#vl = [40.08, 36.6, 41.0, 35.2, 41.0]
indices = []
for x in vl:
if x == max(vl):
indices.append(vl.index(x))
print(indices)
**Here max element 41 is present 2 times in the list at indexes 2 and 4. So, these indexes should be appended to the list indices. I am getting the output as [2,2] instead of [2,4]. Can Anyone please tell me what is wrong with this code? **
You get [2, 2] as index() is going to always give you the index of the first match.
I think you want to check out enumerate() here as it will give you the indices you are looking for in addition to the values.
Via List Comprehension:
vl = [40.08, 36.6, 41.0, 35.2, 41.0]
indices = [index for index, value in enumerate(vl) if value == max(vl)]
print(indices)
Via Traditional Loop:
vl = [40.08, 36.6, 41.0, 35.2, 41.0]
indices = []
for index, value in enumerate(vl):
if value == max(vl):
indices.append(index)
print(indices)
both should give you:
[2, 4]
Related
I am trying to solve the following problem:
Write a function solution(l) that takes a list of positive integers l and counts the number of "lucky triples" of (li, lj, lk) where the list indices meet the requirement i < j < k. The length of l is between 2 and 2000 inclusive. A "lucky triple" is a tuple (x, y, z) where x divides y and y divides z, such as (1, 2, 4). The elements of l are between 1 and 999999 inclusive. The solution fits within a signed 32-bit integer. Some of the lists are purposely generated without any access codes to throw off spies, so if no triples are found, return 0.
For example, [1, 2, 3, 4, 5, 6] has the triples: [1, 2, 4], [1, 2, 6], [1, 3, 6], making the solution 3 total.
My solution only passes the first two tests; I am trying to understand what it is wrong with my approach rather then the actual solution. Below is my function for reference:
def my_solution(l):
from itertools import combinations
if 2<len(l)<=2000:
l = list(combinations(l, 3))
l= [value for value in l if value[1]%value[0]==0 and value[2]%value[1]==0]
#l= [value for value in l if (value[1]/value[0]).is_integer() and (value[2]/value[1]).is_integer()]
if len(l)<0xffffffff:
l= len(l)
return l
else:
return 0
If you do nested iteration of the full list and remaining list, then compare the two items to check if they are divisors... the result counts as the beginning and middle numbers of a 'triple',
then on the second round it will calculate the third... All you need to do is track which ones pass the divisor test along the way.
For Example
def my_solution(l):
row1, row2 = [[0] * len(l) for i in range(2)] # Tracks which indices pass modulus
for i1, first in enumerate(l):
for i2 in range(i1+1, len(l)): # iterate the remaining portion of the list
middle = l[i2]
if not middle % first: # check for matches
row1[i2] += 1 # increment the index in the tracker lists..
row2[i1] += 1 # for each matching pair
result = sum([row1[i] * row2[i] for i in range(len(l))])
# the final answer will be the sum of the products for each pair of values.
return result
I have a tuple as follows s=[(1,300),(250,800),(900,1000),(1200,1300),(1500,2100)]
I need to compare the upper limit of the list with the lower limit of the next list. If the lower limit of the next list is less than the upper limit of the previous list than it should throw error else it should pass.
Example:
s=[(1,300),(250,800),(900,1000),(1200,1300),(1500,2100)] - This should throw error as 250<300.If it fails for any one, it should throw error immediately.
s=[(1,300),(350,800),(900,1000)] - This should not throw error as 350>300.
I have tried something like this:
s=[(1,300),(250,800),(900,1000)]
s= (sorted(s))
print(s)
def f(mytuple, currentelement):
return mytuple[mytuple.index(currentelement) + 1]
for i in s:
j = f(s,i)
if i[0]<j[1]:
print("fail")
else:
print("pass")
But it's not working. Help me out here.
zip() combines lists (or any iterables) to a new iterable. It stops when the shortest list is exhausted. Imagine:
a = [1, 2, 3, 4]
b = ['a', 'b', 'c']
zipped = zip(a, b) # Gives: [(1, 'a'), (2, 'b'), (3, 'c')]
# 4 is skipped, because there is no element remaining in b
We can used this to get all pairs in s in an elegant, easy to read form:
s=[(1,300),(250,800),(900,1000)]
s= (sorted(s))
pairs = zip(s, s[1:]) # zip s from index 0 with s from index 1
Now that we have pairs in the form of ((a0, a1), (b0, b1)) you can easily compare if a1 > b0 in a loop:
for a,b in pairs:
if a[1] > b[0]:
print("fail")
else:
print("pass")
Two problems I see:
1) You're running into an out of bounds error, as the last element (900,1000) is trying to check the follow element which does not exist.
