Reading certain lines from a file in python without loading it in memory
to read certain rows from csv file use skiprows argument of pandas.read_csv function:

skiprows list-like, int or callable, optional
Line numbers to skip
(0-indexed) or number of lines to skip (int) at the start of the file.
If callable, the callable function will be evaluated against the row
indices, returning True if the row should be skipped and False
otherwise. An example of a valid callable argument would be lambda x: x in [0, 2].
I have a large csv file (90000 rows, 20000 columns). I want to read certain rows from it in Python using an index list. But i don't want to load the entire file using something like "read_csv" as this will fill up my memory and the program will crash. IS there any way to do it without loading the entire file?
I am open to changing the format of the input file(.csv) if that will help my case.