![\"python\u5982\u4f55\u6279\u91cf\u5904\u7406\u6570\u636e\"](\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25095558\/6ad70adf-916a-40f7-b1d5-ea44116dbc79.webp\")
<\/p>\n<\/p>\n
Python\u6279\u91cf\u5904\u7406\u6570\u636e\u7684\u5e38\u7528\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528Pandas\u5e93\u5904\u7406\u6570\u636e\u8868\u3001\u5229\u7528NumPy\u8fdb\u884c\u6570\u7ec4\u548c\u77e9\u9635\u64cd\u4f5c\u3001\u901a\u8fc7Dask\u5b9e\u73b0\u5e76\u884c\u8ba1\u7b97\u3001\u7ed3\u5408SQLAlchemy\u4e0e\u6570\u636e\u5e93\u4e92\u52a8\u3001\u5229\u7528multiprocessing\u6a21\u5757\u5e76\u884c\u5904\u7406\u6570\u636e\u3002<\/strong> \u5176\u4e2d\uff0c\u4f7f\u7528Pandas\u5e93\u5904\u7406\u6570\u636e\u8868\u662f\u4e00\u79cd\u975e\u5e38\u9ad8\u6548\u7684\u65b9\u6cd5\uff0c\u9002\u7528\u4e8e\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e\uff0c\u5982CSV\u6587\u4ef6\u3001Excel\u8868\u683c\u6216SQL\u6570\u636e\u5e93\u4e2d\u7684\u8868\u683c\u3002Pandas\u63d0\u4f9b\u4e86\u591a\u79cd\u6570\u636e\u5904\u7406\u529f\u80fd\uff0c\u5305\u62ec\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u8f6c\u6362\u3001\u5206\u7ec4\u805a\u5408\u7b49\uff0c\u4f7f\u5f97\u6279\u91cf\u5904\u7406\u6570\u636e\u53d8\u5f97\u66f4\u52a0\u7b80\u4fbf\u3002<\/p>\n<\/p>\n \u4f7f\u7528Pandas\u5904\u7406\u6570\u636e\u65f6\uff0c\u9996\u5148\u9700\u8981\u5c06\u6570\u636e\u52a0\u8f7d\u5230DataFrame\u4e2d\uff0c\u8fd9\u662f\u4e00\u79cd\u7c7b\u4f3c\u4e8e\u7535\u5b50\u8868\u683c\u7684\u4e8c\u7ef4\u6570\u636e\u7ed3\u6784\u3002\u901a\u8fc7DataFrame\uff0c\u7528\u6237\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u7b5b\u9009\u3001\u8fc7\u6ee4\u3001\u6392\u5e8f\u548c\u5408\u5e76\u7b49\u64cd\u4f5c\u3002Pandas\u8fd8\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u6765\u5904\u7406\u7f3a\u5931\u503c\u3001\u91cd\u590d\u503c\u548c\u6570\u636e\u7c7b\u578b\u8f6c\u6362\u7b49\u95ee\u9898\u3002\u4f8b\u5982\uff0c\u901a\u8fc7 \u63a5\u4e0b\u6765\uff0c\u5c06\u8be6\u7ec6\u4ecb\u7ecdPython\u6279\u91cf\u5904\u7406\u6570\u636e\u7684\u5176\u4ed6\u65b9\u6cd5\u548c\u6280\u5de7\u3002<\/p>\n<\/p>\n Pandas\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u5206\u6790\u5e93\u4e4b\u4e00\uff0c\u9002\u7528\u4e8e\u5904\u7406\u5404\u79cd\u7ed3\u6784\u5316\u6570\u636e\u3002<\/p>\n<\/p>\n Pandas\u652f\u6301\u591a\u79cd\u6570\u636e\u683c\u5f0f\u7684\u52a0\u8f7d\uff0c\u5982CSV\u3001Excel\u3001SQL\u7b49\u3002\u53ef\u4ee5\u4f7f\u7528 df_csv = pd.read_csv('data.csv')<\/p>\n df_excel = pd.read_excel('data.xlsx', sheet_name='Sheet1')<\/p>\n import sqlite3<\/p>\n conn = sqlite3.connect('database.db')<\/p>\n df_sql = pd.read_sql_query('SELECT * FROM table', conn)<\/p>\n <\/code><\/pre>\n<\/p>\n \u6570\u636e\u6e05\u6d17\u662f\u6570\u636e\u5904\u7406\u7684\u91cd\u8981\u6b65\u9aa4\uff0cPandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u5de5\u5177\u6765\u6e05\u6d17\u548c\u8f6c\u6362\u6570\u636e\u3002<\/p>\n<\/p>\n \u901a\u8fc7 df_clean = df_csv.dropna()<\/p>\n df_filled = df_csv.fillna(0)<\/p>\n <\/code><\/pre>\n<\/p>\n \u4f7f\u7528 df_csv['column_name'] = df_csv['column_name'].astype(int)<\/p>\n <\/code><\/pre>\n<\/p>\n Pandas\u652f\u6301\u591a\u79cd\u5b57\u7b26\u4e32\u64cd\u4f5c\uff0c\u5982\u5927\u5c0f\u5199\u8f6c\u6362\u3001\u5b57\u7b26\u4e32\u5206\u5272\u7b49\u3002<\/p>\n<\/p>\n df_csv['string_column'] = df_csv['string_column'].str.lower()<\/p>\n <\/code><\/pre>\n<\/p>\n Pandas\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u4e0e\u805a\u5408\u529f\u80fd\uff0c\u5982\u5206\u7ec4\u3001\u7edf\u8ba1\u3001\u900f\u89c6\u8868\u7b49\u3002<\/p>\n<\/p>\n \u4f7f\u7528 grouped = df_csv.groupby('group_column').mean()<\/p>\n <\/code><\/pre>\n<\/p>\n pivot_table = pd.pivot_table(df_csv, values='value_column', index='index_column', columns='columns_column', aggfunc='sum')<\/p>\n <\/code><\/pre>\n<\/p>\n NumPy\u662fPython\u7684\u57fa\u7840\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u9002\u5408\u8fdb\u884c\u5927\u89c4\u6a21\u7684\u6570\u7ec4\u548c\u77e9\u9635\u8fd0\u7b97\u3002<\/p>\n<\/p>\n NumPy\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u5f0f\u521b\u5efa\u6570\u7ec4\uff0c\u5982\u4f7f\u7528\u5217\u8868\u3001\u5143\u7ec4\uff0c\u6216\u4ece\u6587\u4ef6\u52a0\u8f7d\u6570\u636e\u3002<\/p>\n<\/p>\n array = np.array([1, 2, 3, 4, 5])<\/p>\n zeros = np.zeros((3, 3))<\/p>\n array_from_file = np.loadtxt('data.txt')<\/p>\n <\/code><\/pre>\n<\/p>\n NumPy\u652f\u6301\u591a\u79cd\u6570\u7ec4\u8fd0\u7b97\uff0c\u5305\u62ec\u7b97\u672f\u8fd0\u7b97\u3001\u77e9\u9635\u8fd0\u7b97\u3001\u7edf\u8ba1\u8fd0\u7b97\u7b49\u3002<\/p>\n<\/p>\n array_sum = array + 10<\/p>\n matrix_product = np.dot(array, array.T)<\/p>\n mean_value = np.mean(array)<\/p>\n <\/code><\/pre>\n<\/p>\n Dask\u662f\u4e00\u4e2a\u7075\u6d3b\u7684\u5e76\u884c\u8ba1\u7b97\u5e93\uff0c\u9002\u5408\u5904\u7406\u5927\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n Dask\u63d0\u4f9b\u4e86\u4e0ePandas\u7c7b\u4f3c\u7684DataFrame\u63a5\u53e3\uff0c\u4f46\u652f\u6301\u5e76\u884c\u8ba1\u7b97\u3002<\/p>\n<\/p>\n