Welcome to python-tide’s documentation!

python-tide is a Python library for time series data visualization and pipeline creation, with a focus on building data processing pipelines and analyzing data gaps.

GitHub Repository

The source code for python-tide is available on GitHub

Contents:

Features

Hierarchical column naming system (name__unit__bloc__sub_bloc)
Flexible data selection using tags
Configurable data processing pipelines
Advanced gap analysis and visualization
Interactive time series plotting with multiple y-axes
Integration with scikit-learn transformers

Quick Example

import pandas as pd
import numpy as np
from tide.plumbing import Plumber

# Create sample data
data = pd.DataFrame({
    "temp__°C__zone1": [20, 21, np.nan, 23],
    "humid__%HR__zone1": [50, 55, 60, np.nan]
}, index=pd.date_range("2023", freq="h", periods=4))

# Define pipeline
pipe_dict = {
    "pre_processing": {"°C": [["ReplaceThreshold", {"upper": 25}]]},
    "common": [["Interpolate", ["linear"]]]
}

# Create plumber and process data
plumber = Plumber(data, pipe_dict)
corrected = plumber.get_corrected_data()

# Analyze gaps
gaps = plumber.get_gaps_description()

# Plot data
fig = plumber.plot(plot_gaps=True)
fig.show()

Indices and tables