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Implement the function most_popular_character(my_string), which gets the string argument my_string and returns its most frequent letter. In case of a tie, break it by returning the letter of smaller ASCII value.
Note that lowercase and uppercase letters are considered different (e.g., ‘A’ < ‘a’). You may assume my_string consists of English letters only, and is not empty.
Example 1: >>> most_popular_character("HelloWorld") >>> 'l'
Example 2: >>> most_popular_character("gggcccbb") >>> 'c'
Explanation: cee and gee appear three times each (and bee twice), but cee precedes gee lexicographically.
Hints (you may ignore these):
Build a dictionary mapping letters to their frequency;
Find the largest frequency;
Find the smallest letter having that frequency.
def most_popular_character(my_string):
char_count = {} # define dictionary
for c in my_string:
if c in char_count: #if c is in the dictionary:
char_count[c] = 1
else: # if c isn't in the dictionary - create it and put 1
char_count[c] = 1
sorted_chars = sorted(char_count) # sort the dictionary
char_count = char_count.keys() # place the dictionary in a list
max_per = 0
for i in range(len(sorted_chars) - 1):
if sorted_chars[i] >= sorted_chars[i+1]:
max_per = sorted_chars[i]
break
return max_per
my function returns 0 right now, and I think the problem is in the last for loop and if statement - but I can't figure out what the problem is..
If you have any suggestions on how to adjust the code it would be very appreciated!
Your dictionary didn't get off to a good start by you forgetting to add 1 to the character count, instead you are resetting to 1 each time.
Have a look here to get the gist of getting the maximum value from a dict: https://datagy.io/python-get-dictionary-key-with-max-value/
def most_popular_character(my_string):
# NOTE: you might want to convert the entire sting to upper or lower case, first, depending on the use
# e.g. my_string = my_string.lower()
char_count = {} # define dictionary
for c in my_string:
if c in char_count: #if c is in the dictionary:
char_count[c] += 1 # add 1 to it
else: # if c isn't in the dictionary - create it and put 1
char_count[c] = 1
# Never under estimate the power of print in debugging
print(char_count)
# max(char_count.values()) will give the highest value
# But there may be more than 1 item with the highest count, so get them all
max_keys = [key for key, value in char_count.items() if value == max(char_count.values())]
# Choose the lowest by sorting them and pick the first item
low_item = sorted(max_keys)[0]
return low_item, max(char_count.values())
print(most_popular_character("HelloWorld"))
print(most_popular_character("gggcccbb"))
print(most_popular_character("gggHHHAAAAaaaccccbb 12 3"))
Result:
{'H': 1, 'e': 1, 'l': 3, 'o': 2, 'W': 1, 'r': 1, 'd': 1}
('l', 3)
{'g': 3, 'c': 3, 'b': 2}
('c', 3)
{'g': 3, 'H': 3, 'A': 4, 'a': 3, 'c': 4, 'b': 2, ' ': 2, '1': 1, '2': 1, '3': 1}
('A', 4)
So: l and 3, c and 3, A and 4
def most_popular_character(my_string):
history_l = [l for l in my_string] #each letter in string
char_dict = {} #creating dict
for item in history_l: #for each letter in string
char_dict[item] = history_l.count(item)
return [max(char_dict.values()),min(char_dict.values())]
I didn't understand the last part of minimum frequency, so I make this function return a maximum frequency and a minimum frequency as a list!
Use a Counter to count the characters, and use the max function to select the "biggest" character according to your two criteria.
>>> from collections import Counter
>>> def most_popular_character(my_string):
... chars = Counter(my_string)
... return max(chars, key=lambda c: (chars[c], -ord(c)))
...
>>> most_popular_character("HelloWorld")
'l'
>>> most_popular_character("gggcccbb")
'c'
Note that using max is more efficient than sorting the entire dictionary, because it only needs to iterate over the dictionary once and find the single largest item, as opposed to sorting every item relative to every other item.
I am using Python 3.3
I need to create two lists, one for the unique words and the other for the frequencies of the word.
