hubify
Create GitHub-like visualisations from your time series data.
Basic Usage
# A list of datetimes, where each datetime represents an observation
from datetime import datetime, timedelta
import random
# Import Hubify
from hubify import hubify
# Set a seed
random.seed(42)
# Create 400 random events
events = [
datetime.today() - timedelta(days=random.randint(0, 365))
for _ in range(400)
]
# Call hubify
hubify(events)
You should see something like this
Installation
pip install hubify
1 maintainer
Metadata
1 maintainer
Release files for hubify 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hubify-0.3.0.tar.gz | 4.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hubify-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.8 kB
Release files / hubify-0.3.0.tar.gz
| Download URL | hubify-0.3.0.tar.gz |
|---|---|
| Size | 4.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
fab44d8aee6100f0987b5e2664dd31545b93360ff8f475384261cca610b198f9
|
|
BLAKE2b-256 checksum How to use checksums |
521d27c7edc09b6fef3c91fdc980ec847c513a968b3a7dfcab5c0b50d0032ff3
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.13 CPython/3.7.13 Linux/5.13.0-1031-azure
|
Release files / hubify-0.3.0-py3-none-any.whl
| Download URL | hubify-0.3.0-py3-none-any.whl |
|---|---|
| Size | 4.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
1d823c8c9a887f81bc5ca57f56b04dee87b584b0b914d6a5d600685654161ea7
|
|
BLAKE2b-256 checksum How to use checksums |
e4779f960076e43432717b0f1fba4aeaea2134c1c5af573576d9809e79ec262f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.1.13 CPython/3.7.13 Linux/5.13.0-1031-azure
|
