Answers.Body: <p>As you are handling with time series data and you want to find trends; A good approach should be consider applying <a href="https://otexts.com/fpp2/holt-winters.html" rel="nofollow noreferrer">Holt-Winter's seasonal method</a>. This algorithm handle seasonal, trend and smooth parameters. A good implementation of this kind of algorithm is <a href="https://facebook.github.io/prophet/docs/quick_start.html#r-api" rel="nofollow noreferrer">Prophet by Facebook</a>. You can code an exploratory analysis with this library and obtain trend, yearly seasonality, and weekly seasonality of the time series, among other components. Example:</p>
  
  <p><a href="https://i.sstatic.net/pDyOB.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/pDyOB.png" alt="enter image description here"></a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-08-30T18:23:24.510Z
Answers.LastActivityDate: 2019-08-30T18:23:24.510Z
Answers.UserDisplayName: Bitzel
Body: <p>I have a very big table with lots of names and how much they are searched by date. </p>
  
  <p>I would like to find trending patterns. When does a name rise and when does it fall. Without knowing the name or the pattern before.
  The rise could be during the seasons of the year but also during a week.</p>
  
  <p>Like a 'warm hat' is trending in winter and falling in summer.
  Or searches for a "board game" might rise on Sunday and decrease on Monday.</p>
  
  <p>The table looks simplified like this:</p>
  
  <pre><code>winter gloves, 2014-01-01, 200
  warm hat, 2014-01-01, 300
  swimming short, 2014-01-01, 1
  sunscreen, 2014-01-01, 2
  ....
  winter gloves, 2014-07-01, 1
  warm hat, 2014-07-01, 1
  swimming short, 2014-07-01, 200
  sunscreen, 2014-07-01, 300
  </code></pre>
  
  <p>Which algorithms should I have a look at? </p>
  
  <p>Thanks for any hint,
  Joerg</p>
  
Tags: <data-mining>
Title: Algorithm for seasonal trends
UserDisplayName: JoergP
ThreadText: # Algorithm for seasonal trends
  
  (Asked by: username_0 on 2019-08-29)
  
  I have a very big table with lots of names and how much they are searched by date.
  
  I would like to find trending patterns. When does a name rise and when does it fall. Without knowing the name or the pattern before.
  The rise could be during the seasons of the year but also during a week.
  
  Like a 'warm hat' is trending in winter and falling in summer.
  Or searches for a "board game" might rise on Sunday and decrease on Monday.
  
  The table looks simplified like this:
  
  ```
  winter gloves, 2014-01-01, 200
  warm hat, 2014-01-01, 300
  swimming short, 2014-01-01, 1
  sunscreen, 2014-01-01, 2
  ....
  winter gloves, 2014-07-01, 1
  warm hat, 2014-07-01, 1
  swimming short, 2014-07-01, 200
  sunscreen, 2014-07-01, 300
  
  ```
  
  Which algorithms should I have a look at?
  
  Thanks for any hint,
  Joerg
  
  **Tags:** data-mining
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2019-08-30. Score: 1
  
  As you are handling with time series data and you want to find trends; A good approach should be consider applying [Holt-Winter's seasonal method](https://otexts.com/fpp2/holt-winters.html). This algorithm handle seasonal, trend and smooth parameters. A good implementation of this kind of algorithm is [Prophet by Facebook](https://facebook.github.io/prophet/docs/quick_start.html#r-api). You can code an exploratory analysis with this library and obtain trend, yearly seasonality, and weekly seasonality of the time series, among other components. Example:
  
  [![enter image description here](https://i.sstatic.net/pDyOB.png)](https://i.sstatic.net/pDyOB.png)
  
  
  ---
  
  