Snippets Collections
import sys

print(sys.argv[0])  # Outputs: script.py
print(sys.argv[1])  # Outputs: arg1
print(sys.argv[2])  # Outputs: arg
param(
    [string]$param1,
    [string]$param2
)

Write-Host "Parameter 1 is: $param1"
Write-Host "Parameter 2 is: $param2"
$firstArg = $args[0]  # This will be 'arg1'
$secondArg = $args[1] # This will be 'arg2'
$thirdArg = $args[2]  # This will be 'arg3'
//. A List is a collection where its elements are ordered in a sequence. Lists allow us to have duplicate elements and fine-grain control over where elements are inserted in the sequence. Lists are dynamically sized.
import java.util.List;
import java.util.ArrayList;
public class Main {
  public static void main(String[] args) {
    List<String> stringList = new ArrayList<>();
    stringList.add("Hello");
    stringList.add("World");
    stringList.add("!");
    for(String element: stringList){
      System.out.println(element);}
  }
}
>>> l = [-1, 3, 2, 0,0]
>>> [sorted(l).index(x) for x in l]
[0, 4, 3, 1, 1]
li {
-webkit-column-break-inside: avoid;
          page-break-inside: avoid;
               break-inside: avoid;
}
# Definition for singly-linked list.
# class ListNode:
#     def __init__(self, val=0, next=None):
#         self.val = val
#         self.next = next
class Solution:
    def removeNthFromEnd(self, head: Optional[ListNode], n: int) -> Optional[ListNode]:
        dummy = ListNode(0, head)
        left = dummy 
        right = head #we actually want right to be head + n 
        
        #setting right to be head + n 
        while n > 0 and right: 
            right = right.next 
            n -= 1 
        
        #this should get left at previous and right at after thanks to dummy node we inserted 
        while right: 
            left = left.next
            right = right.next 
        
        #delete node 
        left.next = left.next.next 
        
        return dummy.next 



#bottom solution is what I first came up with and works in leetcode except for if head = [1] and n = 1 which is the case I tried to account for in the second elif statement but it gave me an error saying cannot return [] even though it was fine for the first if statement 

#big O: is still O(n) just like 1st scenario 

class Solution: 
	def removeNthFromEnd(self, head: Optional[ListNode], n: int) -> Optional[ListNode]:
    	if head is None: 
            return []
        elif head.next is None and n == 1: 
            return []
        else: 
            current = head
            counter = 0 #will become length of LL 
            
            #to determine length of LL 
            while current is not None: 
                counter += 1 
                current = current.next 
                
            #consider adding an edge case here if n > counter 
            
            #second pass now knowing length of LL 
            previous, current = head, head 
            new_counter = 0 
            target = counter - n 
            while new_counter is not target + 1: 
                if new_counter == (target - 1): 
                    previous = current 
                if new_counter == target: 
                    after = current.next 
                    previous.next = after 
                    current.next = None 
                    break 


                current = current.next 


                new_counter += 1

            return head 











#solution where you just take subset I and replace last return statement 
class Solution:
    def subsetsWithDup(self, nums: List[int]) -> List[List[int]]:

   
        subset = [] 
        result = [] 
        
        #i is index of subset 
        def dfs(i): 
            if i >= len(nums): 
                result.append(subset.copy())
                return 
            
            #decision to include nums[i]
            subset.append(nums[i])
            #this recursive call will be given filled subset 
            dfs(i + 1)
            
            #decision NOT to include nums[i] 
            subset.pop()
            #this recursive call will be given empty subset 
            dfs(i + 1)
        
        dfs(0) 
        
        #need to remove duplicate sublists within result 
        return ([list(i) for i in {*[tuple(sorted(i)) for i in result]}])  
  

#solution to prevent duplicates in the first place
class Solution:
    def subsetsWithDup(self, nums: List[int]) -> List[List[int]]:

   
        result = []
		nums.sort() 

		def backtrack(i, subset): 
        	if i == len(nums): 
            	res.append(subset.copy())
				return 
			
			#all subsets that include nums[i] 
            subset.append(nums[i]) 
			backtrack(i + 1, subset) 
			#remove number we just added 
            subset.pop()
            
            #all subsets that don't include nums[i]
        	while i + 1 < len(nums) and nums[i] == nums[i + 1]: 
            	i += 1 
			backtrack(i + 1, subset)
		
		backtrack(0, [])
		
		return result 
        
        
        
        
#solution for array with unique integer array. only last return line is dfferent 
class Solution:
    def subsets(self, nums: List[int]) -> List[List[int]]:
        subset = [] 
        result = [] 
        
        #i is index of subset 
        def dfs(i): 
            if i >= len(nums): 
                result.append(subset.copy())
                return 
            
            #decision to include nums[i]
            subset.append(nums[i])
            #this recursive call will be given filled subset 
            dfs(i + 1)
            
            #decision NOT to include nums[i] 
            subset.pop()
            #this recursive call will be given empty subset 
            dfs(i + 1)
        
        dfs(0) 
        
        return result 
        
        
        
