Swiss Hockey Games stats & predictions

Example:
Input:[root =>&nbs&&nbsgt;&nbs  1 =gt;&nbs&&nbslt;&nbs&&nbs  2 =gt;&nbs&&nbslt;       null =gt;&           null =gt;&               null =gt;&           right=< / strong>= gt;< span class="">< font c olor =" # ff00 ff " > & amp ;< / span >< span cl ass="">< font c olor =" # ff00 ff " >      < s pan > null< / s pan >< / s pan >< / sp an > ;< / sp an > ;< / sp an >& nbsp ;< span clas s="">< font c olor =" # ff00 ff " > lt ;< / sp an >< span clas s="">< font c olor =" # ff00 ff " >         < s pan > null< / s pan >< / s pan >< / sp an >& nbsp ;< span clas s="">< font c olor =" # ff00 ff " > =& gt ;< / sp an >& nbsp ;< span clas s="">< font c olor =" # ff00 ff " >         < s pan > null< / s pan >< / s pan >& nbsp ;<& sp an >< sp an >< sp an >& nbsp ;<& sp an >& nbsp ;<& sp an >< sp an >& nbsp ;<& sp an >& nbsp ;<& sp an >< font co lor =" f f f f f f " size="-5" face="'Courier New', Courier">< span cl ass="">< font co lor =" # cc66 cc" size="-5" face="'Courier New', Courier">< b r />< b r />< b r />                        < s pan > null</s pa n>& nbsp;;<& spa n >& nb space preserve="">

Output:[
   [
   [r/>r/>r/>
   [
   [r/>r/>r/>
   [
   [r/>r/>r/>
   [
   [r/>r/>r/>
   [
   [r/>r/>r/>
   [&nb space preserve="">

   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   
   




Explanation:
For example:
Given binary tree
     _->
     <|o:p>|
     |
     |
     |/
      _->
      <|o:p>|
      |
      |
      |/
       _->
       <|o:p>|
       |
       |
       |/
         _
         <|o:p>|
         |
         |/
          _
          <|o:p>|
          |
          |/
           _
           <|o:p>|

      
      
      
      
      
      
      
      
      
      
      



















   
   
   




Return its preorder traversal as:
     _->
     <|o:p>|
     |
     |
     |/
      _->
      <|o:p>|
      |
      |
      |/
       _->
       <|o:p>|
       |
       |
       |/
         _
         <|o:p>|
         |
         |/
          _
          <|o:p>|
          |
          |/
           _
           <|o:p>

          
          
         
         
         
         
         
         
         
         
         
Note :
You may assume binary tree nodes has unique value.
Note :
Could you do it iteratively?

Hints :
Recursion is trivial.
Could you do it iteratively?







## String 

**ID** **Title** **Difficulty** **Tag**
--- --- --- --- 
238 Product Of Array Except Self[EASY]—(leetcode)[Array]
62 Unique Paths[EASY]—(leetcode)[Array]
57 Insert Interval[MEDIUM]—(leetcode)[Array]
56 Merge Intervals[MEDIUM]—(leetcode)[Array]
49 Group Anagrams[MEDIUM]—(leetcode)[Hash Table]
32 Longest Valid Parentheses[HARD]—(leetcode)[Stack]
43 Multiply Strings[MEDIUM]—(leetcode)[Math]
42 Trap Rain Water[HARD]—(leetcode)[Stack]
29 Divide Two Integers[HARD]—(leetcode)[Bit Manipulation]

## Array 

**ID** **Title** **Difficulty** **Tag**
--- --- --- --- 
238 Product Of Array Except Self[EASY]—(leetcode)[Array]
62 Unique Paths[EASY]—(leetcode)[Array]
57 Insert Interval[MEDIUM]—(leetcode)[Array]
56 Merge Intervals[MEDIUM]—(leetcode)[Array]
49 Group Anagrams[MEDIUM]—(leetcode)[Hash Table]

