All Projects → nickslevine → Zebras

nickslevine / Zebras

Data analysis library for JavaScript built with Ramda

Programming Languages

javascript
184084 projects - #8 most used programming language

Projects that are alternatives of or similar to Zebras

Pandas Summary
An extension to pandas dataframes describe function.
Stars: ✭ 361 (+88.02%)
Mutual labels:  data-science, data-analysis, pandas
Mlcourse.ai
Open Machine Learning Course
Stars: ✭ 7,963 (+4047.4%)
Mutual labels:  data-science, data-analysis, pandas
Prettypandas
A Pandas Styler class for making beautiful tables
Stars: ✭ 376 (+95.83%)
Mutual labels:  data-science, data-analysis, pandas
Dtale
Visualizer for pandas data structures
Stars: ✭ 2,864 (+1391.67%)
Mutual labels:  data-science, data-analysis, pandas
Dat8
General Assembly's 2015 Data Science course in Washington, DC
Stars: ✭ 1,516 (+689.58%)
Mutual labels:  data-science, data-analysis, pandas
Data Science Hacks
Data Science Hacks consists of tips, tricks to help you become a better data scientist. Data science hacks are for all - beginner to advanced. Data science hacks consist of python, jupyter notebook, pandas hacks and so on.
Stars: ✭ 273 (+42.19%)
Mutual labels:  data-science, data-analysis, pandas
Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
Stars: ✭ 8,329 (+4238.02%)
Mutual labels:  data-science, data-analysis, pandas
Dataframe
C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types, continuous memory storage, and no pointers are involved
Stars: ✭ 828 (+331.25%)
Mutual labels:  data-science, data-analysis, pandas
Seaborn Tutorial
This repository is my attempt to help Data Science aspirants gain necessary Data Visualization skills required to progress in their career. It includes all the types of plot offered by Seaborn, applied on random datasets.
Stars: ✭ 114 (-40.62%)
Mutual labels:  data-science, data-analysis, pandas
Sweetviz
Visualize and compare datasets, target values and associations, with one line of code.
Stars: ✭ 1,851 (+864.06%)
Mutual labels:  data-science, data-analysis, pandas
Deepgraph
Analyze Data with Pandas-based Networks. Documentation:
Stars: ✭ 232 (+20.83%)
Mutual labels:  data-science, data-analysis, pandas
Rightmove webscraper.py
Python class to scrape data from rightmove.co.uk and return listings in a pandas DataFrame object
Stars: ✭ 125 (-34.9%)
Mutual labels:  data-science, data-analysis, pandas
Functional intro to python
[tutorial]A functional, Data Science focused introduction to Python
Stars: ✭ 228 (+18.75%)
Mutual labels:  data-science, pandas, functional-programming
Ai Learn
人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域
Stars: ✭ 4,387 (+2184.9%)
Mutual labels:  data-science, data-analysis, pandas
Data Science Notebook
📖 每一个伟大的思想和行动都有一个微不足道的开始
Stars: ✭ 196 (+2.08%)
Mutual labels:  data-science, data-analysis, pandas
Sspipe
Simple Smart Pipe: python productivity-tool for rapid data manipulation
Stars: ✭ 96 (-50%)
Mutual labels:  data-science, pandas, functional-programming
Pandas Videos
Jupyter notebook and datasets from the pandas Q&A video series
Stars: ✭ 1,716 (+793.75%)
Mutual labels:  data-science, data-analysis, pandas
Dtale Desktop
Build a data visualization dashboard with simple snippets of python code
Stars: ✭ 128 (-33.33%)
Mutual labels:  data-science, data-analysis, pandas
Ml Workspace
🛠 All-in-one web-based IDE specialized for machine learning and data science.
Stars: ✭ 2,337 (+1117.19%)
Mutual labels:  data-science, data-analysis
Machine Learning With Python
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
Stars: ✭ 2,197 (+1044.27%)
Mutual labels:  data-science, pandas

zebras - data analysis library for javascript

Coverage Status

Zebras is a data manipulation and analysis library written in JavaScript offering the convenience of pandas or R.

Zebras is especially useful for JS data analysis and visualization projects in notebooks on ObservableHQ or using the JS Jupyter kernel.

Unlike pandas, zebras is purely functional. All zebras functions accept data as an argument and return a new data structure transformed, and 'dataframes' are simply arrays of JS objects without any special methods.

Zebras is built on top of Ramda. Think of zebras as a collection of Ramda functions, and compositions of them, curated and repackaged for common data processing and data analysis tasks.

As in Ramda, all zebras functions are curried, making them easier to chain together. This means that, for example, zebras.sortByCol(col, df) is equivalent to zebras.sortByCol(col)(df).

An interactive introduction to the zebras library - using S&P 500 data - is available as an Observable notebook.

See the project roadmap on the zebras wiki here.

A guide to using zebras in a JS Jupyter notebook can be found on the zebras wiki here.

To Install

Locally with Node / Jupyter

npm install zebras --save
const z = require("zebras")

Online in an Observable notebook

z = require("zebras")

Example Usage

const z = require("zebras")
const data = z.readCSV("data.csv")
const parsedData = z.parseNums(["speed", "acc"], data)
const speed = z.getCol("speed", parsedData)
const avgSpeed = z.mean(speed)

Note: make sure numerical data imported into Zebras does not contain commas ("2342.5", not "2,342.5") - commas within numbers will throw off the parsing and lead to unexpected results.

Piping example:

const z = require("zebras")
const avgSpeed = z.pipe([
  // array of functions for input to travel through
  z.readCSV,
  z.parseNums(["speed", "acc"]),
  z.getCol("speed"),
  z.mean,
])("data.csv")

Documentation

See the full documentation here.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].