Tutorial: Super-Charge manipulation with DataFrames

Super-Charge manipulation with DataFrames

This library only intends to ease those getting into Jupyter and Notebooks.

There are many other libraries that go into detail farther than we will want to provide.

If you are just getting started, I might suggest working with d3 as a swiss army knife of the internet

If you are more familiar with Pandas and DataFrames, I might suggest DanfoJS

Additionally, if you are looking for number processing at hardware accelerated speeds, I would suggest reviewing other libraries, such as ScramJet and NumJS

Additionally, StdLib has some amazing work with hardware acceleration and GPU utilization.

D3

D3, specifically: group / rollup and flatGroup / flatRollup

DanfoJS

DanfoJS - a js library heavily inspired by Pandas so someone familiar with Pandas can get up to speed very quickly

DataFrame-JS

dataframe-js - provides an immutable data structure for DataFrames which allows to work on rows and columns with a sql and functional programming inspired api.

StandardLib

StdLib - is a great library that compiles down to C/C++ level to providespeeds comparable to Numpy.

NumJS

NumJS is also a great number processing library. It may not be as fast as StdLib, but it can sometimes be easier touse.