# //almost identical to doubly linked list but 
# //every node has another pointer to previous node 
# //Advantages: able to access list at end instead of going from start 
# //Disadvantages: takes up more memory 

class Node: 
  def __init__(self, value, next=None, previous=None): 
    self.value = value 
    self.next = next 
    self.previous = previous 

class DoublyLinkedList:
  def __init__(self, head=None, tail=None, length=0):
    self.head = head 
    self.tail = tail 
    self.length = length 

  #add to end of list 
  def append(self, value): 
    new_node = Node(value)
    #if there is no head (list is empty), set head and tail to be new_node 
    if self.head == None: 
      self.head = new_node 
      self.tail = new_node
    #otheriwse, set next property on tail to be new node and set tail to be newly created node 
    else: 
      self.tail.next = new_node 
      new_node.previous = self.tail 
      self.tail = new_node 
    #increment length and return 
    self.length += 1 
    return self 
  
  #removes last element of list 
   def pop(self): 
    if self.head == None: 
      return None 
    #current will eventually be the last elemeent and will be removed 
    current = self.head 
    #variable right before end 
    new_tail = current 
    #while loop to traverse to end 
    while current.next: 
      new_tail = current 
      current = current.next 
    #sets new tail 
    self.tail = new_tail 
    #cuts off old tail and current previous property 
    self.tail.next = None 
    current.previous = None 
    #decrement list 
    self.length -= 1 
    #to account when list will be destroyed 
    if self.length == 0: 
      self.head = None
      self.tail = None 
    return current 
  
  #removes elememnt at head. Note in python, shift doesn't exist, it would be .pop(0) or you can use remove which is defined later
  def shift(self): 
    if self.head == None: 
      return None 
    #current_head will be removed and returned 
    current_head = self.head 
    self.head = current_head.next 
    #severs new self.head previous property
    self.head.previous = None 
    self.length -= 1 
    #to account when list will be destroyed 
    if self.length == 0: 
      self.tail = None 
    #severs current_head. Note previous is already set to None 
    current_head.next = None 
    return current_head 

  
  #adds to start of list and replaces head. I included shift/unshift because this is what makes linked list special in terms of reducing big O 
  def unshift(self, value): 
    new_node = Node(value)
    #edge case to account if list is originally empty 
    if self.head == None: 
      self.head = new_node 
      self.tail = self.head 
    else: 
      temp = self.head 
      self.head = new_node 
      self.head.next = temp 
      temp.previous = self.head 
    self.length += 1 
  
  #travels to node at index and returns node 
  def traverse(self, index): 
    if index < 0 or index >= self.length: 
      raise IndexError('index out of range')
    counter = 0 
    current = self.head 
    #since this is doubly linked list, you can also approach from tail and go backwards 
    while counter != index: 
      current = current.next 
      counter += 1 
    return current 
  
  #travels to node at index and returns node's value 
  def get(self, index): 
    #to accomodate normal python function, where if you give index = -1 in a get(), it will return last index and so on 
    if index < 0: 
      index = self.length + index 
    node = self.traverse(index)
    return node.value 
  
  #replaces value at index 
  def set(self, index, value): 
    found_node = self.traverse(index) 
    if found_node: 
      found_node.value = value
      return True 
    else: 
      return False 
  
  #insert value at index and adds 1 to length, returns boolean if successful 
  def insert(self, index, value): 
    if index < 0 or index > self.length: 
      raise IndexError('index out of range')
    if index == self.length: 
      #not not is similar to !! in javascript and it's so it returns a boolean if successful 
      return not not self.append(value)
    if index == 0: 
      return not not self.unshift(value) 
    else: 
      new_node = Node(value) 
      previous_node = self.traverse(index - 1) 
      after_node = previous_node.next 
      
      #creating relations before new_node 
      previous_node.next = new_node 
      new_node.previous = previous_node 
      #creating relations after new_node 
      new_node.next = after_node 
      after_node.previous = new_node 
      
      #increment length
      self.length += 1 
      return self 
  
  
  def remove(self, index): 
    if index < 0 or index > self.length: 
      return indexError('index out of range') 
    if index == self.length - 1: 
      return self.pop()
    if index == 0: 
      return self.shift() 
    else: 
      #need to get previous node and after node to create relationships 
      previous_node = self.traverse(index - 1) 
      #removed_node will be removed and returned  
      removed_node = previous_node.next 
      after_node = removed_node.next 
      #unlink removed_node 
      previous_node.next = removed_node.next 
      after_node.previous = previous_node 
      #sever removed_node next 
      removed_node.next = None 
      removed_node.previous = None 
      self.length -= 1 
      return removed_node 
  
 #common interview question 
  def reverse(self): 
    #switching head and tail 
    current = self.head 
    self.head = self.tail 
    self.tail = current 
    
    next, previous = None, None 
    #to show for loop is possible in LL. Could use while loop as well 
    for i in range(0, self.length): 
      #think of this as creating the block 
      next = current.next 
      current.next = previous #initially None 
      current.previous = next
      #think of this as connecting head/previous to the block 
      previous = current 
      current = next 
    return self 

