636e\u6846\u4e2d\uff0c\u884c\u6807\u7b7e\u5206\u522b\u662f'A'\u3001'B'\u548c'C'\u3002\u5982\u679c\u6211\u4eec\u60f3\u83b7\u53d6\u6807\u7b7e\u4e3a'B'\u7684\u90a3\u4e00\u884c\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
row_b = df.loc['B']<\/p>\n
print(row_b)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
Name             Bob<\/p>\n
Age               30<\/p>\n
City    San Francisco<\/p>\n
Name: B, dtype: object<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.1\u3001\u83b7\u53d6\u591a\u884c\u6570\u636e<\/h3>\n<\/p>\n
.loc\u7d22\u5f15\u8fd8\u53ef\u4ee5\u7528\u4e8e\u83b7\u53d6\u591a\u884c\u6570\u636e\u3002\u5047\u8bbe\u6211\u4eec\u60f3\u83b7\u53d6\u6807\u7b7e\u4e3a'A'\u548c'C'\u7684\u4e24\u884c\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
rows_ac = df.loc[['A', 'C']]<\/p>\n
print(rows_ac)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
       Name  Age         City<\/p>\n
A     Alice   25     New York<\/p>\n
C  Charlie   35  Los Angeles<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.2\u3001\u57fa\u4e8e\u6761\u4ef6\u83b7\u53d6\u884c<\/h3>\n<\/p>\n
.loc\u7d22\u5f15\u4e5f\u53ef\u4ee5\u57fa\u4e8e\u6761\u4ef6\u6765\u83b7\u53d6\u884c\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u60f3\u83b7\u53d6\u5e74\u9f84\u5927\u4e8e30\u7684\u6240\u6709\u884c\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
rows_age_gt_30 = df.loc[df['Age'] > 30]<\/p>\n
print(rows_age_gt_30)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
      Name  Age         City<\/p>\n
C  Charlie   35  Los Angeles<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528iloc\u7d22\u5f15<\/h2>\n<\/p>\n
.iloc\u7d22\u5f15\u662f\u57fa\u4e8e\u6574\u6570\u4f4d\u7f6e\u8fdb\u884c\u5b9a\u4f4d\u7684\u7d22\u5f15\u65b9\u6cd5\u3002\u5b83\u9002\u7528\u4e8e\u90a3\u4e9b\u6ca1\u6709\u660e\u786e\u884c\u6807\u7b7e\u7684\u6570\u636e\u6846\uff0c\u6216\u8005\u4f60\u53ea\u77e5\u9053\u8981\u83b7\u53d6\u7684\u884c\u7684\u6574\u6570\u4f4d\u7f6e\u3002<\/p>\n<\/p>\n
\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u6570\u636e\u6846df\uff0c\u5305\u542b\u4ee5\u4e0b\u6570\u636e\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [25, 30, 35],<\/p>\n
    'City': ['New York', 'San Francisco', 'Los Angeles']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u6570\u636e\u6846\u4e2d\uff0c\u884c\u6807\u7b7e\u662f\u9ed8\u8ba4\u7684\u6574\u6570\u7d22\u5f150\u30011\u548c2\u3002\u5982\u679c\u6211\u4eec\u60f3\u83b7\u53d6\u7b2c\u4e8c\u884c\uff08\u7d22\u5f15\u4e3a1\uff09\u7684\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
row_1 = df.iloc[1]<\/p>\n
print(row_1)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
Name             Bob<\/p>\n
Age               30<\/p>\n
City    San Francisco<\/p>\n
Name: 1, dtype: object<\/p>\n
<\/code><\/pre>\n<\/p>\n
2.1\u3001\u83b7\u53d6\u591a\u884c\u6570\u636e<\/h3>\n<\/p>\n
.iloc\u7d22\u5f15\u4e5f\u53ef\u4ee5\u7528\u4e8e\u83b7\u53d6\u591a\u884c\u6570\u636e\u3002\u5047\u8bbe\u6211\u4eec\u60f3\u83b7\u53d6\u7b2c\u4e00\u884c\u548c\u7b2c\u4e09\u884c\uff08\u7d22\u5f15\u4e3a0\u548c2\uff09\u7684\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