I have to sort the unique word list based on the frequencies list so that the word with the highest frequency is first in the list.
I have the design in text but am uncertain how to implement it in Python.
The methods I have found so far use either Counter or dictionaries which we have not learned. I have already created the list from the file containing all the words but do not know how to find the frequency of each word in the list. I know I will need a loop to do this but cannot figure it out.
Here's the basic design:
original list = ["the", "car",....]
newlst = []
frequency = []
for word in the original list
if word not in newlst:
newlst.append(word)
set frequency = 1
else
increase the frequency
sort newlst based on frequency list
use this
from collections import Counter
list1=['apple','egg','apple','banana','egg','apple']
counts = Counter(list1)
print(counts)
# Counter({'apple': 3, 'egg': 2, 'banana': 1})
You can use
from collections import Counter
It supports Python 2.7，read more information here
1.
>>>c = Counter('abracadabra')
>>>c.most_common(3)
[('a', 5), ('r', 2), ('b', 2)]
use dict
>>>d={1:'one', 2:'one', 3:'two'}
>>>c = Counter(d.values())
[('one', 2), ('two', 1)]
But, You have to read the file first, and converted to dict.
2.
it's the python docs example,use re and Counter
# Find the ten most common words in Hamlet
>>> import re
>>> words = re.findall(r'\w+', open('hamlet.txt').read().lower())
>>> Counter(words).most_common(10)
[('the', 1143), ('and', 966), ('to', 762), ('of', 669), ('i', 631),
('you', 554), ('a', 546), ('my', 514), ('hamlet', 471), ('in', 451)]
words = file("test.txt", "r").read().split() #read the words into a list.
uniqWords = sorted(set(words)) #remove duplicate words and sort
for word in uniqWords:
print words.count(word), word
Pandas answer:
import pandas as pd
original_list = ["the", "car", "is", "red", "red", "red", "yes", "it", "is", "is", "is"]
pd.Series(original_list).value_counts()
If you wanted it in ascending order instead, it is as simple as:
pd.Series(original_list).value_counts().sort_values(ascending=True)
Yet another solution with another algorithm without using collections:
def countWords(A):
dic={}
for x in A:
if not x in dic: #Python 2.7: if not dic.has_key(x):
dic[x] = A.count(x)
return dic
dic = countWords(['apple','egg','apple','banana','egg','apple'])
sorted_items=sorted(dic.items()) # if you want it sorted
One way would be to make a list of lists, with each sub-list in the new list containing a word and a count:
list1 = [] #this is your original list of words
list2 = [] #this is a new list
for word in list1:
if word in list2:
list2.index(word)[1] += 1
else:
list2.append([word,0])
Or, more efficiently:
for word in list1:
try:
list2.index(word)[1] += 1
except:
list2.append([word,0])
This would be less efficient than using a dictionary, but it uses more basic concepts.
You can use reduce() - A functional way.
words = "apple banana apple strawberry banana lemon"
reduce( lambda d, c: d.update([(c, d.get(c,0)+1)]) or d, words.split(), {})
returns:
{'strawberry': 1, 'lemon': 1, 'apple': 2, 'banana': 2}
Using Counter would be the best way, but if you don't want to do that, you can implement it yourself this way.
# The list you already have
word_list = ['words', ..., 'other', 'words']
# Get a set of unique words from the list
word_set = set(word_list)
# create your frequency dictionary
freq = {}
# iterate through them, once per unique word.
for word in word_set:
freq[word] = word_list.count(word) / float(len(word_list))
freq will end up with the frequency of each word in the list you already have.
You need float in there to convert one of the integers to a float, so the resulting value will be a float.
Edit:
If you can't use a dict or set, here is another less efficient way:
# The list you already have
word_list = ['words', ..., 'other', 'words']
unique_words = []
for word in word_list:
if word not in unique_words:
unique_words += [word]
word_frequencies = []
for word in unique_words:
word_frequencies += [float(word_list.count(word)) / len(word_list)]
for i in range(len(unique_words)):
print(unique_words[i] + ": " + word_frequencies[i])
The indicies of unique_words and word_frequencies will match.