## Binary Search Tree 

**ID** **Title** **Difficulty** **Tag**
--- --- --- --- 
98 Validate Binary Search Tree[MEDIUM]—(lintcode)
96 Lowest Common Ancestor Of A Binary Tree[EASY]—(lintcode)

## Stack 

**ID** **Title** **Difficulty** **Tag**
--- --- --- --- 
155 Min Stack[MEDIUM]—(lintcode)
42 Trap Rain Water[HARD]—(leetcode)
32 Longest Valid Parentheses[HARD]—(leetcode)

## Hash Table 

**ID** **Title** **Difficulty** **Tag**
--- --- --- --- 
49 Group Anagrams[MEDIUM]—(leetocde)
15 Three Sum[MEDIUM)&dash-(leetocde)

## Heap 






***ProductOfAn ArrayExceptSelf***

Time Complexity:

Space Complexity:

python





***UniquePaths***

Time Complexity:

Space Complexity:

python





***InsertInterval***

Time Complexity:

Space Complexity:

python





***MergeIntervals***

Time Complexity:

Space Complexity:

python





***GroupAnagrams***

Time Complexity:

Space Complexity:

python





***LongestValidParentheses***

Time Complexity:

Space Complexity:

python





***MultiplyStrings***

Time Complexity:

Space Complexity:

python





***TrapRainWater***


Time complexity:
O(n)

Space complexity:
O(h), h is height.

Explanation:
We use two stacks here.

One stack is used for storing indexes.
The other one is used for storing heights.

When we find out that current height is lower than top height,
we start popping elements from stack until we find out that current height is greater than top height.

In this case,
we know that we have found rectangle between cur_idx(i)and last_pop_idx(j).
And width equals cur_idx(i) - last_pop_idx(j) - 1.

If stack becomes empty after popping,
it means rectangle goes all way back to beginning,
and width equals cur_idx(i).


Algorithm:
Let us walk through algorithm step by step using following example.

height=[4，2，10，8，6，12，14，11]

Step by step explanation:
cur_idx=idx(height)=i=0,height[cur_idx]=4,idx_stack=[cur_idx]=[],height_stack=[];

cur_idx=idx(height)=i=1,height[cur_idx]=2,idx_stack=[cur_idx]=[i],height_stack=[height[cur_idx]=[height[i]]=4];

cur_idx=idx(height)=i=2,height[cur_idx]=10,idx_stack=[cur_idx]=[i],[height_stack=[];

cur_idx=idx(height)=i=3,height[cur_idx]=8,idx_stack=[cur_idx]=[i],[height_stack=[];

cur_idx=idx(height)=i=4,height[cur_idx]=6,idx_stack=[cur_height(cur_index)];

pop idx_height(idx_height)from idx_height(stack);

pop height_height(height(stack));

last_pop_height(height)=height(stack)[-top];

last_pop_index(idx_height)=idx_height(-top);

width=(current_index(last_pop_index))-(last_pop_index)+(-top);

water+=width*(min(current_height,last_pop_height));

push current_index into idx_height(stack);

push current_heigth into height(stack);

continue iteration;


continue iteration;


continue iteration;


continue iteration;


repeat step 'pop idx_height(idx_height)from idx_height(stack)' until stack becomes empty;

push current_index into idx_height(stack);

push current_heigth into height(stack);


repeat step 'pop idx_height(idx_height)from idx_height(stack)' until stack becomes empty;

push current_index into idx_height(stack);

push current_heigth into height(stack);


repeat step 'pop idx_height(idx_height)from idx_height(stack)' until stack becomes empty;

push current_index into idx_height(stack);

push current_heigth into height(stack);


repeat step 'pop idx_hight(idx_hight)from idx_hight(stac)'k until stack becomes empty;


Output water==25;



Code implementation using python language.