rows_0_2 = df.iloc[[0, 2]]<\/p>\n
print(rows_0_2)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
      Name  Age         City<\/p>\n
0    Alice   25     New York<\/p>\n
2  Charlie   35  Los Angeles<\/p>\n
<\/code><\/pre>\n<\/p>\n
2.2\u3001\u57fa\u4e8e\u6761\u4ef6\u83b7\u53d6\u884c<\/h3>\n<\/p>\n
\u867d\u7136.iloc\u7d22\u5f15\u672c\u8eab\u4e0d\u652f\u6301\u57fa\u4e8e\u6761\u4ef6\u7684\u83b7\u53d6\uff0c\u4f46\u6211\u4eec\u53ef\u4ee5\u7ed3\u5408\u5176\u4ed6\u65b9\u6cd5\u6765\u5b9e\u73b0\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u60f3\u83b7\u53d6\u5e74\u9f84\u5927\u4e8e30\u7684\u6240\u6709\u884c\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
rows_age_gt_30 = df[df['Age'] > 30]<\/p>\n
print(rows_age_gt_30)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
      Name  Age         City<\/p>\n
2  Charlie   35  Los Angeles<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528at\u7d22\u5f15<\/h2>\n<\/p>\n
.at\u7d22\u5f15\u662f\u7528\u4e8e\u83b7\u53d6\u5355\u4e2a\u5143\u7d20\u7684\u9ad8\u6548\u65b9\u6cd5\u3002\u867d\u7136\u5b83\u4e0d\u9002\u5408\u76f4\u63a5\u83b7\u53d6\u6574\u884c\u6570\u636e\uff0c\u4f46\u5728\u67d0\u4e9b\u573a\u666f\u4e0b\uff0c\u5b83\u53ef\u4ee5\u975e\u5e38\u9ad8\u6548\u5730\u83b7\u53d6\u7279\u5b9a\u884c\u548c\u5217\u7684\u5355\u4e2a\u5143\u7d20\u3002<\/p>\n<\/p>\n
\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u6570\u636e\u6846df\uff0c\u5305\u542b\u4ee5\u4e0b\u6570\u636e\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
data = {<\/p>\n
    'Name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
    'Age': [25, 30, 35],<\/p>\n
    'City': ['New York', 'San Francisco', 'Los Angeles']<\/p>\n
}<\/p>\n
df = pd.DataFrame(data, index=['A', 'B', 'C'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u6570\u636e\u6846\u4e2d\uff0c\u5982\u679c\u6211\u4eec\u60f3\u83b7\u53d6\u6807\u7b7e\u4e3a'B'\u3001\u5217\u4e3a'Age'\u7684\u5143\u7d20\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
age_b = df.at['B', 'Age']<\/p>\n
print(age_b)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
30<\/p>\n
<\/code><\/pre>\n<\/p>\n
3.1\u3001\u6548\u7387\u4f18\u52bf<\/h3>\n<\/p>\n
.at\u7d22\u5f15\u5728\u83b7\u53d6\u5355\u4e2a\u5143\u7d20\u65f6\u6bd4.loc\u548c.iloc\u7d22\u5f15\u66f4\u9ad8\u6548\u3002\u7279\u522b\u662f\u5728\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u65f6\uff0c\u8fd9\u79cd\u6548\u7387\u4f18\u52bf\u66f4\u52a0\u660e\u663e\u3002<\/p>\n<\/p>\n
\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u5927\u89c4\u6a21\u6570\u636e\u6846df_large\uff0c\u5305\u542b\u4ee5\u4e0b\u6570\u636e\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
import numpy as np<\/p>\n
data_large = {<\/p>\n
    'Name': np.random.choice(['Alice', 'Bob', 'Charlie'], size=1000000),<\/p>\n
    'Age': np.random.randint(20, 40, size=1000000),<\/p>\n
    'City': np.random.choice(['New York', 'San Francisco', 'Los Angeles'], size=1000000)<\/p>\n
}<\/p>\n