dask_df = dd.read_csv('large_data.csv')<\/p>\n mean_value = dask_df['column_name'].mean().compute()<\/p>\n <\/code><\/pre>\n<\/p>\n Dask Array\u7c7b\u4f3c\u4e8eNumPy\u6570\u7ec4\uff0c\u4f46\u652f\u6301\u5206\u5e03\u5f0f\u8ba1\u7b97\u3002<\/p>\n<\/p>\n dask_array = da.random.random((10000, 10000), chunks=(1000, 1000))<\/p>\n array_sum = dask_array.sum().compute()<\/p>\n <\/code><\/pre>\n<\/p>\n SQLAlchemy\u662fPython\u7684ORM\u5de5\u5177\uff0c\u9002\u5408\u4e0e\u5173\u7cfb\u578b\u6570\u636e\u5e93\u8fdb\u884c\u4ea4\u4e92\u3002<\/p>\n<\/p>\n \u901a\u8fc7SQLAlchemy\u53ef\u4ee5\u8f7b\u677e\u8fde\u63a5\u5230\u5404\u79cd\u6570\u636e\u5e93\u3002<\/p>\n<\/p>\n engine = create_engine('sqlite:\/\/\/database.db')<\/p>\n connection = engine.connect()<\/p>\n <\/code><\/pre>\n<\/p>\n \u53ef\u4ee5\u4f7f\u7528SQLAlchemy\u6267\u884cSQL\u67e5\u8be2\uff0c\u5e76\u5c06\u7ed3\u679c\u52a0\u8f7d\u5230Pandas DataFrame\u4e2d\u3002<\/p>\n<\/p>\n result = connection.execute('SELECT * FROM table_name')<\/p>\n df_sqlalchemy = pd.DataFrame(result.fetchall(), columns=result.keys())<\/p>\n <\/code><\/pre>\n<\/p>\n multiprocessing\u6a21\u5757\u652f\u6301\u5e76\u884c\u5904\u7406\u6570\u636e\uff0c\u52a0\u5feb\u5904\u7406\u901f\u5ea6\u3002<\/p>\n<\/p>\n \u901a\u8fc7 def process_data(data_chunk):<\/p>\n # \u5904\u7406\u6570\u636e<\/p>\n return sum(data_chunk)<\/p>\n with Pool(processes=4) as pool:<\/p>\n # \u5e76\u884c\u5904\u7406\u6570\u636e<\/p>\n results = pool.map(process_data, data_chunks)<\/p>\n <\/code><\/pre>\n<\/p>\n multiprocessing\u8fd8\u652f\u6301\u5171\u4eab\u5185\u5b58\u5bf9\u8c61\uff0c\u5b9e\u73b0\u8fdb\u7a0b\u95f4\u901a\u4fe1\u3002<\/p>\n<\/p>\n shared_array = Array('i', range(10))<\/p>\n def modify_array(index, value):<\/p>\n shared_array[index] = value<\/p>\n <\/code><\/pre>\n<\/p>\n \u901a\u8fc7\u4ee5\u4e0a\u65b9\u6cd5\uff0cPython\u53ef\u4ee5\u9ad8\u6548\u5730\u5b9e\u73b0\u6279\u91cf\u6570\u636e\u5904\u7406\uff0c\u9002\u7528\u4e8e\u5404\u79cd\u6570\u636e\u5206\u6790\u573a\u666f\u3002\u7ed3\u5408Pandas\u3001NumPy\u3001Dask\u3001SQLAlchemy\u3001multiprocessing\u7b49\u5de5\u5177\uff0c\u7528\u6237\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u548c\u5e93\uff0c\u4ee5\u63d0\u9ad8\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u548c\u6548\u679c\u3002<\/p>\n<\/p>\n \u5982\u4f55\u4f7f\u7528Python\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\uff1f<\/strong> \u5728Python\u4e2d\uff0c\u6709\u54ea\u4e9b\u65b9\u6cd5\u53ef\u4ee5\u52a0\u5feb\u6570\u636e\u5904\u7406\u901f\u5ea6\uff1f<\/strong> \u5982\u4f55\u5728Python\u4e2d\u6279\u91cf\u8bfb\u53d6\u548c\u5199\u5165\u6587\u4ef6\uff1f<\/strong>dropna()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u8f7b\u677e\u53bb\u9664\u7f3a\u5931\u503c\uff0c\u901a\u8fc7fillna()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u586b\u5145\u7f3a\u5931\u503c\uff0c\u901a\u8fc7astype()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u8f6c\u6362\u6570\u636e\u7c7b\u578b\u3002\u6b64\u5916\uff0cPandas\u8fd8\u652f\u6301\u5206\u7ec4\u548c\u805a\u5408\u64cd\u4f5c\uff0c\u4f7f\u5f97\u5bf9\u6570\u636e\u7684\u5206\u6790\u66f4\u52a0\u7075\u6d3b\u548c\u9ad8\u6548\u3002<\/p>\n<\/p>\n\u4e00\u3001\u4f7f\u7528Pandas\u5e93\u8fdb\u884c\u6570\u636e\u5904\u7406<\/h3>\n<\/p>\n
1\u3001\u52a0\u8f7d\u6570\u636e<\/h4>\n<\/p>\n
read_csv()<\/code>\u3001read_excel()<\/code>\u3001read_sql()<\/code>\u7b49\u65b9\u6cd5\u5feb\u901f\u52a0\u8f7d\u6570\u636e\u3002<\/p>\n<\/p>\nimport pandas as pd<\/p>\n\u52a0\u8f7dCSV\u6587\u4ef6<\/strong><\/h2>\n
\u52a0\u8f7dExcel\u6587\u4ef6<\/strong><\/h2>\n
\u4eceSQL\u6570\u636e\u5e93\u52a0\u8f7d\u6570\u636e<\/strong><\/h2>\n
2\u3001\u6570\u636e\u6e05\u6d17\u4e0e\u8f6c\u6362<\/h4>\n<\/p>\n
\n
dropna()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u53bb\u9664\u7f3a\u5931\u503c\uff0c\u901a\u8fc7fillna()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u586b\u5145\u7f3a\u5931\u503c\u3002<\/p>\n<\/p>\n# \u53bb\u9664\u7f3a\u5931\u503c<\/p>\n\u586b\u5145\u7f3a\u5931\u503c<\/strong><\/h2>\n
\n
astype()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u8f6c\u6362\u6570\u636e\u7c7b\u578b\u3002<\/p>\n<\/p>\n# \u5c06\u5217\u8f6c\u6362\u4e3a\u6574\u6570\u7c7b\u578b<\/p>\n\n
# \u5b57\u7b26\u4e32\u8f6c\u5c0f\u5199<\/p>\n3\u3001\u6570\u636e\u5206\u6790\u4e0e\u805a\u5408<\/h4>\n<\/p>\n
\n
groupby()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u5b9e\u73b0\u6570\u636e\u7684\u5206\u7ec4\u548c\u805a\u5408\u3002<\/p>\n<\/p>\n# \u6309\u5217\u5206\u7ec4\u5e76\u8ba1\u7b97\u5e73\u5747\u503c<\/p>\n\n
pivot_table()<\/code>\u65b9\u6cd5\u53ef\u4ee5\u521b\u5efa\u900f\u89c6\u8868\u3002<\/p>\n<\/p>\n# \u521b\u5efa\u900f\u89c6\u8868<\/p>\n\u4e8c\u3001\u4f7f\u7528NumPy\u8fdb\u884c\u6570\u7ec4\u64cd\u4f5c<\/h3>\n<\/p>\n
1\u3001\u521b\u5efa\u6570\u7ec4<\/h4>\n<\/p>\n
import numpy as np<\/p>\n\u4ece\u5217\u8868\u521b\u5efa\u6570\u7ec4<\/strong><\/h2>\n
\u521b\u5efa\u5168\u96f6\u6570\u7ec4<\/strong><\/h2>\n
