{"id":1034312,"date":"2024-12-31T11:49:15","date_gmt":"2024-12-31T03:49:15","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1034312.html"},"modified":"2024-12-31T11:49:17","modified_gmt":"2024-12-31T03:49:17","slug":"python%e5%a6%82%e4%bd%95%e5%b0%86%e6%95%b0%e6%8d%ae%e5%ad%98%e5%85%a5%e5%86%85%e5%ad%98","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1034312.html","title":{"rendered":"python\u5982\u4f55\u5c06\u6570\u636e\u5b58\u5165\u5185\u5b58"},"content":{"rendered":"

\"python\u5982\u4f55\u5c06\u6570\u636e\u5b58\u5165\u5185\u5b58\"<\/p>\n

Python\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5c06\u6570\u636e\u5b58\u5165\u5185\u5b58\uff0c\u4f8b\u5982\u4f7f\u7528\u5217\u8868\u3001\u5b57\u5178\u3001\u96c6\u5408\u7b49\u6570\u636e\u7ed3\u6784\uff0c\u4f7f\u7528Pandas\u5e93\u7684\u6570\u636e\u6846\u3001\u4f7f\u7528Numpy\u5e93\u7684\u6570\u7ec4\u7b49\u3002<\/strong>\u5728\u8fd9\u51e0\u79cd\u65b9\u5f0f\u4e2d\uff0c\u4f7f\u7528\u5217\u8868\u548c\u5b57\u5178\u662f\u6700\u5e38\u89c1\u7684\uff0c\u5c06\u6570\u636e\u5b58\u5165\u8fd9\u4e9b\u6570\u636e\u7ed3\u6784\u4e2d\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u64cd\u4f5c\u548c\u5904\u7406\u3002\u4e0b\u9762\u8be6\u7ec6\u4ecb\u7ecd\u4e00\u4e0b\u4f7f\u7528\u5217\u8868\u548c\u5b57\u5178\u5b58\u50a8\u6570\u636e\u7684\u65b9\u5f0f\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528\u5217\u8868\u5b58\u50a8\u6570\u636e<\/h3>\n<\/p>\n

\u5217\u8868\u662fPython\u4e2d\u6700\u57fa\u672c\u7684\u5185\u7f6e\u6570\u636e\u7ed3\u6784\u4e4b\u4e00\uff0c\u5177\u6709\u7075\u6d3b\u548c\u52a8\u6001\u7684\u7279\u70b9\uff0c\u53ef\u4ee5\u5b58\u50a8\u4efb\u4f55\u7c7b\u578b\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n

1. \u521b\u5efa\u5217\u8868\u5e76\u5b58\u50a8\u6570\u636e<\/h4>\n<\/p>\n

\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u65b9\u62ec\u53f7 []<\/code> \u6765\u521b\u5efa\u5217\u8868\uff0c\u5e76\u5c06\u6570\u636e\u653e\u5165\u5176\u4e2d\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n

# \u521b\u5efa\u4e00\u4e2a\u7a7a\u5217\u8868<\/p>\n
data_list = []<\/p>\n
\u5411\u5217\u8868\u4e2d\u6dfb\u52a0\u6570\u636e<\/strong><\/h2>\n
data_list.append(1)<\/p>\n
data_list.append(2)<\/p>\n
data_list.append(3)<\/p>\n
print(data_list)  # \u8f93\u51fa: [1, 2, 3]<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u76f4\u63a5\u521d\u59cb\u5316\u5217\u8868<\/h4>\n<\/p>\n
\u8fd8\u53ef\u4ee5\u5728\u521b\u5efa\u5217\u8868\u65f6\u76f4\u63a5\u521d\u59cb\u5316\u6570\u636e\uff1a<\/p>\n<\/p>\n
# \u76f4\u63a5\u521b\u5efa\u5e76\u521d\u59cb\u5316\u5217\u8868<\/p>\n
data_list = [1, 2, 3, 4, 5]<\/p>\n
print(data_list)  # \u8f93\u51fa: [1, 2, 3, 4, 5]<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u5217\u8868\u64cd\u4f5c<\/h4>\n<\/p>\n
\u5217\u8868\u5177\u6709\u8bb8\u591a\u5185\u7f6e\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u5404\u79cd\u64cd\u4f5c\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
data_list = [1, 2, 3, 4, 5]<\/p>\n
