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https://github.com/dataship/frame
A DataFrame for Javascript
https://github.com/dataship/frame
data-frame data-science javascript statistics
Last synced: about 15 hours ago
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A DataFrame for Javascript
- Host: GitHub
- URL: https://github.com/dataship/frame
- Owner: dataship
- License: mit
- Created: 2016-11-17T18:31:41.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2017-11-08T16:12:46.000Z (about 7 years ago)
- Last Synced: 2024-11-09T11:42:21.119Z (10 days ago)
- Topics: data-frame, data-science, javascript, statistics
- Language: JavaScript
- Homepage:
- Size: 137 KB
- Stars: 18
- Watchers: 3
- Forks: 5
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# frame
a DataFrame for Javascript.
_crunch numbers in Node or the Browser_
## features
* Interactive performance (<100ms) on millions of rows
* Syntax similar to SQL and Pandas
* Compatible with `PapaParse` and [`BabyParse`](https://github.com/Rich-Harris/BabyParse)
## examples
Parse the [Iris](https://vincentarelbundock.github.io/Rdatasets/datasets.html)
dataset (with [`BabyParse`](https://github.com/Rich-Harris/BabyParse)) and create a `Frame` from the result.
```javascript
var baby = require('babyparse'),
Frame = require('frame');
// parse the csv file
config = {"header" :true, "dynamicTyping" : true, "skipEmptyLines" : true};
iris = baby.parseFiles('iris.csv', config).data;
// create a frame from the parsed results
frame = new Frame(iris);
```
### groupby
Group on `Species` and find the average value (`mean`) for `Sepal.Length`.
```javascript
g = frame.groupby("Species");
g.mean("Sepal.Length");
```
```json
{ "virginica": 6.58799, "versicolor": 5.9360, "setosa": 5.006 }
```
Using the same grouping, find the average value for `Sepal.Width`.
```javascript
g.mean("Sepal.Width");
```
```json
{ "virginica": 2.97399, "versicolor": 2.770, "setosa": 3.4279 }
```
### where
Filter by `Species` value `virginica` then find the average.
```javascript
f = frame.where("Species", "virginica");
f.mean("Sepal.Length");
```
```json
6.58799
```
Get the number of rows that match the filter.
```javascript
f.count();
```
```json
50
```
Columns can also be accessed directly (with the filter applied).
```javascript
f["Species"]
```
```javascript
["virginica", "virginica", "virginica", ..., "virginica"]
```
# tests
Hundreds of tests verify correctness on millions of data points (against a Pandas reference).
`npm run data && npm run test`
# benchmarks
`npm run bench`
typical performance on one million rows
operation | time
----------|------
`groupby` | 54ms
`where` | 29ms
`sum` | 5ms
# design goals and inspiration
* compatibility with [feather](https://github.com/wesm/feather)
## interface
* pandas
* R
* Linq
* rethinkDB
* Matlab
## performance
* [datavore](https://github.com/StanfordHCI/datavore)