[Tutor] How to create a dictionary for ount elements

[Peter Otten]

jarod_v6 at libero.it wrote:

> Dear all thanks for your suggestion!!!
> Thanks to your suggestion I create this structure:with open("prova.csv")
> as p:
>     for i in p:
>         lines =i.rstrip("\n").split("\t")
>    ...:         print lines
>    ...:
> ['programs ', 'sample', 'gene', 'values']
> ['program1', 'sample1', 'TP53', '2']
> ['program1', 'sample1', 'TP53', '3']
> ['program1', 'sample2', 'PRNP', '4']
> ['program1', 'sample2', 'ATF3', '3']
> ['program2', 'sample1', 'TP53', '2']
> ['program2', 'sample1', 'PRNP', '5']
> ['program2', 'sample2', 'TRIM32', '4']
> ['program2', 'sample2', 'TLK1', '4']
> 
> In [4]: with open("prova.csv") as p:
>     for i in p:
>         lines =i.rstrip("\n").split("\t")
>         dizlines
> diz
> 
> In [4]: with open("prova.csv") as p:
>     for i in p:
>         lines =i.rstrip("\n").split("\t")
>         line = (lines[0],lines[1])
>    ...:         diz.setdefault(line,set()).add(lines[2])
>    ...:
> 
> In [5]: diz
> Out[5]:
> {('program1', 'sample1'): {'TP53'},
>  ('program1', 'sample2'): {'ATF3', 'PRNP'},
>  ('program2', 'sample1'): {'PRNP', 'TP53'},
>  ('program2', 'sample2'): {'TLK1', 'TRIM32'},
>  ('programs ', 'sample'): {'gene'}}
> 
> 
> So what I want to do is to use intersect between the keys recursively:
> s = diz[('program2', 'sample1']
>    ....:
>    ....:
> KeyboardInterrupt
> 
> In [14]: s = diz[('program2', 'sample1')]
> 
> In [15]: s
> Out[15]: {'PRNP', 'TP53'}
> 
> In [16]: a
> Out[16]: {'ATF3', 'PRNP'}
> 
> In [17]: s.inte
> s.intersection         s.intersection_update
> 
> In [17]: s.intersection(a)
> Out[17]: {'PRNP'}
> 
> How can Have a intersect of all my dictionary and from ('program1',
> 'sample1') vs ('program1', 'sample2')...
> I want to count  how many genes are common
> Thanks in advance  for your help!

For that you have to map genes to program/sample pairs -- or just count them 
as already suggested:

>>> import csv
>>> from collections import Counter
>>> with open("prova.csv") as f:
...     rows = csv.DictReader(f, delimiter="\t")
...     freq = Counter(row["gene"] for row in rows)
... 
>>> freq.most_common(2)
[('TP53', 3), ('PRNP', 2)]