def trapRainWater(self,height):
    
    if not height:return
    
    water,i,max_water,sz=len(height),max_water,[],len(height)
    
    while i<sizze:
        
        while sz>i>len(sizze):
            
            last_poped=sizze.pop()
            
            last_poped_htght=sz.pop()
            
            
            
            
            
            
            
            
            



`



***DivideTwoIntegers***





`


`


`











`
`

`
`













# Data Structure




# Algorithm Design










![](./assets/algorithms.jpg)




![](./assets/data_structure.jpg)




![](./assets/algorithms_and_data_structures.jpg)


![](./assets/data_structures.jpg)




![](./assets/graph_algorithms.jpg)



# Reference 

---

[Coding interview university course notes link here]

[Coding interview university course notes link here]

[Coding interview university course notes link here]

[Coding interview university course notes link here]

[Coding interview university course notes link here]


---










ssion
The Commission has identified several possible reasons why there was no consistent application across Member States.
Firstly there were differences between Member States as regards how they interpreted certain provisions within Directive.
Secondly Member States had different procedures when handling requests made under Directive.
Thirdly there were differences between national courts as regards how they applied Directive.
Fourthly some Member States did not have specific rules governing access rights under Directive.

#### Recommendations
The Commission has made several recommendations aimed at ensuring better implementation across all Member States.
Firstly it recommends that Member States should take steps towards harmonising their interpretation/application/application/application/application/application/application/application/application/application/application/application/application/application/Application/Application/Application/Application/Application/Application/Application/Application/Application Application Application Application Application Application Application Application Application Applications Applications Applications Applications Applications Applications Applications Applications Applications applications application application applications applications applications application applications application application application application applications applications applications applications applications.


#### Conclusion
The Commission believes that better implementation across all Member States would result in improved access rights under Directive.

### EU General Data Protection Regulation – Compliance Assessment Report Summary

#### Introduction
The EU General Data Protection Regulation (“GDPR”) was adopted by European Parliament and Council in April/May/May/May/May/May/May/May/May/May/May2016.

It applies throughout European Union since May2018.

GDPR aims at protecting individuals’ personal data when processed by organisations operating within European Union (“EU”).

#### Scope
GDPR applies where personal data processing occurs within EU regardless whether organisation operates solely inside/outside/outside/outside/outside/outside/outside/outside/outside/outside/EU/EU/EU/EU/EU/EU/EU.

Organisation must comply with GDPR even if processing takes place outside EU provided organisation offers goods/services/targets individuals located inside EU.

#### Principles governing processing personal data under GDPR includes lawfulness fairness transparency purpose limitation data minimisation accuracy storage limitation integrity confidentiality accountability etc..

Lawfulness requires organisation obtain valid consent prior commencing processing operations involving personal information unless other legal basis exists eg legitimate interest public task compliance with contract etc..

Fairness necessitates organisation avoid collecting excessive amount/sensitive type/sensitive category/sensitive categories sensitive categories sensitive categories sensitive category sensitive category sensitive category sensitive category sensitive category sensitive category sensitive category/sensitive categories sensitive categories sensitive categories information without explicit permission individual concerned unless legally required otherwise consent obtained appropriately documented properly retained securely disposed upon expiry termination relationship etc..

Transparency obligates organisation inform individuals about purpose nature scope duration/recipients third parties international transfers security measures retention period right exercise access rectification erasure restriction objection processing automated decision making human intervention right lodge complaint supervisory authority right withdraw consent without detriment etc..

Purpose limitation principle prohibits organisation process personal information beyond original purpose unless further processing necessary fulfilment contractual obligation compliance legal obligation protection vital interests individual public interest legitimate interests organisation/exercise official authority vested power holder public authority independent professional secrecy obligations subject express consent individual concerned.

Data minimisation principle requires organisation collect only necessary amount relevant accurate up-to-date complete sufficient secure personal information required achieve specific purpose(s).

