I want to make my algorithm more efficient via deleting the items it already sorted, but i don't know how I can do it efficiently. The only way I found was to rewrite the whole list.
l = [] #Here you put your list
sl = [] # this is to store the list when it is sorted
a = 0 # variable to store which numbers he already looked for
while True: # loop
if len(sl) == len(l): #if their size is matching it will stop
print(sl) # print the sorted list
break
a = a + 1
if a in l: # check if it is in list
sl.append(a) # add to sorted list
#here i want it to be deleted from the list.
The variable a is a little awkward. It starts at 0 and increments 1 by 1 until it matches elements from the list l
Imagine if l = [1000000, 1200000, -34]. Then your algorithm will first run for 1000000 iterations without doing anything, just incrementing a from 0 to 1000000. Then it will append 1000000 to sl. Then it will run again 200000 iterations without doing anything, just incrementing a from 1000000 to 1200000.
And then it will keep incrementing a looking for the number -34, which is below zero...
I understand the idea behind your variable a is to select the elements from l in order, starting from the smallest element. There is a function that does that: it's called min(). Try using that function to select the smallest element from l, and append that element to sl. Then delete this element from l; otherwise, the next call to min() will select the same element again instead of selecting the next smallest element.
Note that min() has a disadvantage: it returns the value of the smallest element, but not its position in the list. So it's not completely obvious how to delete the element from l after you've found it with min(). An alternative is to write your own function that returns both the element, and its position. You can do that with one loop: in the following piece of code, i refers to a position in the list (0 is the position of the first element, 1 the position of the second, etc) and a refers to the value of that element. I left blanks and you have to figure out how to select the position and value of the smallest element in the list.
....
for i, a in enumerate(l):
if ...:
...
...
If you managed to do all this, congratulations! You have implemented "selection sort". It's a well-known sorting algorithm. It is one of the simplest. There exist many other sorting algorithms.
Related
I apologize if this is a duplicate, I tried my best to find an existing question but was unsuccessful.
Recently, I've run into a couple of problems where I've needed to find the element in a list that produces the max/min value when a calculation is performed. For example, a list of real numbers where you want to find out which element produces the highest value when squared. The actual value of the squared number is unimportant, I just need the element(s) from the list that produces it.
I know I can solve the problem by finding the max, then making a pass through the list to find out which values' square matches the max I found:
l = [-0.25, 21.4, -7, 0.99, -21.4]
max_squared = max(i**2 for i in l)
result = [i for i in l if i**2 == max_squared]
but I feel like there should be a better way to do it. Is there a more concise/one-step solution to this?
This will return you just the element which gives the max when squared.
result = max(l, key = lambda k: k**2)
It does not get much better if you need the value in a list f.e. to see how often it occures. You can remeber the source element as well if you do not need that:
l = [-0.25, 21.4, -7, 0.99, -21.4]
max_squared = max( (i**2, i) for i in l) # remeber a tuple, with the result coming first
print(max_squared[1]) # print the source number (2nd element of the tuple)
Output:
21.4
Your calculation does only return the first occurence of abs(24.1) because max only returns one value, not two - if you need both, you still need to do:
print( [k for k in l if abs(k) == max_squared[1]])
to get
[21.4,-21.4]
I have the following pieces of code doing the sorting of a list by swapping pairs of elements:
# Complete the minimumSwaps function below.
def minimumSwaps(arr):
counter = 0
val_2_indx = {val: arr.index(val) for val in arr}
for indx, x in enumerate(arr):
if x != indx+1:
arr[indx] = indx+1
s_indx = val_2_indx[indx+1]
arr[s_indx] = x
val_2_indx[indx+1] = indx
val_2_indx[x] = s_indx
counter += 1
return counter
def minimumSwaps(arr):
temp = [0] * (len(arr) + 1)
for pos, val in enumerate(arr):
temp[val] = pos
swaps = 0
for i in range(len(arr)):
if arr[i] != i+1:
swaps += 1
t = arr[i]
arr[i] = i+1
arr[temp[i+1]] = t
temp[t] = temp[i+1]
temp[i+1] = i
return swaps
The second function works much faster than the first one. However, I was told that dictionary is faster than list.
What's the reason here?
A list is a data structure, and a dictionary is a data structure. It doesn't make sense to say one is "faster" than the other, any more than you can say that an apple is faster than an orange. One might grow faster, you might be able to eat the other one faster, and they might both fall to the ground at the same speed when you drop them. It's not the fruit that's faster, it's what you do with it.
If your problem is that you have a sequence of strings and you want to know the position of a given string in the sequence, then consider these options:
You can store the sequence as a list. Finding the position of a given string using the .index method requires a linear search, iterating through the list in O(n) time.
You can store a dictionary mapping strings to their positions. Finding the position of a given string requires looking it up in the dictionary, in O(1) time.
So it is faster to solve that problem using a dictionary.
But note also that in your first function, you are building the dictionary using the list's .index method - which means doing n linear searches each in O(n) time, building the dictionary in O(n^2) time because you are using a list for something lists are slow at. If you build the dictionary without doing linear searches, then it will take O(n) time instead:
val_2_indx = { val: i for i, val in enumerate(arr) }
But now consider a different problem. You have a sequence of numbers, and they happen to be the numbers from 1 to n in some order. You want to be able to look up the position of a number in the sequence:
You can store the sequence as a list. Finding the position of a given number requires linear search again, in O(n) time.