# # // [100. 201, 250, 350, 999]
# # // first part 
# # // NODE  NEXT 
# # // 100 -> null 
 
# # // second part (for loop and beyond) 
# # // PREV  NODE  NEXT 
# # // line 154( prev = current; ) specifically: 
# # // 201 -> 100  -> null 
# # // line 155 (current = next;): 
# # //        PREV  NODE  NEXT 
# # // 250 -> 201 -> 100 
  
  #useful to visualize reverse() or any other function works 
  def print_linkedlist_to_list(self): 
    result = []
    current = self.head 
    while current: 
      result.append(current.value)
      current = current.next 
    print(result)
    
    
    

# l = DoublyLinkedList() 
# l.append(1) 
# l.append(2)
# l.pop()
# l.shift()
# l.unshift(3)
# l.append(4) 
# l.traverse(0)
# l.get(-2)
# l.set(2, 7)
# l.insert(0, 99)
# l.remove(2)
# l.print_linkedlist_to_list()
# l.reverse() 
# l.print_linkedlist_to_list()

# y = l.length
# print(y)

# // Insertion: 
# // O(1) 
# // Removal: recall in SL it depends 
# // O(1)
# // Searching: 
# // O(N) but optimized bc you can start from head or tail (but more memory)
# // Access: 
# // Same as searching 
class Node: 
  def __init__(self, value, next=None): 
    self.value = value 
    self.next = next 

class SinglyLinkedList:
  def __init__(self, head=None, tail=None, length=0):
    self.head = head 
    self.tail = tail 
    self.length = length 

  #add to end of list 
  def append(self, value): 
    new_node = Node(value)
    #if there is no head (list is empty), set head and tail to be new_node 
    if self.head == None: 
      self.head = new_node 
      self.tail = self.head 
    #otheriwse, set next property on tail to be new node and set tail to be newly created node 
    else: 
      self.tail.next = new_node 
      self.tail = self.tail.next
    #increment length and return 
    self.length += 1 
    return self 
  
  #removes last element of list 
  def pop(self): 
    if self.head == None: 
      return None 
    #current will eventually be the last elemeent and will be removed 
    current = self.head 
    #variable right before end 
    new_tail = current 
    #while loop to traverse to end 
    while current.next: 
      new_tail = current 
      current = current.next 
    #sets new tail 
    self.tail = new_tail 
    #cuts off old tail 
    self.tail.next = None 
    #decrement list 
    self.length -= 1 
    #to account when list will be destroyed 
    if self.length == 0: 
      self.head = None
      self.tail = None 
    return current 
  
  #removes elememnt at head. Note in python, shift doesn't exist, it would be .pop(0) or you can use remove which is defined later
  def shift(self): 
    if self.head == None: 
      return None 
    current_head = self.head 
    self.head = current_head.next 
    self.length -= 1 
    #to account when list will be destroyed 
    if self.length == 0: 
      self.tail = None 
    return current_head 
  
  #adds to start of list and replaces head. I included shift/unshift because this is what makes linked list special in terms of reducing big O 
  def unshift(self, value): 
    new_node = Node(value)
    #edge case to account if list is originally empty 
    if self.head == None: 
      self.head = new_node 
      self.tail = self.head 
    else: 
      temp = self.head 
      self.head = new_node 
      self.head.next = temp 
    self.length += 1 
  
  #travels to node at index and returns node 
  def traverse(self, index): 
    if index < 0 or index >= self.length: 
      raise IndexError('index out of range')
    counter = 0 
    current = self.head 
    while counter != index: 
      current = current.next 
      counter += 1 
    return current 
  
  #travels to node at index and returns node's value 
  def get(self, index): 
    #to accomodate normal python function, where if you give index = -1 in a get(), it will return last index and so on 
    if index < 0: 
      index = self.length + index 
    node = self.traverse(index)
    return node.value 
  
  #replaces value at index 
  def set(self, index, value): 
    found_node = self.traverse(index) 
    if found_node: 
      found_node.value = value
      return True 
    else: 
      return False 
  
  #insert value at index and adds 1 to length, returns boolean if successful 
  def insert(self, index, value): 
    if index < 0 or index > self.length: 
      raise IndexError('index out of range')
    if index == self.length: 
      #not not is similar to !! in javascript and it's so it returns a boolean if successful 
      return not not self.append(value)
    if index == 0: 
      return not not self.unshift(value) 
    else: 
      new_node = Node(value) 
      previous_node = self.traverse(index - 1) 
      temp = previous_node.next 
      #set next property of previous node to be new_node 
      previous_node.next = new_node 
      #set new_node next to be old next of previous 
      #you can also write this as previous_node.next.next = temp 
      new_node.next = temp 
      self.length += 1 
      return True 
  
  
  def remove(self, index): 
    if index < 0 or index > self.length: 
      return indexError('index out of range') 
    if index == self.length - 1: 
      return self.pop()
    if index == 0: 
      return self.shift() 
    else: 
      #need to get previous node to create relationships 
      previous_node = self.traverse(index - 1) 
      #removed_node will be removed and returned  
      removed_node = previous_node.next 
      #unlink removed_node 
      previous_node.next = removed_node.next 
      #sever removed_node next 
      removed_node.next = None 
      self.length -= 1 
      return removed_node 
  