The ideal way is to use a dictionary that maps a word to it's count. But if you can't use that, you might want to use 2 lists - 1 storing the words, and the other one storing counts of words. Note that order of words and counts matters here. Implementing this would be hard and not very efficient.
Try this:
words = []
freqs = []
for line in sorted(original list): #takes all the lines in a text and sorts them
line = line.rstrip() #strips them of their spaces
if line not in words: #checks to see if line is in words
words.append(line) #if not it adds it to the end words
freqs.append(1) #and adds 1 to the end of freqs
else:
index = words.index(line) #if it is it will find where in words
freqs[index] += 1 #and use the to change add 1 to the matching index in freqs
Here is code support your question
is_char() check for validate string count those strings alone, Hashmap is dictionary in python
def is_word(word):
cnt =0
for c in word:
if 'a' <= c <='z' or 'A' <= c <= 'Z' or '0' <= c <= '9' or c == '$':
cnt +=1
if cnt==len(word):
return True
return False
def words_freq(s):
d={}
for i in s.split():
if is_word(i):
if i in d:
d[i] +=1
else:
d[i] = 1
return d
print(words_freq('the the sky$ is blue not green'))
for word in original_list:
words_dict[word] = words_dict.get(word,0) + 1
sorted_dt = {key: value for key, value in sorted(words_dict.items(), key=lambda item: item[1], reverse=True)}
keys = list(sorted_dt.keys())
values = list(sorted_dt.values())
print(keys)
print(values)
Simple way
d = {}
l = ['Hi','Hello','Hey','Hello']
for a in l:
d[a] = l.count(a)
print(d)
Output : {'Hi': 1, 'Hello': 2, 'Hey': 1}
word and frequency if you need
def counter_(input_list_):
lu = []
for v in input_list_:
ele = (v, lc.count(v)/len(lc)) #if you don't % remove <</len(lc)>>
if ele not in lu:
lu.append(ele)
return lu
counter_(['a', 'n', 'f', 'a'])
output:
[('a', 0.5), ('n', 0.25), ('f', 0.25)]
the best thing to do is :
def wordListToFreqDict(wordlist):
wordfreq = [wordlist.count(p) for p in wordlist]
return dict(zip(wordlist, wordfreq))
then try to :
wordListToFreqDict(originallist)
Beginner here. I'm currently writing a program that will turn every word in a "movie reviews" text file into a key, storing a list value containing the review number and the number of times the word has been seen. For example:
4 I loved it
1 I hated it
... might look like this as a dictionary:
words['i'] = [5,2]
words['loved'] = [4,1]
words['it'] = [5,2]
words['hated'] = [1,1]
However, this is the output I've been getting:
{'i': [1, 2], 'loved': [4, 1], 'it': [1, 2], 'hated': [1, 1]}
I figured out the counter part, but I can't figure out how to update the review number. Here is my code so far:
def main():
reviews = open("testing.txt", "r")
data = reviews.read();
reviews.close()
# create new dictionary
words = {}
# iterate over every review in text file
splitlines = data.split("\n")
for line in splitlines:
lower = line.lower()
value = lower.split()
rev = int(value[0])
for word in value:
if word.isalpha():
count = 1
if word not in words:
words[word] = [rev, count]
else:
words[word] = [rev, count + 1]
How can I update the review number count?
This is pretty easy to do. Assuming each key has only 2 items in the value list:
if word not in words:
words[word] = [rev, 1]
else:
temp = words[word][1]
words[word] = [rev, temp + 1]
When updating the count, you're using count + 1, but count will always be 1 here; you need to retrieve the existing count first, using something like: count = words[word][1]
my code creates for every document I am processing a vector based Bag-of-words.
