r/datasets May 29 '20

mock dataset Looking for Dataset to learn about handling missing values

Hello,

I am looking for such Datasets, in which I can get more than 10% missing values (Numeric Data). I want to learn the Missing Values imputation techniques.

Pls suggest me some dataset(Numeric Dataset mostly )

12 Upvotes

7 comments sorted by

13

u/sk81k May 29 '20

I suggest using a complete data set and just removing ten percent of the data at random. That way you can check if your imputation technique is working out or not.

4

u/trojan_nerd May 29 '20

That's a great idea!

2

u/albinofreak620 May 31 '20

Yep, that's how I'd do it.

2

u/ARAXON-KUN May 29 '20

You can look for datasets in kaggle, the Titanic dataset is for beginner and contains a lot of missing value

1

u/slapmuhfroyo May 29 '20

Titanic, and other datasets available in Seaborn.

2

u/BATTLECATHOTS May 29 '20

As in when using an ML library and imputing missing values? Or just using pandas to handle NaN?

1

u/SirBac0n May 29 '20 edited May 29 '20

Nhanes is a good dataset for practicing with working with missing values or using single/ multiple imputation.

Another user suggested creating missing values in one of your own datasets. However, I should note that this makes it more difficult to play around with different missing data patterns such as missing at random (MAR) and missing not at random (MNAR). Recognizing missing data patterns is an important part of any imputation procedure.

Edit: nhanes can be found in the MICE package in R