How do I only keep the rows that match the values of the rows in a different list?

3 views (last 30 days)
Hi,
I have this large cell array (low_condition) that contains participant IDs in the first row. I have a second list of IDs (valid_IDs) that I would like to compare witht he cell array and then only keep those participant IDs that are found in the second list. All of the remaining IDs (rows) I want to have deleted. How do I do this?
Thanks

Answers (1)

Voss
Voss on 17 Jul 2022
load low_condition
load valid_low_IDs
valid_low_IDs contains character vectors that appear to be file names:
valid_low_IDs
valid_low_IDs = 17×1 cell array
{'5beeea64a79efb0001faf30a.csv' } {'5db9e0044a8eb40431d5e782.csv' } {'5e8ef2059eeb7a1af7502f3c - edited.csv'} {'5e67640d82b4784eb93f1a32.csv' } {'5ed5aeea88fecc14779b4a29 - edited.csv'} {'5f8998f6bfe9d6067c4b8a72.csv' } {'5fc959ba27fabf4111b918ec - edited.csv'} {'5ff0a3d22c2ee6fa5d47c312 - edited.csv'} {'59a9c0291b7a550001d6392e.csv' } {'60b43c11dcee60f547e013ba.csv' } {'60fdf891d19fd767ebc5eefc.csv' } {'598fa1b80675b100014dacf3.csv' } {'614e51ba8bd7590a59e92f9c.csv' } {'6019ec157baab31e1ad590fc.csv' } {'6079c41a26b231701ceb1e0a.csv' } {'6089aa8120d7418a70f3eba7.csv' } {'60243c357e64550d96eb47f6.csv' }
So the non-ID parts of those file names need to be removed. Here's one way:
IDs = strrep(strrep(valid_low_IDs,' - edited',''),'.csv','')
IDs = 17×1 cell array
{'5beeea64a79efb0001faf30a'} {'5db9e0044a8eb40431d5e782'} {'5e8ef2059eeb7a1af7502f3c'} {'5e67640d82b4784eb93f1a32'} {'5ed5aeea88fecc14779b4a29'} {'5f8998f6bfe9d6067c4b8a72'} {'5fc959ba27fabf4111b918ec'} {'5ff0a3d22c2ee6fa5d47c312'} {'59a9c0291b7a550001d6392e'} {'60b43c11dcee60f547e013ba'} {'60fdf891d19fd767ebc5eefc'} {'598fa1b80675b100014dacf3'} {'614e51ba8bd7590a59e92f9c'} {'6019ec157baab31e1ad590fc'} {'6079c41a26b231701ceb1e0a'} {'6089aa8120d7418a70f3eba7'} {'60243c357e64550d96eb47f6'}
On the other hand, low_condition(:,1) is a cell array of (scalar) string arrays:
disp(low_condition(:,1))
{["59a9c0291b7a550001d6392e" ]} {["60243c357e64550d96eb47f6" ]} {["6019ec157baab31e1ad590fc" ]} {["614e51ba8bd7590a59e92f9c" ]} {["60fdf891d19fd767ebc5eefc" ]} {["5beeea64a79efb0001faf30a" ]} {["5fc959ba27fabf4111b918ec" ]} {["6079c41a26b231701ceb1e0a" ]} {["5d6069f53f69fd0001c0e77f" ]} {["6033acf84fec17043ffef374" ]} {["5efd8bbe8f20d51cd2ab9327" ]} {["608d4e91d08ff4d32dbba3ad" ]} {["60b43c11dcee60f547e013ba" ]} {["615d8b5b98addf4b3d65c41d" ]} {["5ff0a3d22c2ee6fa5d47c312" ]} {["60cef6bc855784dee78ffffd" ]} {["6089aa8120d7418a70f3eba7" ]} {["5c6400cbcb937d00012d8866" ]} {["611cf405ca55c42b27807c3c" ]} {["60b65dd419636fbf792d4470" ]} {["5db9e0044a8eb40431d5e782" ]} {["5dc32687547c1f24648b7c23" ]} {["61742bd3cd78a9f853168cef" ]} {["615c343a80f9bb6fd7362271" ]} {["615db68d9d021708b6e64603" ]} {["5e67640d82b4784eb93f1a32" ]} {["5f8998f6bfe9d6067c4b8a72" ]} {["60ac8807aaad354f950dd131" ]} {["608ac09acb49bef04cade936" ]} {["https://we.tl/t-eeVxbz35Vq?src=dnl"]} {["5e83b43765a5720e30b71b37" ]} {["5ed5aeea88fecc14779b4a29" ]} {["5d175bfe7a5f6d001a64b545" ]} {["598fa1b80675b100014dacf3" ]} {["5aa67d76f053610001726e65" ]} {["61133a6bb907d515d390d08b" ]} {["5e8ef2059eeb7a1af7502f3c" ]} {["" ]}
