A Python library for unevenly-spaced time series analysis. Greatly inspired by traces.
Get Started Notebook.
Usage
from ticts import TimeSeries
ts = TimeSeries({
'2019-01-01': 1,
'2019-01-01 00:10:00': 2,
'2019-01-01 00:11:00': 3,
})
assert ts['2019-01-01 00:05:00'] == 1
ts['2019-01-01 00:04:00'] = 10
assert ts['2019-01-01 00:05:00'] == 10
assert ts + ts == 2 * ts
ts_evenly_spaced = ts.sample(freq='1Min')
# From ticts to pandas, and the other way around
assert ts.equals(
ts.to_dataframe().to_ticts(),
)Installation
pip install tictsContributing
pip install pre-commit
pre-commit install --hook-type pre-push1 maintainer
Metadata
1 maintainer
Release files for ticts 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 | |
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| ticts-0.3.0.tar.gz | 132.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ticts-0.3.0-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 143.1 kB
Release files / ticts-0.3.0.tar.gz
| Download URL | ticts-0.3.0.tar.gz |
|---|---|
| Size | 132.2 kB |
| Tags | Source |
|
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Release files / ticts-0.3.0-py2.py3-none-any.whl
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| Tags | Python 2 Python 3 |
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