509 Open source projects that are alternatives of or similar to raccoon

A linear optimisation model for distributed energy systems

A log parsing website for Guild Wars 2 combat logs

Spark VCF data source implementation for Dataframes

Code, Notebooks and Examples from Practical Business Python

Jupyter notebook and datasets from the pandas Q&A video series

Reading and writing pandas DataFrames in Elasticsearch

Read/write Google spreadsheets using pandas DataFrames

Study E-Book(ComputerVision DeepLearning MachineLearning Math NLP Python ReinforcementLearning)

Small library to read serialized protobuf(s) directly into Pandas Dataframe

Twelve Data Python Client - Financial data APIs & WebSockets

These are the projects I did on my Udacity Deep Learning Nanodegree 🌟 💻 💻. 💥 🌈

100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

Nested Sampling post-processing and plotting

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

DataFrame Library for Java

A directory listing of all my pandas canonicals on Stack Overflow to date.

Facial Expression Recognition

Graph-Based Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, RDFlib, pySHACL, RAPIDS, NetworkX, iGraph, PyVis, pslpython, pyarrow, etc.

Built on data from Pluralsight's course API fetched results. Works with model trained with K-means unsupervised clustering algorithm.

dotweb-start

Learn Python for the next 30 (or so) Days.

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

A simple library to extract video and audio frames from media containers (based on libav).

Credit Risk analysis by using Python and ML

Taking the O out of ORM.

Pandas-based utility to calculate weighted means, medians, distributions, standard deviations, and more.

Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.

This is about learning data scientist with Python 2019 and some new updated courses in DataCamp. All the answers given written by myself

Simplified tracking of your investments

Example notebooks illustrating MovingPandas use cases

A pandas-like deferred expression system, with first-class SQL support

WPF通用权限开发框架

Small Docker image with Python Machine Learning tools (~180MB) https://hub.docker.com/r/frolvlad/alpine-python-machinelearning/

In this repository, You can find the files which implement dimensionality reduction on the hyperspectral image(Indian Pines) with classification.

Tools for financial economics. Curated wrapper over Python ecosystem. Source code for fecon235 Jupyter notebooks.

Go data analysis / manipulation library built on top of Apache Arrow

SQL upsert using pandas DataFrames for PostgreSQL, SQlite and MySQL with extra features

A Grammar of Data Manipulation in python

Tutorial on Using Pandas

Data science and numerical computing with Julia

Material for my PyData Jupyter & Pandas Workshops, I'm also available for personal in-house trainings on request

I have been deeply interested in algorithmic trading and systematic trading algorithms. This Repository contains the code of what I have learnt on the way. It starts form some basic simple statistics and will lead up to complex machine learning algorithms.

Head Pose Estimator on Caffe

Rust crates for the H3 geospatial indexing system

Parallel computing with task scheduling

Make window/frame transparent.

Distance Recognition of a Human Being with Deep CNN's

A component that can arrange items according to the type of grids

Курс "Введение в машинное обучение" (ВМК, МГУ имени М.В. Ломоносова)

daily report of @ARKInvest ETF activity + data collection

📊📈 Serves up Pandas dataframes via the Django REST Framework for use in client-side (i.e. d3.js) visualizations and offline analysis (e.g. Excel)

TrainmanJS - Cross-Origin Communication Library

Some useful Tips and Tricks to speed up the data analysis process in Python.

D-Lab's 3 hour introduction to data visualization with Python. Learn how to create histograms, bar plots, box plots, scatter plots, compound figures, and more, using matplotlib and seaborn.

Accelerate data science

Tools that make working with scikit-learn and pandas easier.

General Assembly's 2015 Data Science course in Washington, DC

Manage Google Spreadsheets in Pandas DataFrame with Python

Using Jupyter Notebook with Django: a presentation

A Los Angeles Times analysis of Every shot in Kobe Bryant's NBA career