https://github.com/fatmatto/timeframes

Dataframe-like API for timeseries-like data
https://github.com/fatmatto/timeframes

dataframe timeseries typescript

Last synced: 10 days ago
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Dataframe-like API for timeseries-like data

• Host: GitHub
• URL: https://github.com/fatmatto/timeframes
• Owner: fatmatto
• License: mit
• Created: 2022-04-08T07:51:33.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2025-01-09T14:41:53.000Z (27 days ago)
• Last Synced: 2025-01-09T15:39:30.114Z (27 days ago)
• Topics: dataframe, timeseries, typescript
• Language: TypeScript
• Homepage: https://fatmatto.github.io/timeframes
• Size: 815 KB
• Stars: 3
• Watchers: 3
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: .github/CONTRIBUTING.md
  • License: LICENSE

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README

        

Timeframes




  Dataframe-like API for timeseries-like data

  
 ⚠️ This is still a work in progress


## Quickstart

Install through NPM

```bash

npm i @apio/timeframes

```

There are a few examples that you can check out in the [examples directory](https://github.com/fatmatto/timeframes/tree/main/examples).

## TimeSeries

![Timeseries](images/timeserie.png?raw=true "Timeseries")

```javascript

import { TimeSerie } from '@apio/timeframes'

// Pass an array of points

// a point is a tuple [DateLike, PointValue]

// DateLike is value that can be passed to new Date()

// PointValue is any value, but preferably a number (to compute sums averages ecc)

const ts = new TimeSerie([["2022-01-01", 12],["2022-01-02", 13]])

const sum = ts.sum()

const avg = ts.avg()

```

## TimeFrames

![Timeframes](images/timeframe.png?raw=true "Timeframes")

```javascript

import { TimeFrame } from '@apio/timeframes'

// Each item is a row

const rows = [

  {time: "2022-01-01", value1:10, value2:140},

  {time: "2022-01-02", value1:41}, // here value2 is null

  {time: "2022-01-03", value1:78, value2:301},

]

const ts = new TimeFrame(rows)

// column() extracts columns as timeseries

const total1 = ts.column("value1").sum()

```