d6tstack | Quickly ingest messy CSV and XLS files | CSV Processing library

by d6t Jupyter Notebook Version: 0.2.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | d6tstack Summary

d6tstack is a Jupyter Notebook library typically used in Utilities, CSV Processing, Pandas applications. d6tstack has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Quickly ingest messy CSV and XLS files. Export to clean pandas, SQL, parquet

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Quality

Security

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Support

d6tstack has a low active ecosystem.

It has 185 star(s) with 44 fork(s). There are 10 watchers for this library.

It had no major release in the last 12 months.

There are 17 open issues and 12 have been closed. On average issues are closed in 32 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of d6tstack is 0.2.0

Quality

d6tstack has 0 bugs and 0 code smells.

Security

d6tstack has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

d6tstack code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

d6tstack is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

d6tstack releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

It has 2234 lines of code, 204 functions and 21 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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d6tstack Key Features

No Key Features are available at this moment for d6tstack.

d6tstack Examples and Code Snippets

No Code Snippets are available at this moment for d6tstack.

Community Discussions

Trending Discussions on d6tstack

Large number of csv files with variable column length using Dask

QUESTION

Large number of csv files with variable column length using Dask

Asked 2020-Apr-27 at 17:00

I'm trying to use Dask to read a large number of csv, but I'm having issues since the number of columns varies between csv files, as does the order of the columns.

I know that packages like d6tstack (as detailed here), can help handle this, but is there a way to fix this without installing additional libraries and without taking up more disk space?

...

ANSWER

Answered 2020-Apr-27 at 17:00

If you use from_delayed, then you can make a function which pre-processes each of your input files as you might wish. This is totally arbitrary, so you can choose to solve the issue using your own code or any package you want to install across the cluster.

Source https://stackoverflow.com/questions/61460926

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install d6tstack

Latest published version pip install d6tstack. Additoinal requirements:. Latest dev version from github pip install git+https://github.com/d6t/d6tstack.git.
d6tstack[psql]: for pandas to postgres
d6tstack[mysql]: for pandas to mysql
d6tstack[xls]: for excel support
d6tstack[parquet]: for ingest csv to parquet

Support

SQL examples notebook - Fast loading of CSV to SQL with pandas preprocessingCSV examples notebook - Quickly load any type of CSV filesExcel examples notebook - Quickly extract from Excel to CSVDask Examples notebook - How to use d6tstack to solve Dask input file problemsPyspark Examples notebook - How to use d6tstack to solve pyspark input file problemsFunction reference docs - Detailed documentation for modules, classes, functions

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