\u8bbf\u95ee\u5217\u8868\u4e2d\u7684\u5143\u7d20<\/strong><\/h2>\n
print(data_list[0])  # \u8f93\u51fa: 1<\/p>\n
\u4fee\u6539\u5217\u8868\u4e2d\u7684\u5143\u7d20<\/strong><\/h2>\n
data_list[1] = 10<\/p>\n
\u5220\u9664\u5217\u8868\u4e2d\u7684\u5143\u7d20<\/strong><\/h2>\n
data_list.remove(3)<\/p>\n
\u5217\u8868\u7684\u957f\u5ea6<\/strong><\/h2>\n
print(len(data_list))  # \u8f93\u51fa: 4<\/p>\n
\u904d\u5386\u5217\u8868<\/strong><\/h2>\n
for item in data_list:<\/p>\n
    print(item)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528\u5b57\u5178\u5b58\u50a8\u6570\u636e<\/h3>\n<\/p>\n
\u5b57\u5178\u662fPython\u4e2d\u53e6\u4e00\u79cd\u5e38\u7528\u7684\u6570\u636e\u7ed3\u6784\uff0c\u7528\u4e8e\u5b58\u50a8\u952e\u503c\u5bf9\u3002\u5b83\u7279\u522b\u9002\u5408\u5b58\u50a8\u5173\u8054\u6570\u636e\u3002<\/p>\n<\/p>\n
1. \u521b\u5efa\u5b57\u5178\u5e76\u5b58\u50a8\u6570\u636e<\/h4>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528\u82b1\u62ec\u53f7 {}<\/code> \u6765\u521b\u5efa\u5b57\u5178\uff0c\u5e76\u5c06\u952e\u503c\u5bf9\u653e\u5165\u5176\u4e2d\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
# \u521b\u5efa\u4e00\u4e2a\u7a7a\u5b57\u5178<\/p>\n
data_dict = {}<\/p>\n
\u5411\u5b57\u5178\u4e2d\u6dfb\u52a0\u6570\u636e<\/strong><\/h2>\n
data_dict['name'] = 'Alice'<\/p>\n
data_dict['age'] = 25<\/p>\n
print(data_dict)  # \u8f93\u51fa: {'name': 'Alice', 'age': 25}<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u76f4\u63a5\u521d\u59cb\u5316\u5b57\u5178<\/h4>\n<\/p>\n
\u8fd8\u53ef\u4ee5\u5728\u521b\u5efa\u5b57\u5178\u65f6\u76f4\u63a5\u521d\u59cb\u5316\u6570\u636e\uff1a<\/p>\n<\/p>\n
# \u76f4\u63a5\u521b\u5efa\u5e76\u521d\u59cb\u5316\u5b57\u5178<\/p>\n
data_dict = {'name': 'Bob', 'age': 30}<\/p>\n
print(data_dict)  # \u8f93\u51fa: {'name': 'Bob', 'age': 30}<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u5b57\u5178\u64cd\u4f5c<\/h4>\n<\/p>\n
\u5b57\u5178\u4e5f\u6709\u8bb8\u591a\u5185\u7f6e\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u5404\u79cd\u64cd\u4f5c\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
data_dict = {'name': 'Charlie', 'age': 35}<\/p>\n
\u8bbf\u95ee\u5b57\u5178\u4e2d\u7684\u503c<\/strong><\/h2>\n
print(data_dict['name'])  # \u8f93\u51fa: Charlie<\/p>\n
\u4fee\u6539\u5b57\u5178\u4e2d\u7684\u503c<\/strong><\/h2>\n
data_dict['age'] = 40<\/p>\n
\u5220\u9664\u5b57\u5178\u4e2d\u7684\u952e\u503c\u5bf9<\/strong><\/h2>\n
del data_dict['name']<\/p>\n
\u5b57\u5178\u7684\u957f\u5ea6<\/strong><\/h2>\n
print(len(data_dict))  # \u8f93\u51fa: 1<\/p>\n
\u904d\u5386\u5b57\u5178<\/strong><\/h2>\n
for key, value in data_dict.items():<\/p>\n
    print(f'{key}: {value}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Pandas\u5b58\u50a8\u6570\u636e<\/h3>\n<\/p>\n
Pandas\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u529f\u80fd\uff0cDataFrame\u662fPandas\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u7ed3\u6784\uff0c\u7c7b\u4f3c\u4e8e\u7535\u5b50\u8868\u683c\u3002<\/p>\n<\/p>\n