  #common interview question 
  def reverse(self): 
    #switching head and tail 
    current = self.head 
    self.head = self.tail 
    self.tail = current 
    
    next, previous = None, None 
    #to show for loop is possible in LL. Could use while loop as well 
    for i in range(0, self.length): 
      #think of this as creating the block 
      next = current.next 
      current.next = previous #initially None 
      #think of this as connecting head/previous to the block 
      previous = current 
      current = next 
    return self 

# // [100. 201, 250, 350, 999]
# // first part 
# // NODE  NEXT 
# // 100 -> null 
 
# // second part (for loop and beyond) 
# // PREV  NODE  NEXT 
# // line 154( prev = current; ) specifically: 
# // 201 -> 100  -> null 
# // line 155 (current = next;): 
# //        PREV  NODE  NEXT 
# // 250 -> 201 -> 100 
  
  #useful to visualize reverse() works 
  def print_linkedlist_to_list(self): 
    result = []
    current = self.head 
    while current: 
      result.append(current.value)
      current = current.next 
    print(result)
    
    
    

l = SinglyLinkedList() 
l.push(1) 
l.push(2)
l.pop()
l.shift()
l.unshift(3)
l.push(4) 
l.traverse(0)
l.get(-2)
l.set(2, 7)
l.insert(0, 99)
l.remove(2)
l.print_linkedlist_to_list()
l.reverse() 
l.print_linkedlist_to_list()

y = l.length
print(y)

# //Big O: 
# //Insertion: O(1)
# //Removal: depends O(1) if start or O(N) at end 
# //Above 2 are main advantages vs. arrays esp at start 
# //Searching: O(N)
# //Access: O(N) 
 
# //Recall with array implenetation, insertion and removal is not constant 
import os

path_cwd = os.listdir()
import re

r = re.compile(".*xlsx")                             ## what searching for
new_list = list(filter(r.match, list-name))			## list-name is the list
print(new_list)
job = {
	'title': title,
	'company': company,
	'salary': salary,
	'summary': summary
}

joblist.append(job)

print(*joblist, sep='\n')
#include<iostream>
using namespace std;

typedef struct NODE{
    int data;
    NODE *next;
}NODE;
class LIST{
    NODE *head;
    public:
    LIST();
    LIST& operator+(int);
    LIST& operator-(int);
    bool operator==(LIST&);
    LIST& operator++(int);
    LIST& operator--(int);
    friend ostream& operator<<(ostream&,LIST&);
    ~LIST();
};
int main(){
    LIST l;
    int choice,ele;
    while(1){
        cout<<"1. L = L + ele\n";
        cout<<"2. L = L - ele\n";
        cout<<"3. L = L++ \n";
        cout<<"4. L = L--\n";
        cout<<"-1: Exit\n";
        cin>>choice;
        switch(choice){
            case 1: 
                    cout<<"Enter the value of the element\n";
                    cin>>ele;
                    l = l + ele;
            break;
            case 2:
                    cout<<"Enter the value of the element\n";
                    cin>>ele;
                    l = l - ele;
            break;
            case 3:
                    l = l++;
            break;
            case 4: 
                    l = l--;
            break;
            case -1:
                    goto out;
            default:
                    cout<<"Invalid entry\n";
        }
        cout<<"List: "<<l;
    }
    out:
    return 0;
}

LIST::LIST(){
    head=NULL;
}
bool ispresent(NODE* chain,NODE *end,int key){
    NODE *temp = chain;
    while(temp!=end){
        if(temp->data==key) return true;
        temp = temp->next;
    }
    if(end!=NULL) return end->data == key ? 1:0;
    return false;
}
LIST& LIST::operator--(int){
    NODE *distinct_head = NULL;
    NODE *distinct_connect = NULL;
    NODE *duplicate_head=NULL;
    NODE *duplicate_connect = NULL;
    NODE *temp = head;
    while(temp){
        if(ispresent(distinct_head,distinct_connect,temp->data)){
            if(!duplicate_connect) duplicate_head = temp;
            else duplicate_connect->next = temp;
            duplicate_connect = temp;
        }
        else{
            if(!distinct_connect) distinct_head = temp;
            else distinct_connect->next = temp;
            distinct_connect = temp;
        }
        NODE *store = temp->next;
        temp->next = NULL;
        temp = store;
    }
    distinct_connect->next  = duplicate_head;
    head = distinct_head;
    return *this;
}
LIST& LIST::operator++(int){
    NODE *temp = head;
    while(temp){
        temp->data = temp->data +1;
        temp=temp->next;
    }
    return *this;
}
bool LIST::operator==(LIST &l2){
    NODE *temp1 = head;
    NODE *temp2 = l2.head;
    if(temp1 == NULL && temp2 == NULL) return true;
    if(temp1==NULL || temp2==NULL) return false;
    while(temp1 && temp2){
        if(temp1->data!=temp2->data) return false;
        temp1 = temp1->next;
        temp2 = temp2->next;
    }
    return temp1 || temp2 ? 0:1;
}
LIST& LIST::operator-(int element){
    NODE *temp = head;
    NODE *prev= NULL;
    while(temp){
        if(temp->data==element){
            if(!prev) head=head->next;
            else prev->next = temp->next;
            delete temp;
            return *this;
        }
        prev=temp;
        temp=temp->next;
    }
    return *this;
}
LIST& LIST::operator+(int element){
    NODE *current = new NODE;
    current->data = element;
    current->next = NULL;
    NODE *temp = head;
    if(!temp){
        head = current;
        return *this;
    }
    while(temp->next){
        temp = temp->next;
    }
    temp->next = current;
    return *this;
}
ostream& operator<<(ostream& print,LIST &l){
    NODE *temp= l.head;
    while(temp){
        print<<temp->data<<" ";
        temp = temp->next;
    }
    print<<endl;
    return print;
}
LIST::~LIST(){
    NODE *temp = head;
    while(temp){
        NODE *store = temp->next;
        delete temp;
        temp = store;
    }
}
#You can do it using GloVe library:

