Counting all NaN for each variable in the table

I have wind and wave data, (9 columns), I would like to have the NaN for each column and then plot the clean data with all the indicated missing values for each column

Answer 1

[MULI]

Hi @Mouhammad Jomaa Alkaseam,

To handle and visualize missing data in your wind and wave data set, you can follow these steps:

• The first step is identifying where the missing values (NaNs) in your dataset. The "ismissing" function scans your table and identifies any NaN or undefined values. You can refer to this documentation for details on its usage: https://www.mathworks.com/help/matlab/ref/ismissing.html
• To clean the data, use the "fillmissing" function. You can choose how to fill these missing values depending on the context of your data. You can refer to this documentation for usage of this function. https://www.mathworks.com/help/matlab/ref/fillmissing.html
• For time-series data like wind and wave measurements, "interpolation" or "forward fill" are often suitable.
• Plot the original data, cleaned data, and highlight the missing values.

For more details, you can refer to this documentation on cleaning messy and missing data in tables: https://www.mathworks.com/help/matlab/matlab_prog/clean-messy-and-missing-data-in-tables.html