1. \u521b\u5efaDataFrame\u5e76\u5b58\u50a8\u6570\u636e<\/h4>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u4e2d\u7684 DataFrame<\/code> \u6765\u521b\u5efa\u6570\u636e\u6846\uff0c\u5e76\u5c06\u6570\u636e\u5b58\u50a8\u5176\u4e2d\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u521b\u5efaDataFrame\u5e76\u5b58\u50a8\u6570\u636e<\/strong><\/h2>\n
data = {'name': ['Alice', 'Bob', 'Charlie'],<\/p>\n
        'age': [25, 30, 35]}<\/p>\n
data_frame = pd.DataFrame(data)<\/p>\n
print(data_frame)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u8bfb\u53d6\u6570\u636e\u5230DataFrame<\/h4>\n<\/p>\n
\u53ef\u4ee5\u4eceCSV\u6587\u4ef6\u6216\u5176\u4ed6\u6570\u636e\u6e90\u8bfb\u53d6\u6570\u636e\u5230DataFrame\u4e2d\uff1a<\/p>\n<\/p>\n
# \u4eceCSV\u6587\u4ef6\u8bfb\u53d6\u6570\u636e<\/p>\n
data_frame = pd.read_csv('data.csv')<\/p>\n
print(data_frame)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. DataFrame\u64cd\u4f5c<\/h4>\n<\/p>\n
DataFrame\u5177\u6709\u4e30\u5bcc\u7684\u64cd\u4f5c\u65b9\u6cd5\uff0c\u53ef\u4ee5\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u5904\u7406\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
# \u8bbf\u95eeDataFrame\u4e2d\u7684\u5217<\/p>\n
print(data_frame['name'])<\/p>\n
\u4fee\u6539DataFrame\u4e2d\u7684\u503c<\/strong><\/h2>\n
data_frame.loc[0, 'age'] = 26<\/p>\n
\u5220\u9664DataFrame\u4e2d\u7684\u884c<\/strong><\/h2>\n
data_frame = data_frame.drop(1)<\/p>\n
DataFrame\u7684\u5f62\u72b6<\/strong><\/h2>\n
print(data_frame.shape)<\/p>\n
\u904d\u5386DataFrame<\/strong><\/h2>\n
for index, row in data_frame.iterrows():<\/p>\n
    print(row['name'], row['age'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528Numpy\u5b58\u50a8\u6570\u636e<\/h3>\n<\/p>\n
Numpy\u5e93\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u591a\u7ef4\u6570\u7ec4\u64cd\u4f5c\uff0c\u9002\u5408\u8fdb\u884c\u6570\u503c\u8ba1\u7b97\u548c\u79d1\u5b66\u8ba1\u7b97\u3002<\/p>\n<\/p>\n
1. \u521b\u5efaNumpy\u6570\u7ec4\u5e76\u5b58\u50a8\u6570\u636e<\/h4>\n<\/p>\n
\u53ef\u4ee5\u4f7f\u7528Numpy\u5e93\u4e2d\u7684 array<\/code> \u6765\u521b\u5efa\u6570\u7ec4\uff0c\u5e76\u5c06\u6570\u636e\u5b58\u50a8\u5176\u4e2d\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
\u521b\u5efaNumpy\u6570\u7ec4\u5e76\u5b58\u50a8\u6570\u636e<\/strong><\/h2>\n
data_array = np.array([1, 2, 3, 4, 5])<\/p>\n
print(data_array)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u6570\u7ec4\u64cd\u4f5c<\/h4>\n<\/p>\n
Numpy\u6570\u7ec4\u5177\u6709\u8bb8\u591a\u5185\u7f6e\u65b9\u6cd5\uff0c\u53ef\u4ee5\u8fdb\u884c\u6570\u503c\u8ba1\u7b97\u548c\u64cd\u4f5c\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
data_array = np.array([1, 2, 3, 4, 5])<\/p>\n
\u8bbf\u95ee\u6570\u7ec4\u4e2d\u7684\u5143\u7d20<\/strong><\/h2>\n
print(data_array[0])  # \u8f93\u51fa: 1<\/p>\n
\u4fee\u6539\u6570\u7ec4\u4e2d\u7684\u5143\u7d20<\/strong><\/h2>\n
data_array[1] = 10<\/p>\n
\u6570\u7ec4\u7684\u5f62\u72b6<\/strong><\/h2>\n
print(data_array.shape)<\/p>\n
