Dstools NPM | npm.io

Dstools - Data Science Tools for Javascript

dstools is a collection of tools that assist in analyzing and visualizing data using Javascript code inside Jupyter notebooks. Its main features are:

All functions are chainable (jQuery style)
Import csv data files from the web or file system (using csv package)
Statistical analysis using jStat package
Show data as tables within Jupyter notebooks
Visualize data using plotly javascript library within Jupyter notebooks

Function reference and jsdoc based documentation can be found at https://elshor.github.io/dstools/

Installing dstools

Install dstools using npm

npm install dstools

When using dstools from Jupyter notebooks with the IJavascript kernel, the package should be installed in the same directory as the notebook.

Getting Started

First step in handling data is usually loading the data

const Collection = require('dstools').Collection;
const data = Collection().loadCSV('data.csv');

Alternatively, the data can be wrapped using the Collection function:

const data = Collection([{field1:2,field2:4},{field1:3,field2:5}]);

inside the Jupyter notebook, the data can be displayed as a table using the show function.

data.show();

The data will be displayed as an HTML table.

Visualizations are possible using the various visualization functions.

data.histogram('field1').show();

When the code is executed inside a Jupyter notebook, it will display a histogram using the plotly javascript library.

The data function can be used to get the underlying data

console.log(data.data());

The html function can be used to wrap html text. Subsequent calls of the show function will display the html in the Jupyter notebook.

Here is a more elaborate example taken from a medium post:

const Collection = require('dstools').Collection;
Collection()
.loadCSV('/home/elshor/data/winemag-data-130k-v2.csv')//load the data
.terms({field:'description'}).dropStopwords('term')
.sortDesc('count').head(50)
.wordCloud('term','count')//arguments are label and measure
.show();//show the wordcloud in Jupyter notebook

Function Reference

Function reference and jsdoc based documentation can be found at https://elshor.github.io/dstools/

Additional Statistical Functions

The following jStat functions take as argument the field name and return the jStat function with the column vector as its argument. The following functions are supported: sum,sumsqrd,sumsqerr,product,min,max,mean,meansqerr,geomean,median,cumsum,cumprod,diff,rank,range,variance,deviation,stdev,skewness,kurtosis,coeffvar,quartiles,quantiles,percentile. Consult the jStat documentation for details.