I am sure this is silly, but I simply cannot get around it. I have a dictionary, like this, with unequal number of values for each key:
'John greased ': ['axle', 'wheel', 'wheels', 'wheel', 'engine', ''],
'Paul alleged ': ['truth', 'crime', 'facts', 'infidelity', 'incident', ''],
'Tracy freed ': ['animals', 'fish', 'slaves', 'slaves', 'slaves', 'pizza'],
'Lisa plowed ': ['field', 'field', '', '', '', ''],
I want to know how many values there are for each key, not each unique value but how many tokens there are per key, repeated or not. So I would have a result like:
John greased 5
Paul alleged 5
Tracy freed 6
Lisa plowed 2
I was trying to use this to work it out using the code bellow:
for key, value in sorted(result.items()):
print(key, len(value))
But because of the missing values all the lengths turn out to be the same. Any ideas on how to solve this or where to find it out? Thanks a lot for any help.
One way to solve this, is by changing your last line:
print(key, len([item for item in value if item]))
So your complete code:
ITEMS = {
'John greased ': ['axle', 'wheel', 'wheels', 'wheel', 'engine', ''],
'Paul alleged ': ['truth', 'crime', 'facts', 'infidelity', 'incident', ''],
'Tracy freed ': ['animals', 'fish', 'slaves', 'slaves', 'slaves', 'pizza'],
'Lisa plowed ': ['field', 'field', '', '', '', ''],
}
for key, value in ITEMS.items():
#print value
print(key, len([item for item in value if item]))
You can also use filter
with bool
:
print(key, len(filter(bool, value)))
So, the loop:
for key, value in ITEMS.items():
#print value
print(key, len(filter(bool, value)))
You need to apply list
over filter
like so print(key, len(list(filter(bool, value))))
in Python 3.
Use filter
with None
, it filters out all falsy values from the iterable passed to it.
In Python3 filter
returns an iterator so you should call list()
on it.:
>>> lis = ['field', 'field', '', '', '', '']
>>> list(filter(None, lis))
['field', 'field']
>>> len(list(filter(None, lis)))
2
Code:
>>> my_dict = {
'John greased ': ['axle', 'wheel', 'wheels', 'wheel', 'engine', ''],
'Paul alleged ': ['truth', 'crime', 'facts', 'infidelity', 'incident', ''],
'Tracy freed ': ['animals', 'fish', 'slaves', 'slaves', 'slaves', 'pizza'],
'Lisa plowed ': ['field', 'field', '', '', '', ''],
}
for k,v in my_dict.items():
print (k, len(list(filter(None, v))))
...
Paul alleged 5
Lisa plowed 2
John greased 5
Tracy freed 6
Timing comparision between filter(None,..)
and list comprehension:
>>> lis = ['field', 'field', '', '', '', '']*100
>>> %timeit list(filter(None, lis))
10000 loops, best of 3: 22.2 us per loop
>>> %timeit [item for item in lis if item]
10000 loops, best of 3: 53.1 us per loop
>>> lis = ['field', 'field', '', '', '', '']*10000
>>> %timeit list(filter(None, lis))
100 loops, best of 3: 2.36 ms per loop
>>> %timeit [item for item in lis if item]
100 loops, best of 3: 5.22 ms per loop
Look at this:
>>> dct = {'John greased ': ['axle', 'wheel', 'wheels', 'wheel', 'engine', ''],
... 'Paul alleged ': ['truth', 'crime', 'facts', 'infidelity', 'incident', ''],
... 'Tracy freed ': ['animals', 'fish', 'slaves', 'slaves', 'slaves', 'pizza'],
... 'Lisa plowed ': ['field', 'field', '', '', '', '']}
>>>
>>> {k:sum(1 for x in v if x) for k,v in dct.items()}
{'Paul alleged ': 5, 'Lisa plowed ': 2, 'John greased ': 5, 'Tracy freed ': 6}
>>>
>>> for key,value in dct.items():
... print(key, sum(1 for v in value if v))
...
Paul alleged 5
Lisa plowed 2
John greased 5
Tracy freed 6
>>>
data = {
'John greased ': ['axle', 'wheel', 'wheels', 'wheel', 'engine', ''],
'Paul alleged ': ['truth', 'crime', 'facts', 'infidelity', 'incident', ''],
'Tracy freed ': ['animals', 'fish', 'slaves', 'slaves', 'slaves', 'pizza'],
'Lisa plowed ': ['field', 'field', '', '', '', '']
}
for each in data:
i = 0
print each
for item in data[each]:
if len(item) > 0:
i =i +1
print i
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