#Install it: 

!pip install glove_python

from glove import Corpus, Glove

#Creating a corpus object
corpus = Corpus() 

#Training the corpus to generate the co-occurrence matrix which is used in GloVe
corpus.fit(lines, window=10)

glove = Glove(no_components=5, learning_rate=0.05) 
glove.fit(corpus.matrix, epochs=30, no_threads=4, verbose=True)
glove.add_dictionary(corpus.dictionary)
glove.save('glove.model')
 Save

 
 
 #for Fasttext
 from gensim.models import FastText
from gensim.test.utils import common_texts  # some example sentences
>>>
print(common_texts[0])
['human', 'interface', 'computer']
print(len(common_texts))
9
model = FastText(vector_size=4, window=3, min_count=1)  # instantiate
model.build_vocab(sentences=common_texts)
model.train(sentences=common_texts, total_examples=len(common_texts), epochs=10)  # train
model2 = FastText(vector_size=4, window=3, min_count=1, sentences=common_texts, epochs=10)

import numpy as np
>>>
np.allclose(model.wv['computer'], model2.wv['computer'])
True


from gensim.test.utils import datapath
>>>
corpus_file = datapath('lee_background.cor')  # absolute path to corpus
model3 = FastText(vector_size=4, window=3, min_count=1)
model3.build_vocab(corpus_file=corpus_file)  # scan over corpus to build the vocabulary
>>>
total_words = model3.corpus_total_words  # number of words in the corpus
model3.train(corpus_file=corpus_file, total_words=total_words, epochs=5)


from gensim.utils import tokenize
from gensim import utils
>>>
>>>
class MyIter:
    def __iter__(self):
        path = datapath('crime-and-punishment.txt')
        with utils.open(path, 'r', encoding='utf-8') as fin:
            for line in fin:
                yield list(tokenize(line))
>>>
>>>
model4 = FastText(vector_size=4, window=3, min_count=1)
model4.build_vocab(sentences=MyIter())
total_examples = model4.corpus_count
model4.train(sentences=MyIter(), total_examples=total_examples, epochs=5)
from gensim.test.utils import get_tmpfile
>>>
fname = get_tmpfile("fasttext.model")
>>>
model.save(fname)
model = FastText.load(fname)


# https://radimrehurek.com/gensim/models/fasttext.html
In [1]: df = pd.DataFrame( {'a':['A','A','B','B','B','C'], 'b':[1,2,5,5,4,6]})
        df

Out[1]: 
   a  b
0  A  1
1  A  2
2  B  5
3  B  5
4  B  4
5  C  6

In [2]: df.groupby('a')['b'].apply(list)
Out[2]: 
a
A       [1, 2]
B    [5, 5, 4]
C          [6]
Name: b, dtype: object

In [3]: df1 = df.groupby('a')['b'].apply(list).reset_index(name='new')
        df1
Out[3]: 
   a        new
0  A     [1, 2]
1  B  [5, 5, 4]
2  C        [6]
colors = ['red', 'green', 'blue']
for idx, color in enumerate(colors):
	print(idx, color)
> 0 red
> 1 green
> 2 blue
JavaScript

for (let i=0; i < arrayName.length; i++){
  console.log(arrayName[i])
}

i.e.):

movies = ['legally blonde', 'Ms. & Ms. Smith', 'The Incredibles'];

for (let i=0; i < movies.length; i++){
  console.log(movies[i])
}

Python

for singular_array_name in array_name_pluralized:
	print(singular_array_name)

i.e.):

movies = ['legally blonde', 'Ms. & Ms. Smith', 'The Incredibles']

for movie in movies:
	print(movie)
@mixin auto-numbers($numbered-element, $sep, $counter: item, $nested-parent: false ){
    $sel: ();
    @if $nested-parent {
        $sel: append($sel, unquote($nested-parent));

        #{$nested-parent}{
            list-style: none;
            margin-left: 0;
        }
    }
    $sel: append($sel, unquote('&'), comma);

    #{$sel}{
        counter-reset: #{$counter};
        > #{$numbered-element}{
            &:before{
                counter-increment: #{$counter};
                content: if($nested-parent, counters(#{$counter}, "#{$sep} ") "#{$sep} ", counter(#{$counter}) "#{$sep} ") ;
            }
        }
    }
}
  .rounded-list a{
    position: relative;
    display: block;
    padding: .4em .4em .4em 2em;
    *padding: .4em;
    margin: .5em 0;
    background: #ddd;
    color: #444;
    text-decoration: none;
    border-radius: .3em;
    transition: all .3s ease-out;
  }

