Archive

Posts Tagged ‘Problem’

Python: Largest Palindrome Product



Python: Largest Palindrome Product
Problem No.4 @ Projecteuler
Complete on: on Fri, 5 Jul 2019, 08:53

The task was to find the largest palindromic number that been generated from multiplying two of 3 digits number.

Definition: Palindromic numbers are numbers that remains the same when its digits are reversed. Like 16461, we may say they are “symmetrical”.wikipedia.org

To solve this I first wrote a function to check if we can read a number from both side or not, Then using while and for loop through numbers 100 to 999, and store largest palindromic, we select the range (100,999) because the task is about tow number each with 3 digits.



The Code:



# Problem 4
# Largest palindrome product
# SOLVED
# Completed on Fri, 5 Jul 2019, 08:53


palin =0
def palindromic(n) :

n_list=[]

for each in str(n) :

n_list.append(each)

n_last = len(n_list)-1

n_first =0

x=0

while (n_first+x != n_last-x) :

if n_list[n_first+x] != n_list[n_last-x] :

return False

else :

x +=1

if (n_first +x > n_last -x):

return True

return True

for set1 in range (1,999):

for set2 in range (set1,999):

if palindromic(set1 * set2) :

if (set1 * set2) > palin :

palin =(set1*set2)

print(‘\n We found it:’,palin, ‘coming from {} * {}’.format(set1,set2))






Follow me on Twitter..



Advertisements

Python: Number Letter Counts



Python: Number Letter Counts
Problem 17, Projecteuler

For problem 17, projectEuler ask for the total numbers of alphabetics in all words of numbers from 1 to 1000.

Here I am coping from there page.

Once I read the task, I decide to create my own version of the requirement. I start to assume that I may have a dictionary with some numbers and words, then base on what ever the user will input (number between 1 and 999) then I shall convert it to words.

Example:
1 –> one
8 –> eight
234 –> tow hundred thirty-four .. and so on.


I start searching the net to get the words I need, and store them in 3 dictionaries.

num_1_9 = {“1″:”one”,”2″:”two” .. ext.
num_10s = {“10″:”ten”,”20″:”twenty” .. ext.
num_11s = {“11″:”eleven”,”12″:”twelve”.. ext


Then, I start writing the functions for each group of numbers/dictionaries, so if the user enter a number we will read number of digits if it is 1 then we call def num_1_d(), if it is 2 digits we call def num_2_ds() and if it is 3 digits we call num_3_ds(). At the end, we got the right answer for Projecteuler, and here is the code in my way, I am asking the user to enter a number then i convert it to a corresponding words.



The Code:



# Date:27/6/2019
# ProjectEuler
# Problem No.17
# Completed on Sun, 30 Jun 2019, 10:30


num_1_9 = {“1″:”one”,”2″:”two”,”3″:”three”,”4″:”four”,”5″:”five”,”6″:”six”,”7″:”seven”,”8″:”eight”,”9″:”nine”}

num_11s={“11″:”eleven”,”12″:”twelve”,”13″:”thirteen”,”14″:”fourteen”,”15″:”fifteen”,”16″:”sixteen”,”17″:”seventeen”,”18″:”eighteen”,”19″:”nineteen”}

num_10s ={“10″:”ten”,”20″:”twenty”,”30″:”thirty”,”40″:”forty”,”50″:”fifty”,”60″:”sixty”,”70″:”seventy”,”80″:”eighty”,”90″:”ninety”}

num_100=’hundred’

def num_1_d(num):

if len(str(num)) == 1:

return num_1_9[str(num)]

def num_2_ds(num):

d0,d1 = num[0], num[1]

if int(num[1])== 0 :

return num_10s[str(num)]

elif int(num[0]) == 1 :

return num_11s[str(num)]

elif (int(num[0])) >1 :

d0=str(d0)+str(0)

return ‘{}-{}’.format(num_10s[str(d0)],num_1_9[str(d1)])

def num_3_ds (num):

d0,d1,d2=num[0],num[1],num[2]

if (int(num[1])==0) and (int(num[2])==0) :

return ‘{} {}’.format(num_1_9[str(d0)],num_100)

elif (int(num[1])>0):

d1 = str(d1)+str(d2)

return ‘{} {} and {}’.format(num_1_9[str(d0)],num_100,num_2_ds(d1))

elif (int(num[1])==0) and (int(num[2])>0):

d1 = str(d1)+str(d2)

return ‘{} {} and {}’.format(num_1_9[str(d0)],num_100,num_1_9[str(d2)])

num =0

while num !=’f’ :

num =input(‘\nEnter a number: (1-999)’)

if len(str(num)) == 1:

print(num ,’ is ‘,(num_1_d(num)))

elif len(str(num)) == 2:

print (num ,’ is ‘,(num_2_ds(num)))

elif len(str(num)) == 3:

print (num ,’ is ‘,(num_3_ds(num)))




This is Output screen for my-way version



Follow me on Twitter..



Python: 10001st Prime



Python: 10001st Prime
Problem No.7 @ ProjectEuler

This is one of shot projects you may find on ProjectEuler, the task is find the prime No 10001, I just run my is_prime function, if the number is prime will add 1 to the counter, until we reach 10001, that will be the answer.



The Code:



# 10001st prime
# Problem 7
# Solved: Wed, 26 Jun 2019, 05:57am (GMT+3)

def is_prime(num):

result = True

for t in range (2,num):

if num%t==0 :

result= False

break

return result

p_count=0
num =0
while p_count <=10001:

num +=1

if is_prime (num):

p_count +=1

print(p_count,num)
print(num,p_count-1)






Follow me on Twitter..



Python: 1000-Digit Fibonacci



Python: 1000-Digit Fibonacci
Problem No.25, ProjectEuler

Another easy fast 5-minites task on projecteuler that Playing around Fibonacci Numbers, the task is to find the first Fibonacci index to contain 1000 digits.