It works and prints the frequency of every single word in the document. Additionally I would like to print every word just right in front of the number, just like this:
['word', 15]
I tried it on my own. What I get right now looks like this:
This is my code:
for doc in docsClean:
bag_vector = np.zeros(len(doc))
for w in doc:
for i,word in enumerate(doc):
if word == w:
bag_vector[i] += 1
print(bag_vector)
print("{0},{1}\n".format(w,bag_vector[i]))
I would suggest using a dict to store the frequency of each word.
There is already an inbuilt python feature to do this - collections.Counter.
from collections import Counter
# Random words
words = ['lacteal', 'brominating', 'postmycotic', 'legazpi', 'enclosing', 'arytaenoid', 'brominating', 'postmycotic', 'legazpi', 'enclosing']
frequency = Counter(words)
print(frequency)
Output:
Counter({'brominating': 2, 'postmycotic': 2, 'legazpi': 2, 'enclosing': 2, 'lacteal': 1, 'arytaenoid': 1})
If, for any reason, you don't want to use collections.Counter, here is a simple code to do the same task.
words = ['lacteal', 'brominating', 'postmycotic', 'legazpi', 'enclosing', 'arytaenoid', 'brominating', 'postmycotic', 'legazpi', 'enclosing']
freq = {} # Empty dict
for word in words:
freq[word] = freq.get(word, 0) + 1
print(freq)
This code works by adding 1 to the frequency of word, if it is already present in freq, otherwise freq.get(word, 0) returns 0, so the frequency of a new word gets stored as 1.
Output:
{'lacteal': 1, 'brominating': 2, 'postmycotic': 2, 'legazpi': 2, 'enclosing': 2, 'arytaenoid': 1}
I am using Python 3.3
I need to create two lists, one for the unique words and the other for the frequencies of the word.
I have to sort the unique word list based on the frequencies list so that the word with the highest frequency is first in the list.
I have the design in text but am uncertain how to implement it in Python.
The methods I have found so far use either Counter or dictionaries which we have not learned. I have already created the list from the file containing all the words but do not know how to find the frequency of each word in the list. I know I will need a loop to do this but cannot figure it out.
Here's the basic design:
original list = ["the", "car",....]
newlst = []
frequency = []
for word in the original list
if word not in newlst:
newlst.append(word)
set frequency = 1
else
increase the frequency
sort newlst based on frequency list
use this
from collections import Counter
list1=['apple','egg','apple','banana','egg','apple']
counts = Counter(list1)
print(counts)
# Counter({'apple': 3, 'egg': 2, 'banana': 1})
You can use
from collections import Counter
It supports Python 2.7，read more information here
1.
>>>c = Counter('abracadabra')
>>>c.most_common(3)
[('a', 5), ('r', 2), ('b', 2)]
use dict
>>>d={1:'one', 2:'one', 3:'two'}
>>>c = Counter(d.values())
[('one', 2), ('two', 1)]
But, You have to read the file first, and converted to dict.
2.
it's the python docs example,use re and Counter
# Find the ten most common words in Hamlet
>>> import re
>>> words = re.findall(r'\w+', open('hamlet.txt').read().lower())
>>> Counter(words).most_common(10)
[('the', 1143), ('and', 966), ('to', 762), ('of', 669), ('i', 631),
('you', 554), ('a', 546), ('my', 514), ('hamlet', 471), ('in', 451)]
words = file("test.txt", "r").read().split() #read the words into a list.
uniqWords = sorted(set(words)) #remove duplicate words and sort
for word in uniqWords:
print words.count(word), word
Pandas answer:
import pandas as pd
original_list = ["the", "car", "is", "red", "red", "red", "yes", "it", "is", "is", "is"]
pd.Series(original_list).value_counts()
If you wanted it in ascending order instead, it is as simple as:
pd.Series(original_list).value_counts().sort_values(ascending=True)
Yet another solution with another algorithm without using collections:
def countWords(A):
dic={}
for x in A:
if not x in dic: #Python 2.7: if not dic.has_key(x):
dic[x] = A.count(x)
return dic
dic = countWords(['apple','egg','apple','banana','egg','apple'])
sorted_items=sorted(dic.items()) # if you want it sorted
One way would be to make a list of lists, with each sub-list in the new list containing a word and a count:
list1 = [] #this is your original list of words
list2 = [] #this is a new list
for word in list1:
if word in list2:
list2.index(word)[1] += 1
else:
list2.append([word,0])
Or, more efficiently:
for word in list1:
try:
list2.index(word)[1] += 1
except:
list2.append([word,0])
This would be less efficient than using a dictionary, but it uses more basic concepts.