\u4ece\u6587\u4ef6\u52a0\u8f7d\u6570\u7ec4<\/strong><\/h2>\n
2\u3001\u6570\u7ec4\u8fd0\u7b97<\/h4>\n<\/p>\n
# \u6570\u7ec4\u52a0\u6cd5<\/p>\n\u77e9\u9635\u4e58\u6cd5<\/strong><\/h2>\n
\u7edf\u8ba1\u8fd0\u7b97<\/strong><\/h2>\n
\u4e09\u3001\u5229\u7528Dask\u8fdb\u884c\u5e76\u884c\u8ba1\u7b97<\/h3>\n<\/p>\n
1\u3001Dask DataFrame<\/h4>\n<\/p>\n
import dask.dataframe as dd<\/p>\n\u4eceCSV\u6587\u4ef6\u521b\u5efaDask DataFrame<\/strong><\/h2>\n
\u8ba1\u7b97\u5217\u7684\u5e73\u5747\u503c<\/strong><\/h2>\n
2\u3001Dask Array<\/h4>\n<\/p>\n
import dask.array as da<\/p>\n\u521b\u5efaDask Array<\/strong><\/h2>\n
\u8ba1\u7b97\u6570\u7ec4\u7684\u603b\u548c<\/strong><\/h2>\n
\u56db\u3001\u7ed3\u5408SQLAlchemy\u4e0e\u6570\u636e\u5e93\u4e92\u52a8<\/h3>\n<\/p>\n
1\u3001\u8fde\u63a5\u6570\u636e\u5e93<\/h4>\n<\/p>\n
from sqlalchemy import create_engine<\/p>\n\u521b\u5efa\u6570\u636e\u5e93\u5f15\u64ce<\/strong><\/h2>\n
\u8fde\u63a5\u5230\u6570\u636e\u5e93<\/strong><\/h2>\n
2\u3001\u6267\u884c\u67e5\u8be2<\/h4>\n<\/p>\n
# \u6267\u884cSQL\u67e5\u8be2<\/p>\n\u52a0\u8f7d\u7ed3\u679c\u5230Pandas DataFrame<\/strong><\/h2>\n
\u4e94\u3001\u4f7f\u7528multiprocessing\u6a21\u5757\u5e76\u884c\u5904\u7406\u6570\u636e<\/h3>\n<\/p>\n
1\u3001\u521b\u5efa\u8fdb\u7a0b\u6c60<\/h4>\n<\/p>\n
Pool<\/code>\u5bf9\u8c61\u53ef\u4ee5\u521b\u5efa\u8fdb\u7a0b\u6c60\uff0c\u5b9e\u73b0\u5e76\u884c\u8ba1\u7b97\u3002<\/p>\n<\/p>\nfrom multiprocessing import Pool<\/p>\n\u5b9a\u4e49\u5904\u7406\u51fd\u6570<\/strong><\/h2>\n
\u521b\u5efa\u8fdb\u7a0b\u6c60<\/strong><\/h2>\n
2\u3001\u5171\u4eab\u5185\u5b58\u5bf9\u8c61<\/h4>\n<\/p>\n
from multiprocessing import Array<\/p>\n\u521b\u5efa\u5171\u4eab\u6570\u7ec4<\/strong><\/h2>\n
\u8bbf\u95ee\u5171\u4eab\u6570\u7ec4<\/strong><\/h2>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
Python\u63d0\u4f9b\u4e86\u591a\u79cd\u5e93\uff0c\u5982Pandas\u548cDask\uff0c\u4e13\u95e8\u7528\u4e8e\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u3002Pandas\u4ee5\u5176\u5f3a\u5927\u7684\u6570\u636e\u6846\u67b6\u548c\u7075\u6d3b\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\u800c\u95fb\u540d\uff0c\u800cDask\u5219\u5141\u8bb8\u7528\u6237\u5728\u5185\u5b58\u53d7\u9650\u7684\u60c5\u51b5\u4e0b\u8fdb\u884c\u5e76\u884c\u5904\u7406\u3002\u901a\u8fc7\u8fd9\u4e9b\u5de5\u5177\uff0c\u7528\u6237\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3001\u8f6c\u6362\u548c\u5206\u6790\u3002<\/p>\n
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