So we will write a function to get the fibonacci numbers and each time we will check if it’s digits reach 1000, if not we will go for generating the next number.



The Code:



#1000-digit Fibonacci number
# problem no 25
# Solved.

def get_fibonacci():

x=1

fibo=[1,1]

while len(str(fibo[x])) != 1000:

fibo.append(fibo[-2]+fibo[-1])

x +=1

print(‘The index of the first term in the Fibonacci sequence to contain 1000 digits is ‘,x+1)

# Call the function
get_fibonacci()






Follow me on Twitter..



Python: Even Fibonacci Numbers



Python: Even Fibonacci Numbers
ProjectEuler Problem No.2

Easy fast task in ProjectEuler, The Task is to find the sum of the even-valued terms in Fibonacci sequence whose values do not exceed four million.

In this code we will add some print-statment to just show how mane even numbers there and the summation of it.



The Code:


# Even Fibonacci Numbers
# projectEuler Problem No. 2

def get_fibonacci_sequence():

n1 = 1

n2 = 1

fibo = 1

while fibo < 4000000:

fibo = n1+n2

n1 = n2

n2 = fibo

if fibo% 2 == 0:

even_fibo_num.append(fibo)

tot = 0
even_fibo_num = []
get_fibonacci_sequence()
print(‘\n We fond {} even fibonacci”s number less than 4000000.’.format(len(even_fibo_num)))
for each in even_fibo_num:

tot = tot + each

print(‘ The summation on those even Fibonacci”s is: ‘, tot)






Follow me on Twitter..



Python: Square Digit Chain



Python: Square Digit Chain
ProjectEuler Problem No.92

Here we have a mathematical definition called Happy Number..

A Happy Number is defined by the following process:

Starting with any positive integer, replace the number by the sum of the squares of its digits in base-ten, and repeat the process until the number either:
equals 1 (where it will stay), or
it loops endlessly in a cycle that does not include 1.
(Wikipedia).


In ProjectEuler the task stated in this problem as ” How many starting numbers below ten million will arrive at 89?”

Enhancement: Here we will do something else, we will try to solve the task and post the answer to the projecteuler portal, BUT we are not talking about this here, we will use the concept of this task to generate chains of looped number and I will use it later in another post (project) and trying to represent this chains in a graphic way.

So to do this we need two functions, First one will read a number, get its digits, squaring each digit and get the summation. To keep our eyes on the numbers we need to store it, so we will use list called the_chain.

To check if we have reach a closed chain then we need to ask if the new number (sum of square digit) exists in the chain list or not. If exists we finish and will return the chain for more manipulating.


I will solve this on my way .. 🙂

In this code we will do the following:

1. We will ask the user to enter a number.

2. We will run the function on that number.

3. Outputs:

If we ends with 1 then we have a Happy Number.

If we have closed chain (current number exists in the chain) then we will have tow cases:

If the current number is the same as the start number, then we will call this “Perfect Chain“. Otherwise we will call it “Tail Chain



The Code:


# Square digit chain.
# Pprojecteuler problem No 92

num = 1
the_chain=[]

def get_square_digit_chain(n):

tot=0

the_chain.append(n)

while n != 0:

tot=0

for each in str(n):

tot= tot + int(each)**2

n = tot

if n in the_chain:

return n

else:

the_chain.append(n)

#We ask the user to enter a number.
num =int(input(“Enter a number “))

chain_closed = get_square_digit_chain(num)
if chain_closed == 1:

print(“We have a Happy Number”)

print(the_chain,’This is Open Chain’)
else:

if chain_closed == num:

print(“We have a Perfect Chain”)

print(the_chain,’Closed on’,chain_closed)

else:

print(“We have a Tail Chain”)

print(the_chain,’Closed on’,chain_closed)






Follow me on Twitter..



Python : Triangle Number



Python: Triangle Number
Projecteuler problem No.42

With Problem 42, we have to read a file containing nearly two-thousand common English words and find how many are triangle words?

Difinetion: Triangle Words: If we give each alphabetical in English language a value related to its corresponding location such as A=1, B=2, C=3 and so on, then we convert the word to a value based on a sum of its characters values, we can said that a word is a triangular if its value equal to sequence in a Triangular Number formula.


Triangular Number formula:
Tn =(n/2)*(n+1)

Example.. If we have a word “SKY”, We will find that:
The Value of S=19
The Value of K= 11
The value of Y= 25

The Total is (19+11+25) = 55

(55) is a number in the Triangular Number Sequence n=10
T10=(10/2)*(10+1)
=5*11
=55


Notes In this task, I will not write a code to read the text-file, but i will copy-paste it in a variable called “The_words”.

