Reverse Dependencies of seaborn
The following projects have a declared dependency on seaborn:
- PREAGeoFuns — A package for geo tools used to map card score
- predectorutils — Utility scripts for the predector pipeline.
- predictionconsoandrea — Utilities package
- predictit — Library/framework for making time series predictions with help of AutoML tools.
- prefsampling — Algorithms to sample preferences of all kinds.
- prenigma-automl — prenigma_automl - An open source, low-code machine learning library.
- prenigmaautoml — prenigma_automl - An open source, low-code machine learning library.
- PRESC — Performance Robustness Evaluation for Statistical Classifiers
- prestools — My personal functions and utilities for Python programming.
- prettierplot — Quickly create prettier plots
- pretty-confusion-matrix — plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib
- pretty-jupyter — Exports Jupyter notebook into beautiful and dynamic HTML report.
- prfiesta — Collect and Analyze Individual Contributor Pull Requests
- prfsim — A free & open source python tool for population receptive field simulation of fMRI data.
- pricer — Use WoW addon data to optimize auction buying and selling policies
- PricingEngine — Predict the the ACV of the used car dealer can buy in optimised price to gain maximum profit.
- primary-data-analysis — Primary data analysis for pandas dataframe
- prjforinfcreditvilfw — no summary
- probatus — Validation of regression & classifiers and data used to develop them
- process-improve — Process Improvement using Data: Designed Experiments; Latent Variables (PCA, PLS, multivariate methods with missing data); Process Monitoring; Batch data analysis.
- processmining — Python processmining Package
- prodclass — Uma biblioteca Python para auxiliar na vetorização e categorização de descrições de produto.
- profiles-pycorelib — A Python Native package that registers the core python models
- profiplots — Package for helping data scientists create beautiful profinit-styled plots.
- ProgPlot — progplot - Timeseries barplot animations.
- projected-earnings — Automate emails
- projplot — Projection plots for assessing convergence of optimization routines
- prolif — Interaction Fingerprints for protein-ligand complexes and more
- prolint2 — ProLint2: Lipid-Protein Interaction Analysis.
- prolothar-common — algorithms for process mining and data mining on event sequences
- promptedgraphs — From Dataset Labeling to Deployment: The Power of NLP and LLMs Combined.
- PromptMeteo — Enable the use of LLMs as a conventional ML model
- prosit — A topic models algorithm
- ProsNet — A package for processing activPAL activity monitor data.
- prosper-nn — Package contains, in PyTorch implemented, neural networks with problem specific pre-structuring architectures and utils that help building and understanding models.
- prosphera — Visualize Multidimensional Data on a Sphere
- prospr — A toolbox for protein folding with Python.
- protein-cluster-conformers — Clusters conformations of monomeric protein
- protein-design — Python tools for protein design
- protein-inference — Protein Inference Library for Network based Inference
- proteomicruler — Estimate copy number from deep profile MS experiment using the Proteomic Ruler algorithm from Wiśniewski, J. R., Hein, M. Y., Cox, J. and Mann, M. (2014) A “Proteomic Ruler” for Protein Copy Number and Concentration Estimation without Spike-in Standards. Mol Cell Proteomics 13, 3497–3506.
- proteomics-downstream-analysis — A package for downstream data analysis of proteomics data
- protes — Method PROTES (PRobabilistic Optimizer with TEnsor Sampling) for derivative-free optimization of the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) format
- proteusPy — proteusPy - Protein Structure Analysis and Modeling Tools
- protexam — Inspect your quantitative proteomics results using this streamlit-powered dashboard. The app is specifically tailored for comprehensive examination of result files from isobaric labeling-based quantitative experiments.
- protloc-mex-x — ...
- protloc-mex1 — ...
- protoflow — Highly extensible, GPU-supported Learning Vector Quantization (LVQ) toolbox built using Tensorflow 2.x and its Keras API.
- ps-signal — Module for parsing and analysing data from a picoscope.
- psdm-analysis — no summary
- psdmpy — no summary
- psifr — Psifr: Analysis and visualization of free recall data
- psinspect — Power spectra inspector for the SO LAT experiment
- psireact — Response time modeling of psychology experiments
- psite — Model-based inference of P-site offsets
- psite-recommender — RS for Proteomics
- psmpy — Propensity score matching for python and graphical plots
- psy-maps — Psyplot plugin for visualization on a map
- psy-simple — Psyplot plugin for simple visualization tasks
- psyplot — Python package for interactive data visualization
- ptitprince — A Python implementation of Rainclouds, originally on R, ggplot2. Written on top of seaborn.
- ptrail — PTRAIL: A Mobility-data Preprocessing Library using parallel computation.
- ptvpy — A command line tool and library for particle tracking velocimetry.
- public-data-food-analysis-3 — This project analyzes data from a few input sources.
- pubmed-lib — Simple wrapper for pubmed resutls
- pubmed-screen — Automates the initial screening phase of systematic PubMed search using keywords.
- pug-nlp — Python Natural Language Processing by and for the Python User Group in Portland, OR
- pugnlp — Python Natural Language Processing by and for the Python User Group in Portland, OR
- pull-the-pitcher — Predicting when AL managers will remove their starting pitchers.
- pumml — Positive and Unlabeled Materials Machine Learning (pumml) is a code that uses semi-supervised positive and unlabeled (PU) machine learning to classify materials when data is incomplete and only examples of 'positive' materials are available.
- punctuation-stylometry — This package represents the code used for the publication of the article https://arxiv.org/abs/1901.00519
- punditkit — PunditKit: A GUI for Scikit-Learn Models
- pupil-invisible-lsl-relay — Relay Pupil Invisible data to LabStreamingLayer
- pureml-evaluate — no summary
- pureml-policy — no summary
- pv-vision — Image analysis of defects on solar modules, including automatic detection and power loss prediction
- pvOps — pvops is a python library for the analysis of field collected operational data for photovoltaic systems.
- pvtpy — Oil&Gas PVT Tool
- PW-explorer — An Extensible Possible World Explorer for Answer Set Programming
- pwmdist — package for essential statistics of extreme value distirbutions using probability weighted moments
- py-bpca — Python Bounded PCA
- py-csi-cobotics — A Python framework for controlling and processing experiments built upon the CSI:Cobot Digital Twin
- py-data-juicer — A One-Stop Data Processing System for Large Language Models.
- py-doc — Used for working with documentations in Python.
- py-easyDL — easyDL - Where Deep learning is meant to be easy.
- py-feat — Facial Expression Analysis Toolbox
- py-neuromodulation — Real-time analysis of intracranial neurophysiology recordings.
- Py-OMA — PyOMA allows the experimental estimation of the modal parameters (natural frequencies, mode shapes, damping ratios) of a structure from measurements of the vibration response in operational condition.
- py-open-dsse — Open source library for state estimation of a distribution network modeled in OpenDSS
- py-rdpackages — A Pythonic Package for Regression Discontinuity
- py-replay-bg — ReplayBG is a digital twin-based methodology to assess new strategies for type 1 diabetes management.
- py-report-html — Add a short description here!
- py-scProportionTest — Python package to evaluate differences in cell type proportions
- py-smps — A simple python library to import and visualize data from particle sizing instruments.
- py-utilz — Faster, easier, more robust python data analysis
- py3dpolys-le — 3D Polymer Simulations - Loop Extrusion model
- py4dgeo — Library for change detection in 4D point cloud data
- py4pm — no summary
- py50 — Generate Dose-Response Curves
- pyAB — A/B Testing using Bayesian & Frequentist Statistics