5/26/2023 0 Comments Python count run of same value![]() The brute force search and count() methods outperform the Counter, mainly because the Counter inherently counts all words instead of one. Print( "Brute Force: %ss" % timeit.Timer(bruteForce(words, 'hello')).timeit( 1000)) Print( "Counter: %ss" % timeit.Timer(counterObject(words, 'hello')).timeit( 1000)) ![]() Print( "count(): %ss" % timeit.Timer(countFunction(words, 'hello')).timeit( 1000)) Print( "Counter: %ss" % timeit.Timer(counterObject(words)).timeit( 1000))Īlternatively, if you're looking for a single word: import numpy as npĭef countFunction( words, word_to_search): def _countFunction(): return unt(word_to_search)ĭef counterObject( words, word_to_search): def _counterObject(): return collections.Counter(words)ĭef bruteForce( words, word_to_search): def _bruteForce(): Print( "count(): %ss" % timeit.Timer(countFunction(words)).timeit( 1000)) Print( "Pandas/Numpy: %ss" % timeit.Timer(pdNumpy(words)).timeit( 1000)) The task can be broken down into finding occurrences for all words or a single word, and we'll be doing benchmarks for both, starting with all words: import numpy as npĭef pdNumpy( words): def _pdNumpy(): return pd.value_counts(np.array(words))ĭef countFunction( words): def _countFunction():ĭef counterObject( words): def _counterObject(): return collections.Counter(words) Let's benchmark all of these to see how they perform. Naturally - you'll be searching for the most efficient solution if you're dealing with large corpora of words. If you run this code you should see this output: "hello" appears 3 time(s) We can wrap the list into a Numpy array, and then call the value_counts() method of the pd instance (which is also available for all DataFrame instances): import numpy as np The shortest and easiest way to get value counts in an easily-manipulable format ( DataFrame) is via Numpy and Pandas. ![]() In practice, you'll use Pandas/Nunpy, the count() function or a Counter as they're pretty convenient to use. This guide will show you three different ways to count the number of word occurrences in a Python list: Say we have a list - we have two occurrences on "b" and one of "a". Counting the word frequency in a list element in Python is a relatively common task - especially when creating distribution data for histograms.
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