ticts
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,
})
not_in_index = '2019-01-01 00:05:00'
assert ts[not_in_index] == 1 # step function, previous value
ts['2019-01-01 00:04:00'] = 10
assert ts[not_in_index] == 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 ticts
Metadata
Release files for ticts 0.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| ticts-0.6.1.tar.gz | 79.6 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ticts-0.6.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 92.1 kB
Release files / ticts-0.6.1.tar.gz
| Download URL | ticts-0.6.1.tar.gz |
|---|---|
| Size | 79.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
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|
Release files / ticts-0.6.1-py3-none-any.whl
| Download URL | ticts-0.6.1-py3-none-any.whl |
|---|---|
| Size | 12.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.14
|
Security for ticts 0.6.1
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