\u6570\u7ec4\u7684\u957f\u5ea6<\/strong><\/h2>\n
print(len(data_array))<\/p>\n
\u6570\u7ec4\u7684\u8fd0\u7b97<\/strong><\/h2>\n
data_array = data_array * 2<\/p>\n
print(data_array)  # \u8f93\u51fa: [ 2 20  6  8 10]<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u5c06\u6570\u636e\u5b58\u5165\u5185\u5b58\u7684\u65b9\u5f0f\u6709\u5f88\u591a\uff0c\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u7ed3\u6784\u548c\u5e93\u53ef\u4ee5\u63d0\u9ad8\u6570\u636e\u64cd\u4f5c\u548c\u5904\u7406\u7684\u6548\u7387\u3002\u5217\u8868\u548c\u5b57\u5178\u662f\u6700\u57fa\u7840\u7684\u6570\u636e\u7ed3\u6784\uff0c\u9002\u5408\u5b58\u50a8\u7b80\u5355\u7684\u6570\u636e\u3002Pandas\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u529f\u80fd\uff0c\u9002\u5408\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e\u3002Numpy\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u503c\u8ba1\u7b97\u529f\u80fd\uff0c\u9002\u5408\u8fdb\u884c\u79d1\u5b66\u8ba1\u7b97\u548c\u6570\u503c\u5206\u6790\u3002\u6839\u636e\u5177\u4f53\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u5f0f\uff0c\u53ef\u4ee5\u66f4\u597d\u5730\u5b9e\u73b0\u6570\u636e\u5b58\u50a8\u548c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528\u6570\u636e\u7ed3\u6784\u5b58\u50a8\u6570\u636e\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5404\u79cd\u6570\u636e\u7ed3\u6784\u6765\u5b58\u50a8\u6570\u636e\uff0c\u4f8b\u5982\u5217\u8868\u3001\u5143\u7ec4\u3001\u5b57\u5178\u548c\u96c6\u5408\u3002\u5217\u8868\u9002\u5408\u5b58\u50a8\u6709\u5e8f\u7684\u5143\u7d20\uff0c\u5143\u7ec4\u7528\u4e8e\u4e0d\u53ef\u53d8\u7684\u5e8f\u5217\uff0c\u5b57\u5178\u5219\u662f\u952e\u503c\u5bf9\u7684\u96c6\u5408\uff0c\u975e\u5e38\u9002\u5408\u5feb\u901f\u67e5\u627e\uff0c\u800c\u96c6\u5408\u5219\u7528\u4e8e\u5b58\u50a8\u4e0d\u91cd\u590d\u7684\u5143\u7d20\u3002\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u7ed3\u6784\u5c06\u5e2e\u52a9\u60a8\u66f4\u6709\u6548\u5730\u7ba1\u7406\u5185\u5b58\u548c\u6570\u636e\u3002<\/p>\n
\u5185\u5b58\u4e2d\u7684\u6570\u636e\u5b58\u50a8\u6709\u4ec0\u4e48\u9650\u5236\uff1f<\/strong>
\u5185\u5b58\u7684\u5b58\u50a8\u5bb9\u91cf\u901a\u5e38\u53d7\u5230\u8ba1\u7b97\u673a\u7269\u7406\u5185\u5b58\u7684\u9650\u5236\u3002\u5b58\u50a8\u5927\u91cf\u6570\u636e\u53ef\u80fd\u4f1a\u5bfc\u81f4\u5185\u5b58\u6ea2\u51fa\uff0c\u5c24\u5176\u662f\u5728\u5904\u7406\u5927\u6570\u636e\u96c6\u65f6\u3002\u56e0\u6b64\uff0c\u4e86\u89e3\u60a8\u7684\u7cfb\u7edf\u5185\u5b58\u548c\u6570\u636e\u5927\u5c0f\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u5982\u679c\u5185\u5b58\u4e0d\u8db3\uff0c\u53ef\u4ee5\u8003\u8651\u4f7f\u7528\u6570\u636e\u5e93\u6216\u6587\u4ef6\u7cfb\u7edf\u6765\u5b58\u50a8\u6570\u636e\uff0c\u6216\u8005\u4f7f\u7528Python\u7684\u751f\u6210\u5668\u6765\u9010\u6b65\u5904\u7406\u6570\u636e\u3002<\/p>\n
\u5982\u4f55\u4f18\u5316\u5728\u5185\u5b58\u4e2d\u5b58\u50a8\u6570\u636e\u7684\u6548\u7387\uff1f<\/strong>
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