{"repo":"BBVA/mercury-dataschema","free":true,"listed":false,"github":"https://github.com/BBVA/mercury-dataschema","clone":"git clone https://github.com/BBVA/mercury-dataschema.git","description":"Utility package that, given a Pandas DataFrame, it uses the DataSchema class which auto-infers feature types and automatically calculates different statistics depending on the types.","language":"Python","stars":16,"topics":["analytics","data","data-cleaning","data-processing","feature-engineering","data-science"],"license":"Apache-2.0","category":"analytics","readme_excerpt":"mercury-dataschema mercury-dataschema is a submodule of the Mercury library which acts as a utility tool that, given a Pandas DataFrame, its DataSchema class auto-infers feature types and automatically calculates different statistics depending on them. This type inference isn't solely based on data types but in the information the variables contain. For example: if a feature is encoded as a float but its cardinality is 2, we can be sure it's a binary feature. This package is used by other Mercury submodules, and you also can use it separately from the rest of the library. As an idea (there are plenty of them, though), it is particularly useful when preprocessing datasets. Having to specify the typical categorical cols and coninuous cols is over! Mercury project at BBVA Mercury is a collaborative library that was developed by the Advanced Analytics community at BBVA. Originally, it was created as an InnerSource project but after some time, we decided to release certain parts of the project as Open Source. That's the case with the mercury-dataschema package. If you're interested in learning more about the Mercury project, we recommend reading this blog post from www.bbvaaifactory.com User installation The easiest way to install mercury-dataschema is using pip : pip install -U mercury-dataschema Example Then, we can inspect all the features with And we can get extra feature statistics by inspecting the .stats attribute of the Feature objects. Note how for different features, the","default_branch":null,"files":null,"tree":[],"storefront":"/r/BBVA","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/BBVA/mercury-dataschema/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}