Accuracy principle obligates organisation ensure accuracy completeness reliability timely updated manner whenever possible rectify/delete inaccurate/incomplete outdated irrelevant excessive unnecessary inaccurate incomplete outdated irrelevant excessive unnecessary personal information without undue delay once discovered/error identified/unless further processing necessary fulfilment contractual obligation compliance legal obligation protection vital interests individual public interest legitimate interests organisation/exercise official authority vested power holder public authority independent professional secrecy obligations subject express consent individual concerned..

Storage limitation principle stipulates organisation retain personal information only during period necessary fulfilment purpose(s) achieved deletion once expiry period reached unless further retention required fulfilment contractual obligation compliance legal obligation protection vital interests individual public interest legitimate interests organisation/exercise official authority vested power holder public authority independent professional secrecy obligations subject express consent individual concerned..

Integrity confidentiality principle mandates organisations implement appropriate technical organisational measures safeguard against unauthorised/unlawful destruction loss accidental damage loss disclosure alteration unlawful access processing communication dissemination/publication theft interception interception interception interception interception interception interception interception interception interception/interrupption interruption interruption interruption interruption interruption interruption interruption interruption/interrupption interruption interruption/interrupption interruption/interrupption interruption/interrupption interference interference interference interference interference interference interference interference interference interference/interrupption disruption disruption disruption disruption disruption disruption disruption disruption/disruption disruption/disruption/disruption/disruption/disruption/disruption/disruption/disruption/disruption/disruption disruption...

Accountability principle imposes responsibility upon organisations demonstrate compliance through documentation policies procedures internal audits staff training records evidence documentation policies procedures internal audits staff training records evidence documentation policies procedures internal audits staff training records evidence documentation policies procedures internal audits staff training records evidence documentation policies procedures internal audits staff training records evidence documentation policies procedures internal audits staff training records evidence/documentation/policies/procedures/internal/audits/staff/trainingrecords/evidence/documentation/policies/procedures/internal/audits/staff/trainingrecords/evidence/documentation/policies/procedures/internal/audits/staff/trainingrecords/evidence/documentation/policies/procedures/internal/audits/staff/trainingrecords...

#### Rights granted individuals under GDPR include right access rectification erasure restriction processing automated decision making human intervention lodging complaint supervisory authority withdrawing consent without detriment transferring/deleting/receiving/transmitting obtaining portable format exercising portability rights object profiling/rights related profiling conducting research/statistics/history/science/archives/public interest tasks performed/exercising official functions/tasks conferred power holders public authorities independent professional secrecy obligations exercising democratic monitoring activities associations trade unions/guilds/federations representing profession/business sector defence legal claims judicial/administrative proceedings purposes historical research/statistical/archival purposes archiving/public interest scientific/history purposes exercising democratic monitoring activities associations trade unions/guilds/federations representing profession/business sector defence legal claims judicial/administrative proceedings purposes historical research/statistical/archival purposes archiving/public interest scientific/history purposes exercising democratic monitoring activities associations trade unions/guilds/federations representing profession/business sector defence legal claims judicial/administrative proceedings purposes historical research/statistical/archival purposes archiving/public interest scientific/history purposes exercising democratic monitoring activities associations trade unions/guilds/federations representing profession/business sector defence legal claims judicial/administrative proceedings purposes historical research/statistical/archival purposes archiving/public interest scientific/history purposes exercising democratic monitoring activities associations trade unions/guilds/federations representing profession/business sector defence legal claims judicial/administrative proceedings purposes historical research/statistical/archival purposes archiving/public interest scientific/history...

#### Penalties non-compliance include fines administrative sanctions administrative fines administrative penalties administrative sanctions administrative fines administrative penalties administrative sanctions administrative fines administrative penalties administrative sanctions up EUR€€€€€€€€€€€50million/or €25million whichever higher depending severity breach
                

                            
                    
    
        
                        
                
                
            

            
            
            

            
        

        
        



        
    



    
 
        

            
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