The words:
The_words=(“A”,”ABILITY”,”ABLE”,”ABOUT”,”ABOVE”,”ABSENCE”,”ABSOLUTELY”,”ACADEMIC”,”ACCEPT”,”ACCESS”, “ACCIDENT”,”ACCOMPANY”,”ACCORDING”,”ACCOUNT”,”ACHIEVE”,”ACHIEVEMENT”,”ACID”,”ACQUIRE”, “ACROSS”,”ACT”,”ACTION”,”ACTIVE”,”ACTIVITY”,”ACTUAL”,”ACTUALLY”,”ADD”,”ADDITION”,”ADDITIONAL”,”ADDRESS”,”ADMINISTRATION”,”ADMIT”,”ADOPT”,”ADULT”,”ADVANCE”,”ADVANTAGE”,”ADVICE”,”ADVISE”,”AFFAIR”, “AFFECT”,”AFFORD”,”AFRAID”,”AFTER”,”AFTERNOON”,”AFTERWARDS”,”AGAIN”,”AGAINST”,”AGE”,”AGENCY”,”AGENT”,”AGO”,”AGREE”,”AGREEMENT”,”AHEAD”,”AID”,”AIM”,”AIR”,”AIRCRAFT”,”ALL”,”ALLOW”,”ALMOST”, “ALONE”,”ALONG”,”ALREADY”,”ALRIGHT”,”ALSO”,”ALTERNATIVE”,”ALTHOUGH”,”ALWAYS”,”AMONG”,”AMONGST”, “AMOUNT”,”AN”,”ANALYSIS”,”ANCIENT”,”AND”,”ANIMAL”,”ANNOUNCE”,”ANNUAL”,”ANOTHER”,”ANSWER”,”ANY”, “ANYBODY”,”ANYONE”,”ANYTHING”,”ANYWAY”,”APART”,”APPARENT”,”APPARENTLY”,”APPEAL”,”APPEAR”,”APPEARANCE”,”APPLICATION”,”APPLY”,”APPOINT”,”APPOINTMENT”,”APPROACH”,”APPROPRIATE”,”APPROVE”,”AREA”,”ARGUE”, “ARGUMENT”,”ARISE”,”ARM”,”ARMY”,”AROUND”,”ARRANGE”,”ARRANGEMENT”,”ARRIVE”,”ART”,”ARTICLE”, “ARTIST”,”AS”,”ASK”,”ASPECT”,”ASSEMBLY”,”ASSESS”,”ASSESSMENT”,”ASSET”,”ASSOCIATE”,”ASSOCIATION”,”ASSUME”,”ASSUMPTION”,”AT”,”ATMOSPHERE”,”ATTACH”,”ATTACK”,”ATTEMPT”,”ATTEND”,”ATTENTION”,”ATTITUDE”, “ATTRACT”,”ATTRACTIVE”,”AUDIENCE”,”AUTHOR”,”AUTHORITY”,”AVAILABLE”,”AVERAGE”,”AVOID”,”AWARD”, “AWARE”,”AWAY”,”AYE”,”BABY”,”BACK”,”BACKGROUND”,”BAD”,”BAG”,”BALANCE”,”BALL”,”BAND”,”BANK”, “BAR”,”BASE”,”BASIC”,”BASIS”,”BATTLE”,”BE”,”BEAR”,”BEAT”,”BEAUTIFUL”,”BECAUSE”,”BECOME”,”BED”,”BEDROOM”,”BEFORE”,”BEGIN”,”BEGINNING”,”BEHAVIOUR”,”BEHIND”,”BELIEF”,”BELIEVE”,”BELONG”,”BELOW”, “BENEATH”,”BENEFIT”,”BESIDE”,”BEST”,”BETTER”,”BETWEEN”,”BEYOND”,”BIG”,”BILL”,”BIND”,”BIRD”, “BIRTH”,”BIT”,”BLACK”,”BLOCK”,”BLOOD”,”BLOODY”,”BLOW”,”BLUE”,”BOARD”,”BOAT”,”BODY”,”BONE”, “BOOK”,”BORDER”,”BOTH”,”BOTTLE”,”BOTTOM”,”BOX”,”BOY”,”BRAIN”,”BRANCH”,”BREAK”,”BREATH”,”BRIDGE”,”BRIEF”,”BRIGHT”,”BRING”,”BROAD”,”BROTHER”,”BUDGET”,”BUILD”,”BUILDING”,”BURN”,”BUS”,”BUSINESS”, “BUSY”,”BUT”,”BUY”,”BY”,”CABINET”,”CALL”,”CAMPAIGN”,”CAN”,”CANDIDATE”,”CAPABLE”,”CAPACITY”,”CAPITAL”,”CAR”,”CARD”,”CARE”,”CAREER”,”CAREFUL”,”CAREFULLY”,”CARRY”,”CASE”,”CASH”,”CAT”,”CATCH”, “CATEGORY”,”CAUSE”,”CELL”,”CENTRAL”,”CENTRE”,”CENTURY”,”CERTAIN”,”CERTAINLY”,”CHAIN”,”CHAIR”,”CHAIRMAN”,”CHALLENGE”,”CHANCE”,”CHANGE”,”CHANNEL”,”CHAPTER”,”CHARACTER”,”CHARACTERISTIC”,”CHARGE”, “CHEAP”,”CHECK”,”CHEMICAL”,”CHIEF”,”CHILD”,”CHOICE”,”CHOOSE”,”CHURCH”,”CIRCLE”,”CIRCUMSTANCE”,”CITIZEN”,”CITY”,”CIVIL”,”CLAIM”,”CLASS”,”CLEAN”,”CLEAR”,”CLEARLY”,”CLIENT”,”CLIMB”,”CLOSE”, “CLOSELY”,”CLOTHES”,”CLUB”,”COAL”,”CODE”,”COFFEE”,”COLD”,”COLLEAGUE”,”COLLECT”,”COLLECTION”,”COLLEGE”,”COLOUR”,”COMBINATION”,”COMBINE”,”COME”,”COMMENT”,”COMMERCIAL”,”COMMISSION”,”COMMIT”, “COMMITMENT”,”COMMITTEE”,”COMMON”,”COMMUNICATION”,”COMMUNITY”,”COMPANY”,”COMPARE”,”COMPARISON”, “COMPETITION”,”COMPLETE”,”COMPLETELY”,”COMPLEX”,”COMPONENT”,”COMPUTER”,”CONCENTRATE”,”CONCENTRATION”,”CONCEPT”,”CONCERN”,”CONCERNED”,”CONCLUDE”,”CONCLUSION”,”CONDITION”,”CONDUCT”,”CONFERENCE”,”CONFIDENCE”,”CONFIRM”,”CONFLICT”,”CONGRESS”,”CONNECT”,”CONNECTION”,”CONSEQUENCE”,”CONSERVATIVE”,”CONSIDER”, “CONSIDERABLE”,”CONSIDERATION”,”CONSIST”,”CONSTANT”,”CONSTRUCTION”,”CONSUMER”,”CONTACT”,”CONTAIN”,”CONTENT”,”CONTEXT”,”CONTINUE”,”CONTRACT”,”CONTRAST”,”CONTRIBUTE”,”CONTRIBUTION”,”CONTROL”, “CONVENTION”,”CONVERSATION”,”COPY”,”CORNER”,”CORPORATE”,”CORRECT”,”COS”,”COST”,”COULD”,”COUNCIL”,”COUNT”,”COUNTRY”,”COUNTY”,”COUPLE”,”COURSE”,”COURT”,”COVER”,”CREATE”,”CREATION”,”CREDIT”, “CRIME”,”CRIMINAL”,”CRISIS”,”CRITERION”,”CRITICAL”,”CRITICISM”,”CROSS”,”CROWD”,”CRY”,”CULTURAL”, “CULTURE”,”CUP”,”CURRENT”,”CURRENTLY”,”CURRICULUM”,”CUSTOMER”,”CUT”,”DAMAGE”,”DANGER”,”DANGEROUS”, “DARK”,”DATA”,”DATE”,”DAUGHTER”,”DAY”,”DEAD”,”DEAL”,”DEATH”,”DEBATE”,”DEBT”,”DECADE”,”DECIDE”, “DECISION”,”DECLARE”,”DEEP”,”DEFENCE”,”DEFENDANT”,”DEFINE”,”DEFINITION”,”DEGREE”,”DELIVER”,”DEMAND”, “DEMOCRATIC”,”DEMONSTRATE”,”DENY”,”DEPARTMENT”,”DEPEND”,”DEPUTY”,”DERIVE”,”DESCRIBE”,”DESCRIPTION”, “DESIGN”,”DESIRE”,”DESK”,”DESPITE”,”DESTROY”,”DETAIL”,”DETAILED”,”DETERMINE”,”DEVELOP”,”DEVELOPMENT”, “DEVICE”,”DIE”,”DIFFERENCE”,”DIFFERENT”,”DIFFICULT”,”DIFFICULTY”,”DINNER”,”DIRECT”,”DIRECTION”, “DIRECTLY”,”DIRECTOR”,”DISAPPEAR”,”DISCIPLINE”,”DISCOVER”,”DISCUSS”,”DISCUSSION”,”DISEASE”, “DISPLAY”,”DISTANCE”,”DISTINCTION”,”DISTRIBUTION”,”DISTRICT”,”DIVIDE”,”DIVISION”,”DO”,”DOCTOR”, “DOCUMENT”,”DOG”,”DOMESTIC”,”DOOR”,”DOUBLE”,”DOUBT”,”DOWN”,”DRAW”,”DRAWING”,”DREAM”,”DRESS”,”DRINK”, “DRIVE”,”DRIVER”,”DROP”,”DRUG”,”DRY”,”DUE”,”DURING”,”DUTY”,”EACH”,”EAR”,”EARLY”,”EARN”,”EARTH”, “EASILY”,”EAST”,”EASY”,”EAT”,”ECONOMIC”,”ECONOMY”,”EDGE”,”EDITOR”,”EDUCATION”,”EDUCATIONAL”,”EFFECT”, “EFFECTIVE”,”EFFECTIVELY”,”EFFORT”,”EGG”,”EITHER”,”ELDERLY”,”ELECTION”,”ELEMENT”,”ELSE”,”ELSEWHERE”, “EMERGE”,”EMPHASIS”,”EMPLOY”,”EMPLOYEE”,”EMPLOYER”,”EMPLOYMENT”,”EMPTY”,”ENABLE”,”ENCOURAGE”,”END”, “ENEMY”,”ENERGY”,”ENGINE”,”ENGINEERING”,”ENJOY”,”ENOUGH”,”ENSURE”,”ENTER”,”ENTERPRISE”,”ENTIRE”, “ENTIRELY”,”ENTITLE”,”ENTRY”,”ENVIRONMENT”,”ENVIRONMENTAL”,”EQUAL”,”EQUALLY”,”EQUIPMENT”,”ERROR”, “ESCAPE”,”ESPECIALLY”,”ESSENTIAL”,”ESTABLISH”,”ESTABLISHMENT”,”ESTATE”,”ESTIMATE”,”EVEN”,”EVENING”, “EVENT”,”EVENTUALLY”,”EVER”,”EVERY”,”EVERYBODY”,”EVERYONE”,”EVERYTHING”,”EVIDENCE”,”EXACTLY”, “EXAMINATION”,”EXAMINE”,”EXAMPLE”,”EXCELLENT”,”EXCEPT”,”EXCHANGE”,”EXECUTIVE”,”EXERCISE”,”EXHIBITION”, “EXIST”,”EXISTENCE”,”EXISTING”,”EXPECT”,”EXPECTATION”,”EXPENDITURE”,”EXPENSE”,”EXPENSIVE”, “EXPERIENCE”,”EXPERIMENT”,”EXPERT”,”EXPLAIN”,”EXPLANATION”,”EXPLORE”,”EXPRESS”,”EXPRESSION”, “EXTEND”,”EXTENT”,”EXTERNAL”,”EXTRA”,”EXTREMELY”,”EYE”,”FACE”,”FACILITY”,”FACT”,”FACTOR”, “FACTORY”,”FAIL”,”FAILURE”,”FAIR”,”FAIRLY”,”FAITH”,”FALL”,”FAMILIAR”,”FAMILY”