  .rounded-list a:hover{
    background: #eee;
  }

  .rounded-list a:hover:before{
    transform: rotate(360deg);
  }

  .rounded-list a:before{
    content: counter(li);
    counter-increment: li;
    position: absolute;
    left: -1.3em;
    top: 50%;
    margin-top: -1.3em;
    background: #87ceeb;
    height: 2em;
    width: 2em;
    line-height: 2em;
    border: .3em solid #fff;
    text-align: center;
    font-weight: bold;
    border-radius: 2em;
    transition: all .3s ease-out;
  }
# numpy and matplotlib imported, seed set

# Simulate random walk 500 times
all_walks = []
for i in range(500) :
    random_walk = [0]
    for x in range(100) :
        step = random_walk[-1]
        dice = np.random.randint(1,7)
        if dice <= 2:
            step = max(0, step - 1)
        elif dice <= 5:
            step = step + 1
        else:
            step = step + np.random.randint(1,7)
        if np.random.rand() <= 0.001 :
            step = 0
        random_walk.append(step)
    all_walks.append(random_walk)

# Create and plot np_aw_t
np_aw_t = np.transpose(np.array(all_walks))

# Select last row from np_aw_t: ends
ends = np_aw_t[-1, :]

# Plot histogram of ends, display plot
plt.hist(ends)
plt.show()
# Numpy is imported; seed is set

# Initialize all_walks (don't change this line)
all_walks = []

# Simulate random walk 10 times
for i in range(10):

    # Code from before
    random_walk = [0]
    for x in range(100) :
        step = random_walk[-1]
        dice = np.random.randint(1,7)

        if dice <= 2:
            step = max(0, step - 1)
        elif dice <= 5:
            step = step + 1
        else:
            step = step + np.random.randint(1,7)
        random_walk.append(step)

    # Append random_walk to all_walks
    all_walks.append(random_walk)

# Print all_walks
print(all_walks)


#####################################################################
# numpy and matplotlib imported, seed set

# Simulate random walk 250 times
all_walks = []
for i in range(250) :
    random_walk = [0]
    for x in range(100) :
        step = random_walk[-1]
        dice = np.random.randint(1,7)
        if dice <= 2:
            step = max(0, step - 1)
        elif dice <= 5:
            step = step + 1
        else:
            step = step + np.random.randint(1,7)

        # Implement clumsiness
        if np.random.rand() <= 0.001 :
            step = 0

        random_walk.append(step)
    all_walks.append(random_walk)

# Create and plot np_aw_t
np_aw_t = np.transpose(np.array(all_walks))
plt.plot(np_aw_t)
plt.show()


# Numpy is imported, seed is set

# Initialization
random_walk = [0]

for x in range(100) :
    step = random_walk[-1]
    dice = np.random.randint(1,7)

    if dice <= 2:
        step = max(0, step - 1)
    elif dice <= 5:
        step = step + 1
    else:
        step = step + np.random.randint(1,7)

    random_walk.append(step)

# Import matplotlib.pyplot as plt
import matplotlib.pyplot as plt

# Plot random_walk
plt.plot(random_walk)

# Show the plot
plt.show()
# Numpy is imported, seed is set

# Initialize random_walk
random_walk = [0]

# Complete the ___
for x in range(100) :
    # Set step: last element in random_walk
   
    step = random_walk[-1]

    # Roll the dice
    dice = np.random.randint(1,7)

    # Determine next step
    if dice <= 2:
        step = step - 1
    elif dice <= 5:
        step = step + 1
    else:
        step = step + np.random.randint(1,7)

    # append next_step to random_walk
    random_walk.append(step)

# Print random_walk
print(random_walk)

#Not Going below zero
# Numpy is imported, seed is set

# Initialize random_walk
random_walk = [0]

for x in range(100) :
    step = random_walk[-1]
    dice = np.random.randint(1,7)

    if dice <= 2:
        # Replace below: use max to make sure step can't go below 0
        step = max(0, step - 1)
    elif dice <= 5:
        step = step + 1
    else:
        step = step + np.random.randint(1,7)

    random_walk.append(step)

print(random_walk)
# Numpy is imported, seed is set

# Starting step
step = 50
# Roll the dice
dice = np.random.randint(1,7)
# Finish the control construct
if dice <= 2 :
    step = step - 1
elif dice <= 5 :
    step = step + 1
else:
    step = step + np.random.randint(1,7)

# Print out dice and step
print(dice)
print(step)
# Import numpy as np
import numpy as np

# Set the seed
np.random.seed(123)

# Generate and print random float
print(np.random.rand())

#Roll The Dice
# Import numpy and set seed
import numpy as np
np.random.seed(123)

# Use randint() to simulate a dice
print(np.random.randint(1,7))
# Use randint() again
print(np.random.randint(1,7))


# Import cars data
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Use .apply(str.upper)


cars['COUNTRY'] = cars['country'].apply(str.upper)
print(cars)
# Import cars data
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Adapt for loop
for lab, row in cars.iterrows() :
    print(lab + ": " + str(row['cars_per_cap']))

