For time series analysis, everyone’s talking about ARIMA or Holt-Winters. But there’s other models which could also break down a seasonal series into trend, seasonality and noise. We will use an open source Python library called Seasonal to analyse B2B worldwide travel data.

1. Time Series
Analysis with
Seasonal Data
Case study by Cheuk Ting Ho
@cheukting_ho
https://github.com/Cheukting
@pydataamsterdam

2. Cheuk Tink Ho
@cheukting_ho
Data scientist at
Contributor ofMember of
Organizer of
● Base in London
● Love Python
● Love Comedy
● Love Beer & Cheese
● Love Travel

4. Time Series:
- Sequential data: order matters
- Upsample, Downsample: by day, by week,
by month
- Pandas Datatime index
@pydataamsterdam
@cheukting_ho

5. Seasonal Data:
- Repeating pattern
- Cycle could be week, month or day
- Compare data at the same point in the
cycle
@pydataamsterdam
@cheukting_ho

6. Example -
AirPassenger Dataset
The number of passengers shows a
pattern of:
- Trend
- Seasonality
- Noise
Across time
@cheukting_ho
@pydataamsterdam

7. What can we do to
combat seasonality in
travel data?

8. Wholesale in Travel
- Clients may be closed for business
during public holidays
- Sales are different weekday / weekend
(seasonal)
- Business worldwide
- Estimate impact from public holiday
worldwide
@cheukting_ho
@pydataamsterdam

9. Workflow:
➔ Break data in different countries, for
each country:
➔ De-seasonal and de-trend the time
series
➔ Find the residual that goes beyond
the LCL (for holiday CY) / UCL (for
holiday LY)
➔ Match holidays in the country form
calendar to the residual
➔ Calculate impact (residual - LCL)
@cheukting_ho
@pydataamsterdam

10. Python library - seasonal
- Linear trend fitting with periodic data can be hazardous
- Apply a filter to knock down variations at the maximum expected period
- Seasonal offsets (same as Holt-Winters) for a given periodicity are
estimated as period-over-period averages using all the provided data
- Estimating the period using a time-domain approach that accommodates
any periodic signal shape
- Drawback: computationally expensive (O(n^2))
https://github.com/welch/seasonal
@pydataamsterdam
@cheukting_ho

11. holiday?

12. Google Calendar API
Allows us to scrap all holiday in all countries as a
record, LY and CY holidays are compare on the
same weekday.
@pydataamsterdam
@cheukting_ho

13. Christmas

14. Chinese New Year