You can use reduce() - A functional way.
words = "apple banana apple strawberry banana lemon"
reduce( lambda d, c: d.update([(c, d.get(c,0)+1)]) or d, words.split(), {})
returns:
{'strawberry': 1, 'lemon': 1, 'apple': 2, 'banana': 2}
Using Counter would be the best way, but if you don't want to do that, you can implement it yourself this way.
# The list you already have
word_list = ['words', ..., 'other', 'words']
# Get a set of unique words from the list
word_set = set(word_list)
# create your frequency dictionary
freq = {}
# iterate through them, once per unique word.
for word in word_set:
freq[word] = word_list.count(word) / float(len(word_list))
freq will end up with the frequency of each word in the list you already have.
You need float in there to convert one of the integers to a float, so the resulting value will be a float.
Edit:
If you can't use a dict or set, here is another less efficient way:
# The list you already have
word_list = ['words', ..., 'other', 'words']
unique_words = []
for word in word_list:
if word not in unique_words:
unique_words += [word]
word_frequencies = []
for word in unique_words:
word_frequencies += [float(word_list.count(word)) / len(word_list)]
for i in range(len(unique_words)):
print(unique_words[i] + ": " + word_frequencies[i])
The indicies of unique_words and word_frequencies will match.
The ideal way is to use a dictionary that maps a word to it's count. But if you can't use that, you might want to use 2 lists - 1 storing the words, and the other one storing counts of words. Note that order of words and counts matters here. Implementing this would be hard and not very efficient.
Try this:
words = []
freqs = []
for line in sorted(original list): #takes all the lines in a text and sorts them
line = line.rstrip() #strips them of their spaces
if line not in words: #checks to see if line is in words
words.append(line) #if not it adds it to the end words
freqs.append(1) #and adds 1 to the end of freqs
else:
index = words.index(line) #if it is it will find where in words
freqs[index] += 1 #and use the to change add 1 to the matching index in freqs
Here is code support your question
is_char() check for validate string count those strings alone, Hashmap is dictionary in python
def is_word(word):
cnt =0
for c in word:
if 'a' <= c <='z' or 'A' <= c <= 'Z' or '0' <= c <= '9' or c == '$':
cnt +=1
if cnt==len(word):
return True
return False
def words_freq(s):
d={}
for i in s.split():
if is_word(i):
if i in d:
d[i] +=1
else:
d[i] = 1
return d
print(words_freq('the the sky$ is blue not green'))
for word in original_list:
words_dict[word] = words_dict.get(word,0) + 1
sorted_dt = {key: value for key, value in sorted(words_dict.items(), key=lambda item: item[1], reverse=True)}
keys = list(sorted_dt.keys())
values = list(sorted_dt.values())
print(keys)
print(values)
Simple way
d = {}
l = ['Hi','Hello','Hey','Hello']
for a in l:
d[a] = l.count(a)
print(d)
Output : {'Hi': 1, 'Hello': 2, 'Hey': 1}
word and frequency if you need
def counter_(input_list_):
lu = []
for v in input_list_:
ele = (v, lc.count(v)/len(lc)) #if you don't % remove <</len(lc)>>
if ele not in lu:
lu.append(ele)
return lu
counter_(['a', 'n', 'f', 'a'])
output:
[('a', 0.5), ('n', 0.25), ('f', 0.25)]
the best thing to do is :
def wordListToFreqDict(wordlist):
wordfreq = [wordlist.count(p) for p in wordlist]
return dict(zip(wordlist, wordfreq))
then try to :
wordListToFreqDict(originallist)