I have written a function which return a list of elements which occur only once in a given list and it is working as expected but this is not what I want is there any built-in function or other method which do same functionalities without iterating:
def unique_items(ls):
return [item for item in ls if ls.count(item)==1]
print(unique_items([1,1,1,2,3,2,4,5,4]))
>>> from collections import Counter
>>> a = [1,2,3,4,5,1,2]
>>> c = Counter(a)
>>> c
Counter({1: 2, 2: 2, 3: 1, 4: 1, 5: 1})
>>> [k for k, v in c.items() if v == 1]
[3, 4, 5]
If you don't want to use an explicit loop, you can use filter:
def unique_items(ls):
return list(filter(lambda s : ls.count(s) == 1, ls))
print(unique_items([1,1,1,2,3,2,4,5,4]))
Output:
[3, 5]
Comparing some options mentioned here:
def func_1(ls):
return [
item
for item in ls
if ls.count(item) == 1]
def func_2(ls):
c = collections.Counter(ls)
return [
k
for k, v in c.items()
if v == 1]
Comparisson code:
import timeit
a_1 = [1,1,1,2,3,2,4,5,4]
a_2 = [1,1,1,2,3,2,4,5,4] * 100
for f in [func_1, func_2]:
print(f.__name__)
print(
'short list',
timeit.timeit(
'f(a)',
'from __main__ import {} as f, a_1 as a'.format(f.__name__),
number=100))
print(
'long list ',
timeit.timeit(
'f(a)',
'from __main__ import {} as f, a_2 as a'.format(f.__name__),
number=100))
Results:
func_1
short list 0.00014933500006009126
long list 0.5417057829999976
func_2
short list 0.0005539439998756279
long list 0.0029211379996922915
So far, func_2 is faster for large inputs and func_1 is slightly faster for very short inputs.
Related
If I have:
x = np.array(([1,4], [2,5], [2,6], [3,4], [3,6], [3,7], [4,3], [4,5], [5,2]))
for item in range(3):
choice = random.choice(x)
How can I get the index number of the random choice taken from the array?
I tried:
indexNum = np.where(x == choice)
print(indexNum[0])
But it didn't work.
I want the output, for example, to be something like:
chosenIndices = [1 5 8]
Another possibility is using np.where and np.intersect1d. Here random choice without repetition.
x = np.array(([1,4], [2,5], [2,6], [3,4], [3,6], [3,7], [4,3], [4,5], [5,2]))
res=[]
cont = 0
while cont<3:
choice = random.choice(x)
ind = np.intersect1d(np.where(choice[0]==x[:,0]),np.where(choice[1]==x[:,1]))[0]
if ind not in res:
res.append(ind)
cont+=1
print (res)
# Output [8, 1, 5]
You can achieve this by converting the numpy array to list of tuples and then apply the index function.
This would work:
import random
import numpy as np
chosenIndices = []
x = np.array(([1,4], [2,5], [2,6], [3,4], [3,6], [3,7], [4,3], [4,5], [5,2]))
x = x.T
x = list(zip(x[0],x[1]))
item = 0
while len(chosenIndices)!=3:
choice = random.choice(x)
indexNum = x.index(choice)
if indexNum in chosenIndices: # if index already exist, then it will rerun that particular iteration again.
item-=1
else:
chosenIndices.append(indexNum)
print(chosenIndices) # Thus all different results.
Output:
[1, 3, 2]
When I run this code it returns that the numpy.ndarray object has no attributes. I'm trying to write a function that in case the number given is in the array will return with the position of that number in the array.
a = np.c_[np.array([1, 2, 3, 4, 5])]
x = int(input('Type a number'))
def findelement(x, a):
if x in a:
print (a.index(x))
else:
print (-1)
print(findelement(x, a))
Please use np.where instead of list.index.
import numpy as np
a = np.c_[np.array([1, 2, 3, 4, 5])]
x = int(input('Type a number: '))
def findelement(x, a):
if x in a:
print(np.where(a == x)[0][0])
else:
print(-1)
print(findelement(x, a))
Result:
Type a number: 3
2
None
Note np.where returns the indices of elements in an input array where
the given condition is satisfied.
You should check out np.where and np.argwhere.
