pytrendy 1.1.11

Trend Detection in Python. Applicable for real-world industry use cases in time series.

PyTrendy

PyTrendy is a robust solution for identifying and analyzing trends in time series. Unlike other trend detection packages, it is robust to noisy & flat segments, and handles for gradual & abrupt trend cases with a high precision. It aims to be the best package for trend detection in python.

Features

Quickstart

Install the package from PyPi.

pip install pytrendy

Import pytrendy, and apply trend detection on daily time series data.

import pytrendy as pt
df = pt.load_data('series_synthetic')
results = pt.detect_trends(df, date_col='date', value_col='gradual', plot=True)
results.print_summary()

Detected: 
- 3 Uptrends. 
- 3 Downtrends.
- 3 Flats.
- 0 Noise.

The best detected trend is Down between dates 2025-05-09 - 2025-06-17

Full Results:
-------------------------------------------------------------------------------
            direction       start         end  days  total_change  change_rank
time_index                                                                   
1                 Up  2025-01-02  2025-01-24    22     14.013348            5
2               Down  2025-01-25  2025-02-05    11    -13.564214            6
3               Flat  2025-02-06  2025-02-09     3           NaN            7
4                 Up  2025-02-10  2025-03-14    32     24.632035            3
5               Flat  2025-03-15  2025-03-17     2           NaN            8
6               Down  2025-03-18  2025-04-01    14    -22.721861            4
7                 Up  2025-04-02  2025-05-08    36     72.611833            2
8               Down  2025-05-09  2025-06-17    39    -73.253968            1
9               Flat  2025-06-18  2025-06-30    12           NaN            9 
-------------------------------------------------------------------------------

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Read more in the full documentation: russellsb.github.io/pytrendy/main