Find Outliers with Python- 4 Simple Ways
Learn how to use traditional IQR and leverage algorithms to identify anomalies and outliers in your data. In this tutorial, we will be using Isolation Forest, Local Outlier Factor, and Elliptic Envelope to find outliers with just a few lines of code. Ultimately, we will build a function that we can easily apply to other datasets when needed.
Find the notebook here:
github.com/Gaelim/youtube/blo...
Find the dataset here:
github.com/Gaelim/youtube/blo...
#outliers
#python
#dataanalysis
#datascience
Пікірлер: 10
I notice you have been active last few days in uploading good videos, specially projects specific. You will soon have a gret numbers in subscribers, view counts, and success. Keep going.
@absentdata
2 жыл бұрын
Yes, I am definitely trying to build the channel with more content. I hope I'll get new subs. Thanks!!!
Great video thank you!
@absentdata
Жыл бұрын
Glad you liked it!
Exellent video sir
I tried this code with one of my dataset it gave ValueError: Expected a 1D array, got an array with shape (36, 7) when I executed the traditional_outlier function how to solve that
It appears that you did it by the column, can you do it by rows?
@absentdata
Жыл бұрын
Not sure about your approach. Most database would have a column of data that represent a single variable. Do you mean you would like to identify the row that has an outlier?
Sir In this video you just detect the outliers..why didn't you remove them??
@absentdata
2 жыл бұрын
It depends on your use case. For example, you might want to match those outlier with specific events so in that case they would remain. However, if you have a instrument that was not working properly which created outlier values, then you might want to remove them in that case.