#Something new

# Import cars data
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Code for loop that adds COUNTRY column
for lab, row in cars.iterrows():
    cars.loc[lab,'COUNTRY'] = row['country'].upper()


# Print cars
print(cars)
#Iterating over a Pandas DataFrame is typically done with the iterrows()
# Import cars data
import pandas as pd
cars = pd.read_csv('cars.csv', index_col = 0)

# Iterate over rows of cars
for lab,row in cars.iterrows():
    print(lab)
    print(row)
# Import numpy as np

import numpy as np
#for x in my_array : #in 1D Numpy array
#for x in np.nditer(my_array) : #for 2D Numpy array

# For loop over np_height

for x in np_height:
    print(str(x) + " inches")

# For loop over np_baseball
for x in (np.nditer(np_baseball)):
    print(x)
# Definition of dictionary
europe = {'spain':'madrid', 'france':'paris', 'germany':'berlin',
          'norway':'oslo', 'italy':'rome', 'poland':'warsaw', 'austria':'vienna' }
          
# Iterate over europe
for key, value in europe.items() :
    print('the capital of ' + str(key) + ' is ' + str(value))
# house list of lists
house = [["hallway", 11.25], 
         ["kitchen", 18.0], 
         ["living room", 20.0], 
         ["bedroom", 10.75], 
         ["bathroom", 9.50]]
         
# Build a for loop from scratch
for x in house :
    #x[0] to access name of room
    #x[1] to access area in sqm
    print('the ' + x[0] + " is " + str(x[1]) + " sqm")
Row {
    Button(onClick = {
        coroutineScope.launch {
            // 0 is the first item index
            scrollState.animateScrollToItem(0)
        }
    }) {
        Text("Scroll to the top")
    }

    Button(onClick = {
        coroutineScope.launch {
            // listSize - 1 is the last index of the list
            scrollState.animateScrollToItem(listSize - 1)
        }
    }) {
        Text("Scroll to the end")
    }
}
fruit = {
  "elderberries": 1,
  "figs": 1,
  "apples": 2,
  "durians": 3,
  "bananas": 5,
  "cherries": 8,
  "grapes": 13
}

table_data = []
for k, v in fruit.items():
   table_data.append([k, v])
PSA: How to View Variables in Lists
by 
Bradford Shelley
 Forum Level 2
created 4y ago (edited 3y ago ) in Developer Community
After having to play around with variables quite a bit in a recent project, I thought I'd share how to display variables on a list of Requested Items / Catalog Tasks. This applies to lists and related lists, as reports have their own method of displaying variables. Important note: This was performed on Fuji. Your experience may differ on older versions of ServiceNow.

Step 1 Identify the variables you'd like to display on your list, then copy the sys_id for each variable. This is as simple as heading to the Catalog Item, and jumping into the variable(s) in question. We'll need the sys_id to add the column into the list.

Step 2 Head over to System UI -> Lists

Step 3 Identify the list you'd like to display the variable(s) on. We're looking for one of two things here. Either the name of the view of the list you'd like to include the variable(s) on (I highly recommend creating a new view instead of using the Default view for this, as most likely the variables will apply to certain catalog items instead of every single one), or for a related list look at the Parent and Relationship columns for the table and name of the tab for the related list. Head into the list when you've found it.



Step 4 Create a new List Element(s) from the related list at, using "variables.sys_id" (no quotes) in the actual Element field on the List Element form. Create a new List Element for each variable you wish to add.



Step 5 Head over to the list where variables were just added. They won't show up immediately, so don't panic. Edit the list layout, and move around the variables to the spots you'd like them in the list (even if the position is already how you'd like it, move a variable one position up/down, then move it back and save). At this point, the variables should be visible!

Hope this helps at least one person out there. Take care!
# Python program to illustrate 
# Finding common member in list  
# using 'in' operator 
list1=[1,2,3,4,5] 
list2=[6,7,8,9] 
for item in list1: 
    if item in list2: 
        print("overlapping")       
else: 
    print("not overlapping") 
star

Fri Aug 25 2023 03:35:53 GMT+0000 (Coordinated Universal Time)

#args #list #files #embed #image
star

Thu Aug 24 2023 06:17:58 GMT+0000 (Coordinated Universal Time)

#args #list #files #embed #image
star

Wed Aug 23 2023 22:09:56 GMT+0000 (Coordinated Universal Time)

#args #list #files
star

Wed Aug 23 2023 22:09:38 GMT+0000 (Coordinated Universal Time)

#args #list #files
star

Sun Dec 25 2022 20:47:50 GMT+0000 (Coordinated Universal Time)

#java #generics #list
star

Thu Nov 03 2022 05:16:05 GMT+0000 (Coordinated Universal Time) https://stackoverflow.com/questions/3071415/efficient-method-to-calculate-the-rank-vector-of-a-list-in-python

#python #list
star

Thu Oct 27 2022 02:23:43 GMT+0000 (Coordinated Universal Time)