You can skip the last element by adding [:-1] to your loop.
2) In addition, your "if" condition seems to be backwards. You seem to be wanting to compare i[1] with j[0] instead of i[0] with j[1].
s=[(1,300),(250,800),(900,1000)]
s= (sorted(s))
print(s)
def f(mytuple, currentelement):
return mytuple[mytuple.index(currentelement) + 1]
for i in s[:-1]:
j = f(s,i)
if i[1]>j[0]:
print("fail")
else:
print("pass")
See How to loop through all but the last item of a list? for more details.
I have a 2d array, how can I delete certain element(s) from it?
x = [[2,3,4,5,2],[5,3,6,7,9,2],[34,5,7],[2,46,7,4,36]]
for i in range(len(x)):
for j in range(len(x[i])):
if x[i][j] == 2:
del x[i][j]
This will destroy the array and returns error "list index out of range".
you can use pop on the list item. For example -
>>> array = [[1,2,3,4], [6,7,8,9]]
>>> array [1].pop(3)
>>> array
[[1, 2, 3, 4], [6, 7, 8]]
I think this can solve your problem.
x = [[2,3,4,5,2],[5,3,6,7,9,2],[34,5,7],[2,46,7,4,36]]
for i in range(len(x)):
for j in range(len(x[i])):
if j<len(x[i]):
if x[i][j] == 2:
del x[i][j]
I have tested it locally and working as expected.Hope it will help.
Mutating a list while iterating over it is always a bad idea. Just make a new list and add everything except those items you want to exclude. Such as:
x = [[2,3,4,5,2],[5,3,6,7,9,2],[34,5,7],[2,46,7,4,36]]
new_array = []
temp = []
delete_val = 2
for list_ in x:
for element in list_:
if element != delete_val:
temp.append(element)
new_array.append(temp)
temp = []
x = new_array
print(x)
Edit: made it a little more pythonic by omitting list indices.
I think this is more readable at the cost of temporarily more memory usage (making a new list) compared to the solution that Sai prateek has offered.
I have a list containing n integers. The ith element of the list a, a[i], can be swapped into any integer x such that 0 ≤ x ≤ a[i]. For example if a[i] is 3, it can take values 0, 1, 2, 3.
The task is to find all permutations of such list. For example, if the list is
my_list = [2,1,4]
then the possible permutations are:
[0,0,0], [0,0,1], ... [0,0,4],
[0,1,0], [0,1,1], ... [0,1,4],
[1,0,0], [1,0,1], ... [1,0,4],
[1,1,0], [1,1,1], ... [1,1,4],
[2,0,0], [2,0,1], ... [2,0,4],
[2,1,0], [2,1,1], ... [2,1,4]
How to find all such permutations?
you could use a comibation of range to get all the 'valid' values for each element of the list and itertools.product:
import itertools
my_list = [2,1,4]
# get a list of lists with all the possible values
plist = [list(range(y+1)) for y in my_list]
#
permutations = sorted(list(itertools.product(*plist)))
more on itertools product see e.g. here on SO or the docs.
Here's a solution:
my_list=[2,1,4]
def premutation_list(p_list):
the_number=int("".join(map(str,p_list)))
total_len=len(str(the_number))
a=[i for i in range(the_number)]
r_list=[]
for i in a:
if len(str(i))<total_len:
add_rate=total_len - len(str(i))
b="0,"*add_rate
b=b.split(",")
b=b[0:len(b)-1]
b.append(str(i))
r_list.append([int(y) for x in b for y in x ])
else:
r_list.append([int(x) for x in str(i)])
return r_list
print(premutation_list(my_list))
Explanation:
The basic idea is just getting all the numbers till the given number. For example till 4 there are 0,1,2,3, number.
I have achieved this first by converting the list into a integer.
Then getting all the numbers till the_number.
Try this. Let me know if I misunderstood your question
def permute(l,cnt,n):
if cnt==n:
print(l)
return
limit = l[cnt]
for i in range(limit+1):
l[cnt]=i
permute(l[:n],cnt+1,n)
l =[2,1,4]
permute(l,0,3)
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.