You can store them in a dictionary like before, and do lookups in O(1) time.
You can store the inverse sequence in a list, so that lst[i] holds the position of the value i in the original sequence. This works because every permutation is invertible. Now getting the position of i is a simple list access, in O(1) time.
This is a different problem, so it can take a different amount of time to solve. In this case, both the list and the dictionary allow a solution in O(1) time, but it turns out it's more efficient to use a list. Getting by key in a dictionary has a higher constant time than getting by index in a list, because getting by key in a dictionary requires computing a hash, and then probing an array to find the right index. (Getting from a list just requires accessing an array at an already-known index.)
This second problem is the one in your second function. See this part:
temp = [0] * (len(arr) + 1)
for pos, val in enumerate(arr):
temp[val] = pos
This creates a list temp, where temp[val] = pos whenever arr[pos] == val. This means the list temp is the inverse permutation of arr. Later in the code, temp is used only to get these positions by index, which is an O(1) operation and happens to be faster than looking up a key in a dictionary.
I have a list of values... some are valid, some not, the invalid contain None. I test each element for validity. When I find an invalid element, I need to find indexes of the closest previous and the closest next valid value. I need to treat the list as a cycle, so if there are no valid elements before/after the initial element, it should search from the end/start of the list... This way, if there is at least one valid value in the list, both the previous and the next valid value will be found (it can be the same index, if there is only one valid value in the list).
Ok, it is complicated to explain and it gets very complicated when I try to code it. But I am sure there is some simple and idiomatical way to do it. Can you help me?
Neither I am a programmer, but I use something like this for analysing data around the 24-hour clock (that means, for example 23:00 is before 01:00 etc.). Then I compute the unknown values as a weighted averages of the previous and next known values. The parameters are the position of the unknown element in the list and the list itself:
def get_prev_known(i, some_list):
for j, item in enumerate(some_list[i::-1]+some_list[:i:-1]):
if j > 0 and item is not None:
return (i-j) % len(some_list)
def get_next_known(i, some_list):
for j, item in enumerate(some_list[i:]+some_list[:i]):
if j > 0 and item is not None:
return (i+j) % len(some_list)
it should solve your problem.
I have two lists. I have to choose one. I have to choose the one with the smallest nth element. So I can choose the smallest element easy with min, but how do I back track it to the list itself. Have literally no idea how to solve this presumably easy problem.
a = [2,45,1,56]
b= [0,23,3,87]
Which list has the smallest element at position 2? The answer here is list a.
In case I wasnt clear, the program sould be able to solve this task for any pair of lists.
Here is a very simple snippet that does what you want, but you might want to check for the size of the arrays, in case the index is out of range.
def choose_smallest(a, b, i):
if len(a) >= i or len(b) >= i:
return 0 # do whatever you want here
if a[i] < b[i]:
return a
else:
return b
Also notice that both nth elements in your array can have the exact same value... In this example array b will be returned, but you can change that behaviour if needed.
EDIT
Added array length check
According to your example, here is a sample code you can try. You can change the code as per your requirement.
a = [2,45,1,56]
b = [0,23,3,87]
n= int(input('Enter element number: ')) # n starts from zero to length of list - 1
if a[n] > b[n]:
print('List b has smaller nth element')
elif a[n] < b[n]:
print('List a has smaller nth element')
else:
print('Both lists have equal nth element')
I have a list of about 20-30 items [strings].
I'm able to print them out in my program just fine - but I'd like to save some space, and merge items that are shorter...
So basically, if I have 2 consecutive items that the combined lengths are less than 30, I want to join those to items as a single entry in the list - with a / between them
I'm not coming up with a simple way of doing this.
I don't care if I do it in the same list, or make a new list of items... it's all happening inside 1 function...
You need to loop through the list and keep joining items till they satisfy your requirement (size 30). Then add them to a new list when an element grows that big.
l=[] # your new list
buff=yourList[0] if len(yourList)>0 else "" # hold strings till they reach desired length
for i in range(1,len(yourList)):
# check if concatenating will exceed the size or not
t=yourList[i]
if (len(buff) + len(t) + 1) <= 30:
buff+="/"+t
else:
l.append(buff)
buff=t
l.append(buff) # since last element is yet to be inserted
You can extend method of list as follows:
a = [1,2,3]
b = [4,5,6]
a.append('/')
a.extend(b)
You just need to check the size of two list a and b as per your requirements.
I hope I understood your problem !
This code worked for me, you can check to see if that's what you wanted, it's a bit lenghty but it works.
list1 = yourListOfElements
for elem in list1:
try: # Needs try/except otherwise last iteration would throw an indexerror
listaAUX = [] # Auxiliar list to check length and join smaller elements. You can probably eliminate this using list slicing
listaAUX.append(elem)
listaAUX.append(list1[list1.index(elem)+1])
if len(listaAUX[0]) + len(listaAUX[1]) < 30:
concatenated = '/'.join(listaAUX)
print(concatenated)
else:
print(elem)
except IndexError:
print(elem)