Investigate why data is missing? After finding out reasons, what should I do next? x1 x2 x3 x4 - - - - - - x10 .... x21 x22 x23
 1                                           |
 .         Complete                          |       
 .           data                            |
 88                                          |
 89                                          |
 90 ------------------------------------------
 .          |              |
 .complete  |   missing    |  complete
 .          |              |
 .          |              |
 . -------------------------------------------
 100
 101           Complete data
 102------------------------------------------


The dataset looks like this. 10 % of the data is missing. It doesn't appear missing at random.

From row 90 to 99. Variables x4 to x10 are missing. All other rows do not have any missing values. It is not missing at random. Is there any statistical way to investigate why they are missing. 

My initial plan is to create a new column, 0 is not missing, 1 is missing.
Run a logistic regression on non-missing columns. Is this the correct way to do it or not? 

 My questions:
     How should I investigate why data is missing by just playing around with the data set?

     If I found out the reasons or data is not missing not random, What should I do next?
Add the binary column but start with summary statistics by group (missing/not missing) for all of the x’s. That may reveal an implied ‘why’, eg the values are missing whenever some other x is always above/below some value.