Convert it to a cell array of character vectors, stored here as cond:
cond = cellstr(low_condition(:,1));
disp(cond)
{'59a9c0291b7a550001d6392e' } {'60243c357e64550d96eb47f6' } {'6019ec157baab31e1ad590fc' } {'614e51ba8bd7590a59e92f9c' } {'60fdf891d19fd767ebc5eefc' } {'5beeea64a79efb0001faf30a' } {'5fc959ba27fabf4111b918ec' } {'6079c41a26b231701ceb1e0a' } {'5d6069f53f69fd0001c0e77f' } {'6033acf84fec17043ffef374' } {'5efd8bbe8f20d51cd2ab9327' } {'608d4e91d08ff4d32dbba3ad' } {'60b43c11dcee60f547e013ba' } {'615d8b5b98addf4b3d65c41d' } {'5ff0a3d22c2ee6fa5d47c312' } {'60cef6bc855784dee78ffffd' } {'6089aa8120d7418a70f3eba7' } {'5c6400cbcb937d00012d8866' } {'611cf405ca55c42b27807c3c' } {'60b65dd419636fbf792d4470' } {'5db9e0044a8eb40431d5e782' } {'5dc32687547c1f24648b7c23' } {'61742bd3cd78a9f853168cef' } {'615c343a80f9bb6fd7362271' } {'615db68d9d021708b6e64603' } {'5e67640d82b4784eb93f1a32' } {'5f8998f6bfe9d6067c4b8a72' } {'60ac8807aaad354f950dd131' } {'608ac09acb49bef04cade936' } {'https://we.tl/t-eeVxbz35Vq?src=dnl'} {'5e83b43765a5720e30b71b37' } {'5ed5aeea88fecc14779b4a29' } {'5d175bfe7a5f6d001a64b545' } {'598fa1b80675b100014dacf3' } {'5aa67d76f053610001726e65' } {'61133a6bb907d515d390d08b' } {'5e8ef2059eeb7a1af7502f3c' } {0×0 char }
Now you can compare the two using ismember, and keep the relevant rows of low_condition:
to_keep = ismember(cond,IDs);
low_condition_keep = low_condition(to_keep,:)
low_condition_keep = 17×49 cell array
{["59a9c0291b7a550001d6392e"]} {[2]} {[4]} {[3]} {[3]} {[4]} {[5]} {[5]} {[4]} {[4]} {[5]} {[5]} {[4]} {[5]} {[4]} {[5]} {[4]} {[3]} {[4]} {[4]} {[5]} {[4]} {[4]} {[3]} {[4]} {[4]} {[4]} {[5]} {[4]} {[2]} {[2]} {[3]} {[2]} {[4]} {[3]} {[4]} {[4]} {[2]} {[4]} {[3]} {[2]} {[4]} {[3]} {[4]} {[5]} {[4]} {[2]} {[4]} {[4]} {["60243c357e64550d96eb47f6"]} {[2]} {[1]} {[4]} {[4]} {[1]} {[5]} {[1]} {[4]} {[4]} {[4]} {[4]} {[3]} {[4]} {[4]} {[3]} {[2]} {[2]} {[4]} {[4]} {[3]} {[4]} {[2]} {[4]} {[4]} {[5]} {[4]} {[4]} {[4]} {[1]} {[2]} {[2]} {[5]} {[5]} {[4]} {[3]} {[4]} {[2]} {[5]} {[4]} {[4]} {[2]} {[4]} {[5]} {[5]} {[4]} {[2]} {[3]} {[5]} {["6019ec157baab31e1ad590fc"]} {[2]} {[3]} {[1]} {[3]} {[3]} {[5]} {[5]} {[4]} {[4]} {[5]} {[5]} {[3]} {[3]} {[3]} {[5]} {[4]} {[1]} {[4]} {[4]} {[5]} {[1]} {[2]} {[2]} {[3]} {[5]} {[3]} {[5]} {[5]} {[1]} {[2]} {[3]} {[3]} {[5]} {[1]} {[4]} {[4]} {[2]} {[5]} {[2]} {[2]} {[5]} {[5]} {[5]} {[3]} {[4]} {[1]} {[4]} {[5]} {["614e51ba8bd7590a59e92f9c"]} {[2]} {[2]} 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