Thread by @daansan_ml

What is the difference between seasonality and cycle in Time Series? 🤔

🧵 👇

#Python #DataScience #MachineLearning

🔴Seasonality refers to regular patterns that occur at a specific frequency, often at a yearly, monthly or weekly interval.

For example:

• Retail sales tend to increase during the holiday season

• Electricity consumption tends to be higher in the summer months when people use air conditioning more often

🔴 Cycles, on the other hand, are trends that repeat not consistently, with different frequencies.

Generally, over a longer period.

For example, the stock market tends to follow a cycle of growth and decline over a number of years.

These are related to the business cycle, which is the up-and-down movements in economic activity that happen over a period of time.

▶️ TL;DR

Seasonality is a regular pattern that occurs at a specific time interval, while cycles are longer-term trends that repeat over a number of years.

Both seasonality and cycles can have an impact on time series forecasting.

We should take these factors into account when making predictions about future events.

Yesterday I talked about this in my latest article

👇👇👇👇

medium.com/@andressanchez…

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Thanks! 😉