df_large = pd.DataFrame(data_large)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u4e2a\u5927\u89c4\u6a21\u6570\u636e\u6846\u4e2d\uff0c\u5982\u679c\u6211\u4eec\u60f3\u83b7\u53d6\u7b2c\u4e00\u884c\uff08\u7d22\u5f15\u4e3a0\uff09\u3001\u5217\u4e3a'Age'\u7684\u5143\u7d20\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
age_0_large = df_large.at[0, 'Age']<\/p>\n
print(age_0_large)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3.2\u3001\u7ed3\u5408\u5176\u4ed6\u65b9\u6cd5\u4f7f\u7528<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u7ed3\u5408\u5176\u4ed6\u65b9\u6cd5\u4f7f\u7528.at\u7d22\u5f15\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u5148\u4f7f\u7528.loc\u7d22\u5f15\u83b7\u53d6\u67d0\u4e00\u884c\u6570\u636e\uff0c\u7136\u540e\u518d\u4f7f\u7528.at\u7d22\u5f15\u83b7\u53d6\u8be5\u884c\u4e2d\u7279\u5b9a\u5217\u7684\u5143\u7d20\u3002<\/p>\n<\/p>\n
row_b = df.loc['B']<\/p>\n
age_b_from_row_b = row_b.at['Age']<\/p>\n
print(age_b_from_row_b)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
30<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528ix\u7d22\u5f15\uff08\u5df2\u5f03\u7528\uff09<\/h2>\n<\/p>\n
\u8fc7\u53bb\uff0cPandas\u5e93\u4e2d\u8fd8\u6709\u4e00\u4e2a\u53eb\u505a.ix\u7684\u7d22\u5f15\u65b9\u6cd5\uff0c\u5b83\u53ef\u4ee5\u540c\u65f6\u57fa\u4e8e\u6807\u7b7e\u548c\u6574\u6570\u4f4d\u7f6e\u8fdb\u884c\u5b9a\u4f4d\u3002\u7136\u800c\uff0c\u7531\u4e8e\u8fd9\u4e2a\u65b9\u6cd5\u53ef\u80fd\u4f1a\u5bfc\u81f4\u6df7\u6dc6\uff0cPandas\u5728\u65b0\u7248\u672c\u4e2d\u5df2\u7ecf\u5f03\u7528.ix\u7d22\u5f15\uff0c\u5efa\u8bae\u4f7f\u7528.loc\u548c.iloc\u7d22\u5f15\u6765\u4ee3\u66ff\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u7ed3\u5408\u5176\u4ed6\u65b9\u6cd5\u548c\u6280\u5de7<\/h2>\n<\/p>\n
\u9664\u4e86\u4e0a\u8ff0\u7684\u7d22\u5f15\u65b9\u6cd5\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u7ed3\u5408\u5176\u4ed6\u65b9\u6cd5\u548c\u6280\u5de7\u6765\u83b7\u53d6\u6570\u636e\u6846\u7684\u4e00\u884c\u3002\u4f8b\u5982\uff0c\u4f7f\u7528\u5207\u7247\u64cd\u4f5c\u3001\u4f7f\u7528query\u65b9\u6cd5\u7b49\u3002<\/p>\n<\/p>\n
5.1\u3001\u4f7f\u7528\u5207\u7247\u64cd\u4f5c<\/h3>\n<\/p>\n
\u5207\u7247\u64cd\u4f5c\u53ef\u4ee5\u7528\u4e8e\u83b7\u53d6\u6570\u636e\u6846\u4e2d\u7684\u4e00\u884c\u6216\u591a\u884c\u6570\u636e\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u83b7\u53d6\u6570\u636e\u6846df\u7684\u7b2c\u4e8c\u884c\uff1a<\/p>\n<\/p>\n
row_1_slice = df[1:2]<\/p>\n
print(row_1_slice)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
   Name  Age           City<\/p>\n
1   Bob   30  San Francisco<\/p>\n
<\/code><\/pre>\n<\/p>\n
5.2\u3001\u4f7f\u7528query\u65b9\u6cd5<\/h3>\n<\/p>\n
query\u65b9\u6cd5\u53ef\u4ee5\u57fa\u4e8e\u6761\u4ef6\u6765\u83b7\u53d6\u6570\u636e\u6846\u4e2d\u7684\u4e00\u884c\u6216\u591a\u884c\u6570\u636e\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u83b7\u53d6\u5e74\u9f84\u5927\u4e8e30\u7684\u6240\u6709\u884c\uff1a<\/p>\n<\/p>\n
rows_age_gt_30_query = df.query('Age > 30')<\/p>\n
print(rows_age_gt_30_query)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