,”FAMOUS”,”FAR”, “FARM”,”FARMER”,”FASHION”,”FAST”,”FATHER”,”FAVOUR”,”FEAR”,”FEATURE”,”FEE”,”FEEL”,”FEELING”, “FEMALE”,”FEW”,”FIELD”,”FIGHT”,”FIGURE”,”FILE”,”FILL”,”FILM”,”FINAL”,”FINALLY”,”FINANCE”,”FINANCIAL”, “FIND”,”FINDING”,”FINE”,”FINGER”,”FINISH”,”FIRE”,”FIRM”,”FIRST”,”FISH”,”FIT”,”FIX”,”FLAT”, “FLIGHT”,”FLOOR”,”FLOW”,”FLOWER”,”FLY”,”FOCUS”,”FOLLOW”,”FOLLOWING”,”FOOD”,”FOOT”,”FOOTBALL”, “FOR”,”FORCE”,”FOREIGN”,”FOREST”,”FORGET”,”FORM”,”FORMAL”,”FORMER”,”FORWARD”,”FOUNDATION”,”FREE”, “FREEDOM”,”FREQUENTLY”,”FRESH”,”FRIEND”,”FROM”,”FRONT”,”FRUIT”,”FUEL”,”FULL”,”FULLY”,”FUNCTION”,”FUND”,”FUNNY”,”FURTHER”,”FUTURE”,”GAIN”,”GAME”,”GARDEN”,”GAS”,”GATE”,”GATHER”,”GENERAL”,”GENERALLY”,”GENERATE”,”GENERATION”,”GENTLEMAN”,”GET”,”GIRL”,”GIVE”,”GLASS”,”GO”,”GOAL”,”GOD”,”GOLD”,”GOOD”,”GOVERNMENT”,”GRANT”,”GREAT”,”GREEN”,”GREY”,”GROUND”,”GROUP”,”GROW”,”GROWING”,”GROWTH”,”GUEST”,”GUIDE”,”GUN”,”HAIR”,”HALF”,”HALL”,”HAND”,”HANDLE”,”HANG”,”HAPPEN”,”HAPPY”,”HARD”,”HARDLY”,”HATE”,”HAVE”,”HE”,”HEAD”,”HEALTH”,”HEAR”,”HEART”,”HEAT”,”HEAVY”,”HELL”,”HELP”,”HENCE”,”HER”,”HERE”,”HERSELF”,”HIDE”,”HIGH”,”HIGHLY”,”HILL”,”HIM”,”HIMSELF”,”HIS”,”HISTORICAL”,”HISTORY”,”HIT”,”HOLD”,”HOLE”,”HOLIDAY”,”HOME”,”HOPE”,”HORSE”,”HOSPITAL”,”HOT”,”HOTEL”,”HOUR”,”HOUSE”,”HOUSEHOLD”,”HOUSING”,”HOW”,”HOWEVER”,”HUGE”,”HUMAN”,”HURT”,”HUSBAND”,”I”,”IDEA”,”IDENTIFY”,”IF”,”IGNORE”,”ILLUSTRATE”,”IMAGE”,”IMAGINE”,”IMMEDIATE”,”IMMEDIATELY”,”IMPACT”,”IMPLICATION”,”IMPLY”,”IMPORTANCE”,”IMPORTANT”,”IMPOSE”,”IMPOSSIBLE”,”IMPRESSION”,”IMPROVE”,”IMPROVEMENT”,”IN”,”INCIDENT”,”INCLUDE”,”INCLUDING”,”INCOME”,”INCREASE”,”INCREASED”,”INCREASINGLY”,”INDEED”,”INDEPENDENT”,”INDEX”,”INDICATE”,”INDIVIDUAL”,”INDUSTRIAL”,”INDUSTRY”,”INFLUENCE”,”INFORM”,”INFORMATION”,”INITIAL”,”INITIATIVE”,”INJURY”,”INSIDE”,”INSIST”,”INSTANCE”,”INSTEAD”,”INSTITUTE”,”INSTITUTION”,”INSTRUCTION”,”INSTRUMENT”,”INSURANCE”,”INTEND”,”INTENTION”,”INTEREST”,”INTERESTED”,”INTERESTING”,”INTERNAL”,”INTERNATIONAL”,”INTERPRETATION”,”INTERVIEW”,”INTO”,”INTRODUCE”,”INTRODUCTION”,”INVESTIGATE”,”INVESTIGATION”,”INVESTMENT”,”INVITE”,”INVOLVE”,”IRON”,”IS”,”ISLAND”,”ISSUE”,”IT”,”ITEM”,”ITS”,”ITSELF”,”JOB”,”JOIN”,”JOINT”,”JOURNEY”,”JUDGE”,”JUMP”,”JUST”,”JUSTICE”,”KEEP”,”KEY”,”KID”,”KILL”,”KIND”,”KING”,”KITCHEN”,”KNEE”,”KNOW”,”KNOWLEDGE”,”LABOUR”,”LACK”,”LADY”,”LAND”,”LANGUAGE”,”LARGE”,”LARGELY”,”LAST”,”LATE”,”LATER”,”LATTER”,”LAUGH”,”LAUNCH”,”LAW”,”LAWYER”,”LAY”,”LEAD”,”LEADER”,”LEADERSHIP”,”LEADING”,”LEAF”,”LEAGUE”,”LEAN”,”LEARN”,”LEAST”,”LEAVE”,”LEFT”,”LEG”,”LEGAL”,”LEGISLATION”,”LENGTH”,”LESS”,”LET”,”LETTER”,”LEVEL”,”LIABILITY”,”LIBERAL”,”LIBRARY”,”LIE”,”LIFE”,”LIFT”,”LIGHT”,”LIKE”,”LIKELY”,”LIMIT”,”LIMITED”,”LINE”,”LINK”,”LIP”,”LIST”,”LISTEN”,”LITERATURE”,”LITTLE”,”LIVE”,”LIVING”,”LOAN”,”LOCAL”,”LOCATION”,”LONG”,”LOOK”,”LORD”,”LOSE”,”LOSS”,”LOT”,”LOVE”,”LOVELY”,”LOW”,”LUNCH”,”MACHINE”,”MAGAZINE”,”MAIN”,”MAINLY”,”MAINTAIN”,”MAJOR”,”MAJORITY”,”MAKE”,”MALE”,”MAN”,”MANAGE”,”MANAGEMENT”,”MANAGER”,”MANNER”,”MANY”,”MAP”,”MARK”,”MARKET”,”MARRIAGE”,”MARRIED”,”MARRY”,”MASS”,”MASTER”,”MATCH”,”MATERIAL”,”MATTER”,”MAY”,”MAYBE”,”ME”,”MEAL”,”MEAN”,”MEANING”,”MEANS”,”MEANWHILE”,”MEASURE”,”MECHANISM”,”MEDIA”,”MEDICAL”,”MEET”,”MEETING”,”MEMBER”,”MEMBERSHIP”,”MEMORY”,”MENTAL”,”MENTION”,”MERELY”,”MESSAGE”,”METAL”,”METHOD”,”MIDDLE”,”MIGHT”,”MILE”,”MILITARY”,”MILK”,”MIND”,”MINE”,”MINISTER”,”MINISTRY”,”MINUTE”,”MISS”,”MISTAKE”,”MODEL”,”MODERN”,”MODULE”,”MOMENT”,”MONEY”,”MONTH”,”MORE”,”MORNING”,”MOST”,”MOTHER”,”MOTION”,”MOTOR”,”MOUNTAIN”,”MOUTH”,”MOVE”,”MOVEMENT”,”MUCH”,”MURDER”,”MUSEUM”,”MUSIC”,”MUST”,”MY”,”MYSELF”,”NAME”,”NARROW”,”NATION”,”NATIONAL”,”NATURAL”,”NATURE”,”NEAR”,”NEARLY”,”NECESSARILY”,”NECESSARY”,”NECK”,”NEED”,”NEGOTIATION”,”NEIGHBOUR”,”NEITHER”,”NETWORK”,”NEVER”,”NEVERTHELESS”,”NEW”,”NEWS”,”NEWSPAPER”,”NEXT”,”NICE”,”NIGHT”,”NO”,”NOBODY”,”NOD”,”NOISE”,”NONE”,”NOR”,”NORMAL”,”NORMALLY”,”NORTH”,”NORTHERN”,”NOSE”,”NOT”,”NOTE”,”NOTHING”,”NOTICE”,”NOTION”,”NOW”,”NUCLEAR”,”NUMBER”,”NURSE”,”OBJECT”,”OBJECTIVE”,”OBSERVATION”,”OBSERVE”,”OBTAIN”,”OBVIOUS”,”OBVIOUSLY”,”OCCASION”,”OCCUR”,”ODD”,”OF”,”OFF”,”OFFENCE”,”OFFER”,”OFFICE”,”OFFICER”,”OFFICIAL”,”OFTEN”,”OIL”,”OKAY”,”OLD”,”ON”,”ONCE”,”ONE”,”ONLY”,”ONTO”,”OPEN”,”OPERATE”,”OPERATION”,”OPINION”,”OPPORTUNITY”,”OPPOSITION”,”OPTION”,”OR”,”ORDER”,”ORDINARY”,”ORGANISATION”,”ORGANISE”,”ORGANIZATION”,”ORIGIN”,”ORIGINAL”,”OTHER”,”OTHERWISE”,”OUGHT”,”OUR”,”OURSELVES”,”OUT”,”OUTCOME”,”OUTPUT”,”OUTSIDE”,”OVER”,”OVERALL”,”OWN”,”OWNER”,”PACKAGE”,”PAGE”,”PAIN”,”PAINT”,”PAINTING”,”PAIR”,”PANEL”,”PAPER”,”PARENT”,”PARK”,”PARLIAMENT”,”PART”,”PARTICULAR”,”PARTICULARLY”,”PARTLY”,”PARTNER”,”PARTY”,”PASS”,”PASSAGE”,”PAST”,”PATH”,”PATIENT”,”PATTERN”,”PAY”,”PAYMENT”,”PEACE”,”PENSION”,”PEOPLE”,”PER”,”PERCENT”,”PERFECT”,”PERFORM”,”PERFORMANCE”,”PERHAPS”,”PERIOD”,”PERMANENT”,”PERSON”,”PERSONAL”,”PERSUADE”,”PHASE”,”PHONE”,”PHOTOGRAPH”,”PHYSICAL”,”PICK”,”PICTURE”,”PIECE”,”PLACE”,”PLAN”,”PLANNING”,”PLANT”,”PLASTIC”,”PLATE”,”PLAY”,”PLAYER”,”PLEASE”,”PLEASURE”,”PLENTY”,”PLUS”,”POCKET”,”POINT”,”POLICE”,”POLICY”,”POLITICAL”,”POLITICS”,”POOL”,”POOR”,”POPULAR”,”POPULATION”,”POSITION”,”POSITIVE”,”POSSIBILITY”,”POSSIBLE”,”POSSIBLY”,”POST”,”POTENTIAL”,”POUND”,”POWER”,”POWERFUL”,”PRACTICAL”,”PRACTICE”,”PREFER”,”PREPARE”,”PRESENCE”,”PRESENT”,”PRESIDENT”,”PRESS”,”PRESSURE”,”PRETTY”,”PREVENT”,”PREVIOUS”,”PREVIOUSLY”,”PRICE”,”PRIMARY”,”PRIME”,”PRINCIPLE”,”PRIORITY”,”PRISON”,”PRISONER”,”PRIVATE”,”PROBABLY”,”PROBLEM”,”PROCEDURE”,”PROCESS”,”PRODUCE”,”PRODUCT”,”PRODUCTION”,”PROFESSIONAL”,”PROFIT”,”PROGRAM”,”PROGRAMME”,”PROGRESS”,”PROJECT”,”PROMISE”,”PROMOTE”,”PROPER”,”PROPERLY”,”PROPERTY”,”PROPORTION”,”PROPOSE”,”PROPOSAL”,”PROSPECT”,”PROTECT”,”PROTECTION”,”PROVE”,”PROVIDE”,”PROVIDED”,”PROVISION”,”PUB”,”PUBLIC”,”PUBLICATION”,”PUBLISH”,”PULL”,”PUPIL”,”PURPOSE”,”PUSH”,”PUT”,”QUALITY”,”QUARTER”,”QUESTION”,”QUICK”,”QUICKLY”,”QUIET”,”QUITE”,”RACE”,”RADIO”,”RAILWAY”,”RAIN”,”RAISE”,”RANGE”,”RAPIDLY”,”RARE”,”RATE”,”RATHER”,”REACH”,”REACTION”,”READ”,”READER”,”READING”,”READY”,”REAL”,”REALISE”,”REALITY”,”REALIZE”,”REALLY”,”REASON”,”REASONABLE”,”RECALL”,”RECEIVE”,”RECENT”,”RECENTLY”,”RECOGNISE”,”RECOGNITION”,”RECOGNIZE”,”RECOMMEND”,”RECORD”,”RECOVER”,”RED”,”REDUCE”,”REDUCTION”,”REFER”,”REFERENCE”,”REFLECT”,”REFORM”,”REFUSE”,”REGARD”,”REGION”,”REGIONAL”,”REGULAR”,”REGULATION”,”REJECT”,”RELATE”,”RELATION”,”RELATIONSHIP”,”RELATIVE”,”RELATIVELY”,”RELEASE”,”RELEVANT”,”RELIEF”,”RELIGION”,”RELIGIOUS”,”RELY”,”REMAIN”,”REMEMBER”,”REMIND”,”REMOVE”,”REPEAT”,”REPLACE”,”REPLY”,”REPORT”,”REPRESENT”,”REPRESENTATION”,”REPRESENTATIVE”,”REQUEST”,”REQUIRE”,”REQUIREMENT”,”RESEARCH”,”RESOURCE”,”RESPECT”,”RESPOND”,”RESPONSE”,”RESPONSIBILITY”,”RESPONSIBLE”,”REST”,”RESTAURANT”,”RESULT”,”RETAIN”,”RETURN”,”REVEAL”,”REVENUE”,”REVIEW”,”REVOLUTION”,”RICH”,”RIDE”,”RIGHT”,”RING”,”RISE”,”RISK”,”RIVER”,”ROAD”,”ROCK”,”ROLE”,”ROLL”,”ROOF”,”ROOM”,”ROUND”,”ROUTE”,”ROW”,”ROYAL”,”RULE”,”RUN”,”RURAL”,”SAFE”,”SAFETY”,”SALE”,”SAME”,”SAMPLE”,”SATISFY”,”SAVE”,”SAY”,”SCALE”,”SCENE”,”SCHEME”,”SCHOOL”,”SCIENCE”,”SCIENTIFIC”,”SCIENTIST”,”SCORE”,”SCREEN”,”SEA”,”SEARCH”,”SEASON”,”SEAT”,”SECOND”,”SECONDARY”,”SECRETARY”,”SECTION”,”SECTOR”,”SECURE”,”SECURITY”,”SEE”,”SEEK”,”SEEM”,”SELECT”,”SELECTION”,”SELL”,”SEND”,”SENIOR”,”SENSE”,”SENTENCE”,”SEPARATE”,”SEQUENCE”,”SERIES”,”SERIOUS”,”SERIOUSLY”,”SERVANT”,”SERVE”,”SERVICE”,”SESSION”,”SET”,”SETTLE”,”SETTLEMENT”,”SEVERAL”,”SEVERE”,”SEX”,”SEXUAL”,”SHAKE”,”SHALL”,”SHAPE”,”SHARE”,”SHE”,”SHEET”,”SHIP”,”SHOE”,”SHOOT”,”SHOP”,”SHORT”,”SHOT”,”SHOULD”,”SHOULDER”,”SHOUT”,”SHOW”,”SHUT”,”SIDE”,”SIGHT”,”SIGN”,”SIGNAL”,”SIGNIFICANCE”,”SIGNIFICANT”,”SILENCE”,”SIMILAR”,”SIMPLE”,”SIMPLY”,”SINCE”,”SING”,”SINGLE”,”SIR”,”SISTER”,”SIT”,”SITE”,”SITUATION”,”SIZE”,”SKILL”,”SKIN”,”SKY”,”SLEEP”,”SLIGHTLY”,”SLIP”,”SLOW”,”SLOWLY”,”SMALL”,”SMILE”,”SO”,”SOCIAL”,”SOCIETY”,”SOFT”,”SOFTWARE”,”SOIL”,”SOLDIER”,”SOLICITOR”,”SOLUTION”,”SOME”,”SOMEBODY”,”SOMEONE”,”SOMETHING”,”SOMETIMES”,”SOMEWHAT”,”SOMEWHERE”,”SON”,”SONG”,”SOON”,”SORRY”,”SORT”,”SOUND”,”SOURCE”,”SOUTH”,”SOUTHERN”,”SPACE”,”SPEAK”,”SPEAKER”,”SPECIAL”,”SPECIES”,”SPECIFIC”,”SPEECH”,”SPEED”,”SPEND”,”SPIRIT”,”SPORT”,”SPOT”,”SPREAD”,”SPRING”,”STAFF”,”STAGE”,”STAND”,”STANDARD”,”STAR”,”START”,”STATE”,”STATEMENT”,”STATION”,”STATUS”,”STAY”,”STEAL”,”STEP”,”STICK”,”STILL”,”STOCK”,”STONE”,”STOP”,”STORE”,”STORY”,”STRAIGHT”,”STRANGE”,”STRATEGY”,”STREET”,”STRENGTH”,”STRIKE”,”STRONG”,”STRONGLY”,”STRUCTURE”,”STUDENT”,”STUDIO”,”STUDY”,”STUFF”,”STYLE”,”SUBJECT”,”SUBSTANTIAL”,”SUCCEED”,”SUCCESS”,”SUCCESSFUL”,”SUCH”,”SUDDENLY”,”SUFFER”,”SUFFICIENT”,”SUGGEST”,”SUGGESTION”,”SUITABLE”,”SUM”,”SUMMER”,”SUN”,”SUPPLY”,”SUPPORT”,”SUPPOSE”,”SURE”,”SURELY”,”SURFACE”,”SURPRISE”,”SURROUND”,”SURVEY”,”SURVIVE”,”SWITCH”,”SYSTEM”,”TABLE”,”TAKE”,”TALK”,”TALL”,”TAPE”,”TARGET”,”TASK”,”TAX”,”TEA”,”TEACH”,”TEACHER”,”TEACHING”,”TEAM”,”TEAR”,”TECHNICAL”,”TECHNIQUE”,”TECHNOLOGY”,”TELEPHONE”,”TELEVISION”,”TELL”,”TEMPERATURE”,”TEND”,”TERM”,”TERMS”,”TERRIBLE”,”TEST”,”TEXT”,”THAN”,”THANK”,”THANKS”,”THAT”,”THE”,”THEATRE”,”THEIR”,”THEM”,”THEME”,”THEMSELVES”,”THEN”,”THEORY”,”THERE”,”THEREFORE”,”THESE”,”THEY”,”THIN”,”THING”,”THINK”,”THIS”,”THOSE”,”THOUGH”,”THOUGHT”,”THREAT”,”THREATEN”,”THROUGH”,”THROUGHOUT”,”THROW”,”THUS”,”TICKET”,”TIME”,”TINY”,”TITLE”,”TO”,”TODAY”,”TOGETHER”,”TOMORROW”,”TONE”,”TONIGHT”,”TOO”,”TOOL”,”TOOTH”,”TOP”,”TOTAL”,”TOTALLY”,”TOUCH”,”TOUR”,”TOWARDS”,”TOWN”,”TRACK”,”TRADE”,”TRADITION”,”TRADITIONAL”,”TRAFFIC”,”TRAIN”,”TRAINING”,”TRANSFER”,”TRANSPORT”,”TRAVEL”,”TREAT”,”TREATMENT”,”TREATY”,”TREE”,”TREND”,”TRIAL”,”TRIP”,”TROOP”,”TROUBLE”,”TRUE”,”TRUST”,”TRUTH”,”TRY”,”TURN”,”TWICE”,”TYPE”,”TYPICAL”,”UNABLE”,”UNDER”,”UNDERSTAND”,”UNDERSTANDING”,”UNDERTAKE”,”UNEMPLOYMENT”,”UNFORTUNATELY”,”UNION”,”UNIT”,”UNITED”,”UNIVERSITY”,”UNLESS”,”UNLIKELY”,”UNTIL”,”UP”,”UPON”,”UPPER”,”URBAN”,”US”,”USE”,”USED”,”USEFUL”,”USER”,”USUAL”,”USUALLY”,”VALUE”,”VARIATION”,”VARIETY”,”VARIOUS”,”VARY”,”VAST”,”VEHICLE”,”VERSION”,”VERY”,”VIA”,”VICTIM”,”VICTORY”,”VIDEO”,”VIEW”,”VILLAGE”,”VIOLENCE”,”VISION”,”VISIT”,”VISITOR”,”VITAL”,”VOICE”,”VOLUME”,”VOTE”,”WAGE”,”WAIT”,”WALK”,”WALL”,”WANT”,”WAR”,”WARM”,”WARN”,”WASH”,”WATCH”,”WATER”,”WAVE”,”WAY”,”WE”,”WEAK”,”WEAPON”,”WEAR”,”WEATHER”,”WEEK”,”WEEKEND”,”WEIGHT”,”WELCOME”,”WELFARE”,”WELL”,”WEST”,”WESTERN”,”WHAT”,”WHATEVER”,”WHEN”,”WHERE”,”WHEREAS”,”WHETHER”,”WHICH”,”WHILE”,”WHILST”,”WHITE”,”WHO”,”WHOLE”,”WHOM”,”WHOSE”,”WHY”,”WIDE”,”WIDELY”,”WIFE”,”WILD”,”WILL”,”WIN”,”WIND”,”WINDOW”,”WINE”,”WING”,”WINNER”,”WINTER”,”WISH”,”WITH”,”WITHDRAW”,”WITHIN”,”WITHOUT”,”WOMAN”,”WONDER”,”WONDERFUL”,”WOOD”,”WORD”,”WORK”,”WORKER”,”WORKING”,”WORKS”,”WORLD”,”WORRY”,”WORTH”,”WOULD”,”WRITE”,”WRITER”,”WRITING”,”WRONG”,”YARD”,”YEAH”,”YEAR”,”YES”,”YESTERDAY”,”YET”,”YOU”,”YOUNG”,”YOUR”,”YOURSELF”,”YOUTH”)



alpha_value={“A”:1,”B”:2,”C”:3,”D”:4,”E”:5,”F”:6,”G”:7,”H”:8,”I”:9,”J”:10,”K”:11,”L”:12,
“M”:13,”N”:14,”O”:15,”P”:16,”Q”:17,”R”:18,”S”:19,”T”:20,”U”:21,”V”:22,”W”:23,”X”:24,”Y”:25,”Z”:26}

The Code:


# Function to get the word value
def get_word_value (the_word):

tot=0

for each in the_word:

tot = tot + alpha_value [each]

return tot

def triangle_numbers (the_value):

count_n = 1

while count_n <= the_value :

if ((count_n / 2) * (count_n + 1)) == the_value :

return True

break

else:

count_n = count_n + 1

return False

# Here we call each function and get the total_count of Triangle words
total_count=0

for each in The_words:

check_word =(each)

word_value = get_name_value (check_word)

if triangle_numbers (word_value) :

print (each,word_value,’True’)

total_count = total_count +1

print(‘Total Triangle Words=’,total_count)








Follow me on Twitter..