#html #lists #list #htmllist
star

Thu Oct 20 2022 14:06:51 GMT+0000 (Coordinated Universal Time) https://css-tricks.com/almanac/properties/b/break-inside/

#list #typography #css
star

Sat Oct 15 2022 07:20:17 GMT+0000 (Coordinated Universal Time) https://docs.aws.amazon.com/cli/latest/reference/kinesis/list-streams.html

#kinesis #aws #list
star

Mon Sep 26 2022 07:17:25 GMT+0000 (Coordinated Universal Time) https://stackoverflow.com/questions/46334850/sorting-a-list-of-integers-and-strings-by-integer-descending-order-in-vb

#list
star

Fri Aug 12 2022 20:01:25 GMT+0000 (Coordinated Universal Time) https://leetcode.com/problems/remove-nth-node-from-end-of-list/submissions/

#python #linked #list #two #pointer #dummy #node
star

Tue Aug 09 2022 22:02:17 GMT+0000 (Coordinated Universal Time) https://leetcode.com/problems/subsets-ii/submissions/

#python #depth #first #search #recursive #codesignal #climb #list
star

Mon Jul 04 2022 09:55:34 GMT+0000 (Coordinated Universal Time)

#pytho #list
star

Mon Jul 04 2022 09:54:47 GMT+0000 (Coordinated Universal Time)

#pytho #list
star

Sun May 15 2022 06:41:38 GMT+0000 (Coordinated Universal Time) https://stackoverflow.com/questions/13443588/how-can-i-format-a-list-to-print-each-element-on-a-separate-line-in-python

#python #print #list #newline
star

Sat May 07 2022 12:46:49 GMT+0000 (Coordinated Universal Time)

#c++ #list #oop
star

Thu Apr 21 2022 17:21:57 GMT+0000 (Coordinated Universal Time) https://medium.com/analytics-vidhya/word-vectorization-using-glove-76919685ee0b

#pandas #list #group
star

Wed Apr 20 2022 18:10:53 GMT+0000 (Coordinated Universal Time) https://stackoverflow.com/questions/22219004/how-to-group-dataframe-rows-into-list-in-pandas-groupby

#pandas #list #group
star

Sat Jan 15 2022 19:30:51 GMT+0000 (Coordinated Universal Time)

#python #iteration #enumerate #list
star

Sat Jan 15 2022 19:01:04 GMT+0000 (Coordinated Universal Time)

#python #javascript #array #list #forloop #iteration
star

Wed Jan 05 2022 04:40:37 GMT+0000 (Coordinated Universal Time) https://gabri.me/blog/sass-mixin-for-auto-numbering-with-css

#list #mixin
star

Sat Jan 01 2022 04:12:55 GMT+0000 (Coordinated Universal Time) https://catalin.red/css3-ordered-list-styles/

#css #list
star

Fri Nov 26 2021 10:49:17 GMT+0000 (Coordinated Universal Time)

#list #forloop #for #loop #dicegame #matplotlib #[plot #graph
star

Fri Nov 26 2021 10:42:38 GMT+0000 (Coordinated Universal Time)

#list #forloop #for #loop #dicegame
star

Fri Nov 26 2021 10:06:16 GMT+0000 (Coordinated Universal Time)

#list #forloop #for #loop ##dictionary
star

Fri Nov 26 2021 09:45:49 GMT+0000 (Coordinated Universal Time)

#list #forloop #for #loop ##dictionary
star

Thu Nov 25 2021 17:01:18 GMT+0000 (Coordinated Universal Time)

#list #forloop #for #loop ##dictionary
star

Thu Nov 25 2021 16:48:58 GMT+0000 (Coordinated Universal Time)

#list #forloop #for #loop ##dictionary
star

Thu Nov 25 2021 16:42:08 GMT+0000 (Coordinated Universal Time)

#list #forloop #for #loop ##dictionary
star

Thu Nov 25 2021 16:28:23 GMT+0000 (Coordinated Universal Time)

#list #forloop #for #loop ##dictionary
star

Thu Nov 25 2021 16:16:28 GMT+0000 (Coordinated Universal Time)

#list #forloop #for #loop ##dictionary
star

Thu Nov 25 2021 15:55:42 GMT+0000 (Coordinated Universal Time)

#numpy #booleans_in_numpy #list #forloop #for #loop
star

Sun Jun 20 2021 19:49:37 GMT+0000 (Coordinated Universal Time) https://developer.android.com/courses/pathways/compose

#lazycolumn #list #jetpackcompose
star

Sun May 02 2021 08:00:48 GMT+0000 (Coordinated Universal Time)

#python #list #dictionary
star

Thu Nov 19 2020 21:32:35 GMT+0000 (Coordinated Universal Time) https://community.servicenow.com/community?id

#servicenow #catalog #servicecatalog #variables #list #listview #view
star

Fri Oct 30 2020 20:19:26 GMT+0000 (Coordinated Universal Time) https://www.geeksforgeeks.org/python-membership-identity-operators-not-not/

#python #in #list
star

Mon Mar 23 2020 07:13:49 GMT+0000 (Coordinated Universal Time) https://www.30secondsofcode.org/python/s/max-by/

#python #python #math #list

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