What is Time Series Decomposition? - Time Series Analysis in Python

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Decomposition is powerful to aid you in understanding your time series. In this video, we dive into how you can apply decomposition in Python. 📈

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Hi, I'm Egor! 👋 I am a Data Scientist with a master's in Physics currently living in London. I share data science tutorials, advice and general tech topics!

⏰ TIMESTAMPS
00:00 Intro
00:14 Python tutorial
00:38 Time series components
01:27 Additive vs multiplicative time series
03:55 Decomposition in Python
09:04 Recap
09:25 Outro

DISCLAIMERS
This content is for educational and entertainment purposes only and should not be considered as professional advice. Views and opinions are my own and do not represent or reflect the opinions of my current or past employer or any organisations I am associated with. This description also contains affiliate links from which I may receive a small commission from.
  1. Egor Howell
  2. data science
  3. time series
  4. python
  5. machine learning
  6. time series analysis
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Комментарии
Автор

thanks for posting on time series... I've been looking for good tutorials for the past two months, and your videos are actually what I was looking for

THANK YOU !

baharl
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Please make a machine learning crash course too! This was the exact thing I was looking over all across YouTube

KalpShah-sz
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Hey, quick question, not sure if you will mention it in the following videos of the series. In the previous videos you mentioned techniques to find whether data is stationary or not (by removing trend, seasonality, and even transforming the data with boxcox, log functions, etc). Now we are decomposing the "original" time series, but shouldn't we transform data first?

I mean, why should we run statistical tests for stationary data if the decomposition process doesn't use that? Is it related to assumptions? Can we only assume the time series decomposition models work if data is stationary?

And thanks for the content, mate! Really awesome and didatic

gustavogran-hotmart
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Thank you! Clear explanation and nice presentation

ОПривет-ъъ
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Nice. What if you have additive trend and multiplicative seasonality or vice versa, how would we decompose that? it would be tricky.

michalkiwanuka
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Glad to see the lighting is better than the first video but it's still too bright at the window's side.
Found you on medium, looking forward to seeing more.

yorailevi
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How do I apply for Data scientist jobs ? pov i am from India and interested to work abroad

KalpShah-sz