Orange3 add-on for exploring time series and sequential data.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for AlesErjavec from gravatar.com AlesErjavec Avatar for apretnar from gravatar.com apretnar Avatar for biolab-helper from gravatar.com biolab-helper Avatar for janezdemsar from gravatar.com janezdemsar Avatar for lanzagar from gravatar.com lanzagar Avatar for markotoplak from gravatar.com markotoplak Avatar for primozgodec from gravatar.com primozgodec Avatar for rokgomiscek from gravatar.com rokgomiscek

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU General Public License v3 or later (GPLv3+) (GPLv3+)
  • Author: Bioinformatics Laboratory, FRI UL
  • Tags time series, sequence analysis, orange3 add-on, ARIMA, VAR model, forecast
Classifiers

Project description

Orange3-Timeseries

Orange add-on for analyzing, visualizing, manipulating, and forecasting time series data. The add-on includes ARIMA and VAR models, model evaluation, time series preprocessing, seasonal adjustment and a wide array of visualizations. See documentation.

Features

Use time series data

  • reinterpret data as time series
  • induce missing values
  • generate time series from Yahoo Finance stock market data

Analysis of time series data

  • aggregate data by a given time interval
  • decompose the time series into seasonal, trend, and residual components
  • apply rolling window functions to the time series
  • make forecasts for the future
  • evaluate models

Visualize time series data

  • visualize time series’ sequence and progression
  • visualize variables’ auto-correlation
  • visualize time series’ cycles, seasonality, periodicity, and most significant periods

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for AlesErjavec from gravatar.com AlesErjavec Avatar for apretnar from gravatar.com apretnar Avatar for biolab-helper from gravatar.com biolab-helper Avatar for janezdemsar from gravatar.com janezdemsar Avatar for lanzagar from gravatar.com lanzagar Avatar for markotoplak from gravatar.com markotoplak Avatar for primozgodec from gravatar.com primozgodec Avatar for rokgomiscek from gravatar.com rokgomiscek

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU General Public License v3 or later (GPLv3+) (GPLv3+)
  • Author: Bioinformatics Laboratory, FRI UL
  • Tags time series, sequence analysis, orange3 add-on, ARIMA, VAR model, forecast
Classifiers

Release history Release notifications | RSS feed

0.6.3

0.6.2

0.6.1

0.6.0

This version

0.5.3

0.5.2

0.5.1

0.5.0 yanked

Reason this release was yanked:

Pyqtgraph not fixed, Line Chart won't work.

0.4.1

0.4.0

0.3.12

0.3.11

0.3.10

0.3.9

0.3.8

0.3.7

0.3.6

0.3.5

0.3.4

0.3.3

0.3.2

0.3.1

0.3.0

0.2.7

0.2.6

0.2.5

0.2.4

0.2.3

0.2.2

0.2.1

0.2.0

0.1.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Orange3-Timeseries-0.5.3.tar.gz (2.3 MB view details)

Uploaded Source

Built Distribution

Orange3_Timeseries-0.5.3-py3-none-any.whl (280.8 kB view details)

Uploaded Python 3

File details

Details for the file Orange3-Timeseries-0.5.3.tar.gz.

File metadata

  • Download URL: Orange3-Timeseries-0.5.3.tar.gz
  • Upload date:
  • Size: 2.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.9

File hashes

Hashes for Orange3-Timeseries-0.5.3.tar.gz
Algorithm Hash digest
SHA256 b2edc48b8646a791db312a76eee412a1f4b28997b60b9ac984a8674f82bcd08f
MD5 3e2f0090d900e86637e2e0d46dddf1de
BLAKE2b-256 79530fcf4da63080b519c0cac924af0b2332fdee0791ba7d1b1b7f23219557be

See more details on using hashes here.

File details

Details for the file Orange3_Timeseries-0.5.3-py3-none-any.whl.

File metadata

File hashes

Hashes for Orange3_Timeseries-0.5.3-py3-none-any.whl
Algorithm Hash digest
SHA256 c889874b0a7fd1cb1b12c225a154c16f99f975e5447ac86e102b5f50c0a9a429
MD5 0f43703ffd5f3f23c318a5a6719b1296
BLAKE2b-256 9f76209b066fa87ecd6cbfa6c1b58e299ad4126ceaad1c8b8760a9ca7b6306b2

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page