Amphi Visual data transformation platform for ETL, data preparation, and reporting. cstructpy Binary serialization framework for structured data using C-like primitive types. HashStash Caching library with multiple storage engines, serializers and compression options. iceaxe ORM framework for PostgreSQL ...
构建在NumPy之上的Pandas（Python Data Analysis Library的缩写）非常适合数据分析和数据处理。它拥有大量强...
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Pandas is a Python library that provides you with data structures and analysis tools. It simplifies ETL processes likedata cleansingby adding R-style data frames. However, it is time-consuming as you would have to write your own code. It can be used to write simple scripts quickly and is ...
etlhelperetlhelper is a Python ETL library to simplify data transfer into and out of databases.ETL Helper makes it easy to run SQL queries via Python and return the results. It takes care of cursor management, importing drivers and formatting connection strings, while providing memory-efficient ...
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. - pathwaycom/pathway
How to pick the best Python ETL tool? When choosing the right Python library for your data engineering tasks, pick one that: Covers all the different data sources you need to extract raw data from. Can handle complex pipelines used for cleaning and transforming data. Covers all the data dest...
在本书中最重要的库之一将是pandas,一个用于表格数据的库,非常适用于提取、转换、加载(ETL)任务。Pandas 是一个很棒的库,但是一旦涉及到更复杂的任务,您可能会遇到一些限制。Pandas 是处理数据加载和转换的首选库。数据处理的一个问题是,即使您向量化函数或使用df.apply(),它也可能速度较慢。 通过并行化apply可以...
前文提到过,数据处理另外一个流派是 data.table,基于 data.table 之上形成的分布式处理框架就是 disk.frame,disk.frame 和 Spark 的最大区别就是,disk.frame 优先解决的是计算密集型的复杂模型运算任务,让数据跟随计算;而 Spark 因为使用的是 Map-Reduce 模型,计算跟随数据,所以更擅长数据密集型的简单ETL运算任务...
粉丝的问题来源于实际的需求,她的Excel文件中现有20行数据,需要使用Python实现这个Excel文件中每3行存一个Excel文件。下图是原始数据: 如果是正常操作的话,肯定是点击进去Excel文件,然后每三行进行复制,然后粘贴到新文件,然后保存,之后重命名。 这样做肯定是可以,但是当有上百个文件夹需要复制呢?上千个文件呢?肯定就...