pudl | Public Utility Data Liberation Project | Dataset library

by catalyst-cooperative Python Version: v2022.11.30.post1 License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | pudl Summary

pudl is a Python library typically used in Artificial Intelligence, Dataset applications. pudl has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However pudl build file is not available. You can install using 'pip install pudl' or download it from GitHub, GitLab, PyPI.

The Public Utility Data Liberation Project provides analysis-ready energy system data to climate advocates, researchers, policymakers, and journalists.

Support

Quality

Security

License

Reuse

Support

pudl has a low active ecosystem.

It has 369 star(s) with 86 fork(s). There are 16 watchers for this library.

It had no major release in the last 12 months.

There are 332 open issues and 1241 have been closed. On average issues are closed in 138 days. There are 29 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pudl is v2022.11.30.post1

Quality

pudl has 0 bugs and 91 code smells.

Security

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

pudl code analysis shows 0 unresolved vulnerabilities.

There are 8 security hotspots that need review.

License

pudl 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

pudl releases are available to install and integrate.

Deployable package is available in PyPI.

pudl has no build file. You will be need to create the build yourself to build the component from source.

pudl saves you 6488 person hours of effort in developing the same functionality from scratch.

It has 13488 lines of code, 388 functions and 84 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed pudl and discovered the below as its top functions. This is intended to give you an instant insight into pudl implemented functionality, and help decide if they suit your requirements.

Calculate fuel cost for each component
Returns a dictionary mapping fields to dtypes
Clean merged dataframe
Apply dtypes to dataframe
Parse distributed generation
Compares the data columns and returns the sum of the calculated totals
Takes a DataFrame and returns a cleaned dataframe
Convert pct to mw
Parse the non - net metering table
Convert Ferc1 db to a sqlite database
Calculates plant_hydro
Assigns a set of generators to the prime_mover_code
Compute plant generation
Extract the utilities from EU860
Implements the latc method
Assign the number of unit_ids for each plant
Calculates MCOE
Computes the ownership of the EIA60 transform step
Parses the demand side management output
Merge fuel receipts costs
Concatenate generator data
Calculate plant_small_ffs
Calculate fuel costs
Extractility data from the utility data table
Extract generation genotypes from eia9
Assign plant IDs to fc

Get all kandi verified functions for this library.

pudl Key Features

No Key Features are available at this moment for pudl.

pudl Examples and Code Snippets

No Code Snippets are available at this moment for pudl.

Community Discussions

Trending Discussions on pudl

append specific amount of empty rows to pandas dataframe

script works in Jupyter notebook, fails from command line or Atom IDE

QUESTION

append specific amount of empty rows to pandas dataframe

Asked 2020-Nov-16 at 20:51

I want to append a specific amount of empty rows to that df

...

ANSWER

Answered 2020-Nov-16 at 20:44

I'm not too pandas savvy, but if you can already add one empty row, why not just try writing a for loop and appending x times?

Source https://stackoverflow.com/questions/64865397

QUESTION

script works in Jupyter notebook, fails from command line or Atom IDE

Asked 2020-Jan-10 at 16:35

I have python installed via Anaconda, and want to serialize a rather large dataframe to a disk file. This runs well on a Jupyter notebook, but fails when run from the Atom IDE or the command prompt (i.e. python script_name.py)

...

ANSWER

Answered 2020-Jan-10 at 16:35

You probably need to activate the environment where your Jupyter kernel resides, as that will be pulling in the necessary dependencies on your behalf.

Assuming you've already created an environment using conda create -n my_conda_env you'll also have to activate it using conda activate -n my_conda_env then your cmd prompt will be prefixed with the name of the environment.

If you're not running in an environment - I'd really recommend it - as it can avoid some dependency issues.

Source https://stackoverflow.com/questions/59673085

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

Vulnerabilities

No vulnerabilities reported

Install pudl

You can install using 'pip install pudl' or download it from GitHub, GitLab, PyPI.
You can use pudl like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: