Reputation: 523
I have a text file which contains a log like this:
245 (click,view,view,check,view,view) (22,1,5,6,7,15)
305 (view,run) (5,6)
3051 (run,run) (115,36)
It is tab seperated, the number of entries in the second column field is equal to the third column field.
I am finding it difficult to take this into python using np.loadtxt as it has a delimiter and text and brackets (circular) to separate the 2nd fields and 3rd fields.
Looking forward for suggestions on how I should go about it?
Upvotes: 1
Views: 63
Reputation: 402
Perhaps it'd be best to parse it in some way with standard python first, before loading into numpy? Without knowing a lot about how numpy needs this to be formatted, below is an example to turn it into an array of arrays.
For instance you could use split()
.
Def MakeItAList(lineFromFile): list = split(lineFromFile, " ") list[1] = split(list[1][1:-1],",") list[2] = split(list[2][1:-1],",")
It's a bit clunky but it will turn 245 (click,view,view,check,view,view) (22,1,5,6,7,15)
. into something like [245, [click,view,view,check,view,view], [22,1,5,6,7,15]]
which is a little more manageable as a data-structure.
Upvotes: 2