      Name  Age         City<\/p>\n
2  Charlie   35  Los Angeles<\/p>\n
<\/code><\/pre>\n<\/p>\n
5.3\u3001\u4f7f\u7528\u51fd\u6570\u548c\u81ea\u5b9a\u4e49\u65b9\u6cd5<\/h3>\n<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u7f16\u5199\u81ea\u5b9a\u4e49\u51fd\u6570\u548c\u65b9\u6cd5\u6765\u83b7\u53d6\u6570\u636e\u6846\u4e2d\u7684\u4e00\u884c\u3002\u4f8b\u5982\uff0c\u7f16\u5199\u4e00\u4e2a\u51fd\u6570\u6765\u83b7\u53d6\u6570\u636e\u6846\u4e2d\u6307\u5b9a\u7d22\u5f15\u548c\u5217\u7684\u5143\u7d20\uff1a<\/p>\n<\/p>\n
def get_element(df, index, column):<\/p>\n
    return df.at[index, column]<\/p>\n
age_b_custom = get_element(df, 'B', 'Age')<\/p>\n
print(age_b_custom)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
30<\/p>\n
<\/code><\/pre>\n<\/p>\n
5.4\u3001\u4f7f\u7528numpy\u548c\u5176\u4ed6\u5e93<\/h3>\n<\/p>\n
\u6709\u65f6\uff0c\u6211\u4eec\u53ef\u80fd\u9700\u8981\u7ed3\u5408\u5176\u4ed6\u5e93\uff08\u5982numpy\uff09\u6765\u5904\u7406\u6570\u636e\u6846\u3002\u4f8b\u5982\uff0c\u4f7f\u7528numpy\u6765\u83b7\u53d6\u6570\u636e\u6846\u4e2d\u7684\u4e00\u884c\u6570\u636e\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
row_1_np = np.array(df.iloc[1])<\/p>\n
print(row_1_np)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8f93\u51fa\u7ed3\u679c\u5c06\u662f\uff1a<\/p>\n<\/p>\n
['Bob' 30 'San Francisco']<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u603b\u7ed3<\/h2>\n<\/p>\n
\u5728Python\u4e2d\uff0c\u6709\u591a\u79cd\u65b9\u6cd5\u53ef\u4ee5\u7528\u6765\u83b7\u53d6\u6570\u636e\u6846\u7684\u4e00\u884c\uff0c\u5305\u62ec.loc\u7d22\u5f15\u3001.iloc\u7d22\u5f15\u3001.at\u7d22\u5f15\u3001\u5207\u7247\u64cd\u4f5c\u3001query\u65b9\u6cd5\u7b49<\/strong>\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002\u901a\u8fc7\u5408\u7406\u9009\u62e9\u548c\u7ed3\u5408\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u6211\u4eec\u53ef\u4ee5\u9ad8\u6548\u5730\u5904\u7406\u548c\u5206\u6790\u6570\u636e\u6846\u4e2d\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n
\u4f7f\u7528.loc\u7d22\u5f15\u53ef\u4ee5\u65b9\u4fbf\u5730\u901a\u8fc7\u884c\u6807\u7b7e\u6765\u83b7\u53d6\u6570\u636e\u6846\u7684\u4e00\u884c\u6570\u636e<\/strong>\uff0c\u7279\u522b\u9002\u5408\u5904\u7406\u6709\u660e\u786e\u884c\u6807\u7b7e\u7684\u6570\u636e\u6846\u3002\u4f7f\u7528.iloc\u7d22\u5f15\u53ef\u4ee5\u901a\u8fc7\u6574\u6570\u4f4d\u7f6e\u6765\u83b7\u53d6\u6570\u636e\u6846\u7684\u4e00\u884c\u6570\u636e<\/strong>\uff0c\u9002\u5408\u5904\u7406\u6ca1\u6709\u660e\u786e\u884c\u6807\u7b7e\u7684\u6570\u636e\u6846\u3002\u4f7f\u7528.at\u7d22\u5f15\u53ef\u4ee5\u9ad8\u6548\u5730\u83b7\u53d6\u5355\u4e2a\u5143\u7d20<\/strong>\uff0c\u7279\u522b\u9002\u5408\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u3002\u901a\u8fc7\u7ed3\u5408\u8fd9\u4e9b\u65b9\u6cd5\u548c\u5176\u4ed6\u6280\u5de7\uff0c\u6211\u4eec\u53ef\u4ee5\u7075\u6d3b\u5730\u6ee1\u8db3\u4e0d\u540c\u7684\u6570\u636e\u5904\u7406\u9700\u6c42\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u83b7\u53d6\u6570\u636e\u6846\u7279\u5b9a\u884c\u