So I'm trying to make this program that will ask the user for input and store the values in an array / list.
Then when a blank line is entered it will tell the user how many of those values are unique.
I'm building this for real life reasons and not as a problem set.
enter: happy
enter: rofl
enter: happy
enter: mpg8
enter: Cpp
enter: Cpp
enter:
There are 4 unique words!
My code is as follows:
# ask for input
ipta = raw_input("Word: ")
# create list
uniquewords = []
counter = 0
uniquewords.append(ipta)
a = 0 # loop thingy
# while loop to ask for input and append in list
while ipta:
ipta = raw_input("Word: ")
new_words.append(input1)
counter = counter + 1
for p in uniquewords:
..and that's about all I've gotten so far.
I'm not sure how to count the unique number of words in a list?
If someone can post the solution so I can learn from it, or at least show me how it would be great, thanks!
I'd use a set myself, but here's yet another way:
uniquewords = []
while True:
ipta = raw_input("Word: ")
if ipta == "":
break
if not ipta in uniquewords:
uniquewords.append(ipta)
print "There are", len(uniquewords), "unique words!"
Use a set:
words = ['a', 'b', 'c', 'a']
unique_words = set(words) # == set(['a', 'b', 'c'])
unique_word_count = len(unique_words) # == 3
Armed with this, your solution could be as simple as:
words = []
ipta = raw_input("Word: ")
while ipta:
words.append(ipta)
ipta = raw_input("Word: ")
unique_word_count = len(set(words))
print "There are %d unique words!" % unique_word_count
How about:
import pandas as pd
#List with all words
words=[]
#Code for adding words
words.append('test')
#When Input equals blank:
pd.Series(words).nunique()
It returns how many unique values are in a list
ipta = raw_input("Word: ") ## asks for input
words = [] ## creates list
while ipta: ## while loop to ask for input and append in list
words.append(ipta)
ipta = raw_input("Word: ")
words.append(ipta)
#Create a set, sets do not have repeats
unique_words = set(words)
print "There are " + str(len(unique_words)) + " unique words!"
ipta = raw_input("Word: ") ## asks for input
words = [] ## creates list
unique_words = set(words)
For ndarray there is a numpy method called unique:
np.unique(array_name)
Examples:
>>> np.unique([1, 1, 2, 2, 3, 3])
array([1, 2, 3])
>>> a = np.array([[1, 1], [2, 3]])
>>> np.unique(a)
array([1, 2, 3])
For a Series there is a function call value_counts():
Series_name.value_counts()
Although a set is the easiest way, you could also use a dict and use some_dict.has(key)
to populate a dictionary with only unique keys and values.
Assuming you have already populated words[]
with input from the user, create a dict mapping the unique words in the list to a number:
word_map = {}
i = 1
for j in range(len(words)):
if not word_map.has_key(words[j]):
word_map[words[j]] = i
i += 1
num_unique_words = len(new_map) # or num_unique_words = i, however you prefer
values, counts = np.unique(words, return_counts=True)
Other method by using pandas
import pandas as pd
LIST = ["a","a","c","a","a","v","d"]
counts,values = pd.Series(LIST).value_counts().values, pd.Series(LIST).value_counts().index
df_results = pd.DataFrame(list(zip(values,counts)),columns=["value","count"])
You can then export results in any format you want
In addition, use collections.Counter to refactor your code:
from collections import Counter
words = ['a', 'b', 'c', 'a']
Counter(words).keys() # equals to list(set(words))
Counter(words).values() # counts the elements' frequency
Output:
['a', 'c', 'b']
[2, 1, 1]
The following should work. The lambda function filter out the duplicated words.
inputs=[]
input = raw_input("Word: ").strip()
while input:
inputs.append(input)
input = raw_input("Word: ").strip()
uniques=reduce(lambda x,y: ((y in x) and x) or x+[y], inputs, [])
print 'There are', len(uniques), 'unique words'
aa="XXYYYSBAA"
bb=dict(zip(list(aa),[list(aa).count(i) for i in list(aa)]))
print(bb)
# output:
# {'X': 2, 'Y': 3, 'S': 1, 'B': 1, 'A': 2}
If you would like to have a histogram of unique values here's oneliner
import numpy as np
unique_labels, unique_counts = np.unique(labels_list, return_counts=True)
labels_histogram = dict(zip(unique_labels, unique_counts))
Source: Stackoverflow.com