摘要: SELECT TABLE_NAME AS '表名', COLUMN_NAME AS '字段名', DATA_TYPE AS '数据类型', IS_NULLABLE AS '是否可空', COLUMN_DEFAULT AS '默认值', COLUMN_COMMENT AS '字段注释', CHARAC 阅读全文
posted @ 2025-12-08 16:09 xxxyyyxxxok 阅读(2) 评论(0) 推荐(0)
摘要: SELECT TABLE_NAME AS '表名', COLUMN_NAME AS '字段名', DATA_TYPE AS '数据类型', IS_NULLABLE AS '是否可空', COLUMN_DEFAULT AS '默认值', COLUMN_COMMENT AS '字段注释', CHARAC 阅读全文
posted @ 2025-12-08 16:07 xxxyyyxxxok 阅读(2) 评论(0) 推荐(0)
摘要: 加载模型及量化 from modelscope import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained(model_dir, trust_remote_code=True) model = AutoModel 阅读全文
posted @ 2024-07-29 19:12 xxxyyyxxxok 阅读(63) 评论(0) 推荐(0)
摘要: import pandas as pd from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression,Ridge from sklearn.svm im 阅读全文
posted @ 2024-07-28 19:05 xxxyyyxxxok 阅读(188) 评论(0) 推荐(0)
摘要: import pandas as pd from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression,Ridge from sklearn.svm im 阅读全文
posted @ 2024-07-28 18:49 xxxyyyxxxok 阅读(13) 评论(0) 推荐(0)
摘要: 更改顺序 insert、pop df.insert(0,'a',df.pop('a')) 分组排序 df['班级Python成绩排名'] = df.groupby('班级')['Python成绩'].rank(method='min', ascending=False) 离散化 df['class' 阅读全文
posted @ 2024-07-28 17:29 xxxyyyxxxok 阅读(21) 评论(0) 推荐(0)
摘要: assign df.assign( col3=df["col2"].str.upper(), col4=df["col1"] * 3 / 4 + 25, col5=lambda x: x["col1"] / 2 + 10, col6=lambda x: x["col5"] * 5, # 在col6计 阅读全文
posted @ 2024-07-28 17:27 xxxyyyxxxok 阅读(58) 评论(0) 推荐(0)