7684\u6570\u636e\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u4f7f\u7528Pandas\u5e93\u53ef\u4ee5\u8f7b\u677e\u83b7\u53d6\u6570\u636e\u6846\u7684\u7279\u5b9a\u884c\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528loc<\/code>\u6216iloc<\/code>\u65b9\u6cd5\u6765\u5b9e\u73b0\u3002loc<\/code>\u6839\u636e\u884c\u6807\u7b7e\u63d0\u53d6\u6570\u636e\uff0c\u800ciloc<\/code>\u6839\u636e\u884c\u7684\u6574\u6570\u4f4d\u7f6e\u63d0\u53d6\u3002\u6bd4\u5982\uff0c\u8981\u83b7\u53d6\u7b2c3\u884c\u7684\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528df.iloc[2]<\/code>\uff0c\u800c\u8981\u83b7\u53d6\u6807\u7b7e\u4e3a\u201cindex_name\u201d\u7684\u884c\uff0c\u53ef\u4ee5\u4f7f\u7528df.loc['index_name']<\/code>\u3002<\/p>\n
\u5982\u4f55\u4f7f\u7528\u6761\u4ef6\u7b5b\u9009\u5728\u6570\u636e\u6846\u4e2d\u83b7\u53d6\u884c\uff1f<\/strong>
\u4f60\u53ef\u4ee5\u4f7f\u7528\u5e03\u5c14\u7d22\u5f15\u6765\u6839\u636e\u7279\u5b9a\u6761\u4ef6\u7b5b\u9009\u6570\u636e\u6846\u4e2d\u7684\u884c\u3002\u4f8b\u5982\uff0c\u5982\u679c\u4f60\u60f3\u83b7\u53d6\u201c\u5e74\u9f84\u201d\u5217\u5927\u4e8e30\u5c81\u7684\u6240\u6709\u884c\uff0c\u53ef\u4ee5\u4f7f\u7528df[df['\u5e74\u9f84'] > 30]<\/code>\u3002\u8fd9\u79cd\u65b9\u6cd5\u5141\u8bb8\u7528\u6237\u5feb\u901f\u83b7\u53d6\u7b26\u5408\u6761\u4ef6\u7684\u884c\u6570\u636e\uff0c\u5341\u5206\u9ad8\u6548\u3002<\/p>\n
\u5728\u6570\u636e\u6846\u4e2d\u83b7\u53d6\u591a\u884c\u6570\u636e\u7684\u6700\u4f73\u65b9\u6cd5\u662f\u4ec0\u4e48\uff1f<\/strong>
\u82e5\u60f3\u83b7\u53d6\u591a\u884c\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528loc<\/code>\u6216iloc<\/code>\u7ed3\u5408\u884c\u7d22\u5f15\u7684\u5217\u8868\u3002\u4f8b\u5982\uff0c\u8981\u83b7\u53d6\u7b2c1\u5230\u7b2c3\u884c\u7684\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528df.iloc[0:3]<\/code>\uff0c\u800c\u8981\u83b7\u53d6\u6807\u7b7e\u4e3a\u201cindex_name1\u201d\u548c\u201cindex_name2\u201d\u7684\u591a\u884c\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528df.loc[['index_name1', 'index_name2']]<\/code>\u3002\u8fd9\u79cd\u65b9\u5f0f\u4fbf\u4e8e\u540c\u65f6\u8bbf\u95ee\u591a\u4e2a\u884c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u6cd5\u6765\u83b7\u53d6\u6570\u636e\u6846\u7684\u4e00\u884c\uff1a\u4f7f\u7528.loc\u7d22\u5f15\u3001\u4f7f\u7528.iloc\u7d22\u5f15\u3001\u4f7f\u7528at\u7d22\u5f15\u3002\u5176\u4e2d […]","protected":false},"author":3,"featured_media":1142366,"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\/1142358"}],"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=1142358"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1142358\/revisions"}],"predecessor-version":[{"id":1142371,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1142358\/revisions\/1142371"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1142366"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1142358"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1142358"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1142358"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}