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