I am having list which as follows
input_list= [2, 3, 5, 2, 5, 1, 5]
I want to get all the indexes of maximum value. Need efficient solution. The output will be as follows.
output = [2,4,6] (The above list 5 is maximum value in a list)
I have tried by using below code
m = max(input_list)
output = [i for i, j in enumerate(a) if j == m]
I need to find any other optimum solution.
from collections import defaultdict
dic=defaultdict(list)
input_list=[]
for i in range(len(input_list)):
dic[input_list[i]]+=[i]
max_value = max(input_list)
Sol = dic[max_value]
You can use numpy (numpy arrays are very fast):
import numpy as np
input_list= np.array([2, 3, 5, 2, 5, 1, 5])
i, = np.where(input_list == np.max(input_list))
print(i)
Output:
[2 4 6]
Here's the approach which is described in comments. Even if you use some library, fundamentally you need to traverse at least once to solve this problem (considering input list is unsorted). So even lower bound for the algorithm would be Omega(size_of_list). If list is sorted we can leverage binary_search to solve the problem.
def max_indexes(l):
try:
assert l != []
max_element = l[0]
indexes = [0]
for index, element in enumerate(l[1:]):
if element > max_element:
max_element = element
indexes = [index + 1]
elif element == max_element:
indexes.append(index + 1)
return indexes
except AssertionError:
print ('input_list in empty')
Use a for loop for O(n) and iterating just once over the list resolution:
from itertools import islice
input_list= [2, 3, 5, 2, 5, 1, 5]
def max_indexes(l):
max_item = input_list[0]
indexes = [0]
for i, item in enumerate(islice(l, 1, None), 1):
if item < max_item:
continue
elif item > max_item:
max_item = item
indexes = [i]
elif item == max_item:
indexes.append(i)
return indexes
Here you have the live example
Think of it in this way, unless you iterate through the whole list once, which is O(n), n being the length of the list, you won't be able to compare the maximum with all values in the list, so the best you can do is O(n), which you already seems to be doing in your example.
So I am not sure you can do it faster than O(n) with the list approach.
I am trying to write a function to extract only words unique to each key and list them in a dictionary output like {"key1": "unique words", "key2": "unique words", ... }. I start out with a dictionary. To test with I created a simple dictionary:
d = {1:["one", "two", "three"], 2:["two", "four",
"five"], 3:["one","four", "six"]}
My output should be:
{1:"three",
2:"five",
3:"six"}
I am thinking maybe split in to separate lists
def return_unique(dct):
Klist = list(dct.keys())
Vlist = list(dct.values())
aList = []
for i in range(len(Vlist)):
for j in Vlist[i]:
if
What I'm stuck on is how do I tell Python to do this: if Vlist[i][j] is not in the rest of Vlist then aList.append(Vlist[i][j]).
Thank you.
You can try something like this:
def return_unique(data):
all_values = []
for i in data.values(): # Get all values
all_values = all_values + i
unique_values = set([x for x in all_values if all_values.count(x) == 1]) # Values which are not duplicated
for key, value in data.items(): # For Python 3.x ( For Python 2.x -> data.iteritems())
for item in value: # Comparing values of two lists
for item1 in unique_values:
if item == item1:
data[key] = item
return data
d = {1:["one", "two", "three"], 2:["two", "four", "five"], 3:["one","four", "six"]}
print (return_unique(d))
result >> {1: 'three', 2: 'five', 3: 'six'}
Since a key may have more than one unique word associated with it, it makes sense for the values in the new dictionary to be a container type object to hold the unique words.
The set difference operator returns the difference between 2 sets:
>>> a = set([1, 2, 3])
>>> b = set([2, 4, 6])
>>> a - b
{1, 3}
We can use this to get the values unique to each key. Packaging these into a simple function yields:
def unique_words_dict(data):
res = {}
values = []
for k in data:
for g in data:
if g != k:
values += data[g]
res[k] = set(data[k]) - set(values)
values = []
return res
>>> d = {1:["one", "two", "three"],
2:["two", "four", "five"],
3:["one","four", "six"]}
>>> unique_words_dict(d)
{1: {'three'}, 2: {'five'}, 3: {'six'}}
If you only had to do this once, then you might be interested in the less efficeint but more consice dictionary comprehension:
>>> from functools import reduce
>>> {k: set(d[k]) - set(reduce(lambda a, b: a+b, [d[g] for g in d if g!=k], [])) for k in d}
{1: {'three'}, 2: {'five'}, 3: {'six'}}
In my program, when a user inputs a word, it needs to be checked for letters that are the same.
For example, in string = "hello", hello has 2 'l's. How can i check for this in a python program?
Use a Counter object to count characters, returning those that have counts over 1.
from collections import Counter
def get_duplicates(string):
c = Counter(string)
return [(k, v) for k, v in c.items() if v > 1]
In [482]: get_duplicates('hello')
Out[482]: [('l', 2)]
In [483]: get_duplicates('helloooo')
Out[483]: [('l', 2), ('o', 4)]
You can accomplish this with
d = defaultdict(int)
def get_dupl(some_string):
# iterate over characters is some_string
for item in some_string:
d[item] += 1
# select all characters with count > 1
return dict(filter(lambda x: x[1]>1, d.items()))
print(get_dupl('hellooooo'))
which yields
{'l': 2, 'o': 5}