Python find similar strings in list
Let's say I have a Show
How can I find the In this case, we would have So the strategy is to sort the list words from the closest word to the furthest. I thought about something like this
but it's very slow in large lists. UPDATE When we deal with data from different sources, we often encounter one problem – some strings could be spelled differently, but they have the same meaning. We humans can identify the meanings right away, but machines cannot. This short tutorial will cover how to find similar strings using Python. Machines don’t really understand the human language…For example, we have two sentences:
We humans can tell that
So how can we let the machine recognize that these two sentences mean the same thing? Applying machine learning technique is one way, but today we’ll show something much easier to use. Introducing The Levenshtein DistanceIt turns out that there’s a formula called Levenshtein distance that measures the minimum of single-character edits required to change one string into the other string. This distance is named after the Soviet mathematician Vladimir Levenshtein. In this tutorial, we will leave out all the theoretical details, but if you are interested, Wikipedia is a good starting point. Fuzzy String Matching In PythonThe appropriate terminology for finding similar strings is called a fuzzy string matching. We are going to use a library called fuzzywuzzy. Although it has a funny name, it a very popular library for fuzzy string matching. The fuzzywuzzy library can calculate the Levenshtein distance, and it has a few other powerful functions to help us with fuzzy string matching. Let’s start from something easy, like comparing two words. Then we’ll move on to more complicated scenarios, such as comparing multiple sentences. Here we go! Let’s first install the library. If you are new to this blog and need help with installing Python and libraries, read this tutorial here.
Single Word ExampleStarting with the simplest example. What do you think the computer views these two words: “Bezos” and “bezos”? Of course, they are not the same. Because of the capital letter “B” does not equal to the lower case “b”!
It’s rather easy to match these two words. we can simply make both words all lower cases (or upper cases), then compare again. We can use the String
Multiple Words ExampleYou might already know that “Jeff” is the short name for “Jeffery”, but apparently machines don’t know that yet.
Now, using the fuzzy string matching technique, we get a number of 87. The
Let’s now introduce another variable n3 = “Bezos”, and then calculate the Levenshtein distance ratio with both “Jeff Bezos” and “Jeffery Bezos”. The matching results are very poor. This is because by definition of the Levenshtein distance, it takes many edits to change “Bezos” to either “Jeff Bezos” or “Jeffery Bezos”.
We can use fuzzywuzzy’s
Sentence ExampleLet’s take it a step further and compare two sentences.
Note one sentence contains both upper and lower case letters, and the other sentence contains only upper case letters. We need to help the The performance is still very poor with the Do not worry, because the fuzzywuzzy library provides other powerful functions for string comparison!
To see why the
It’s clear that by the end of the above process, the two strings Sentence Example – ContinuedNow let’s review our original question at the beginning of this tutorial. We’ll first try the
This time, the fuzzywuzzy provides another useful function to solve this problem: This function is very similar to
Let’s try it on the two strings
What’s next?Now we are equipped with the knowledge of fuzzy string matching in Python. In the next tutorial, we’ll walk through some examples how to use fuzzy string matching together with pandas and Excel. How do you find similar strings in Python?import string def match(a,b): a,b = a. lower(), b. lower() error = 0 for i in string.. Normalized, metric, similarity and distance.. (Normalized) similarity and distance.. Metric distances.. Shingles (n-gram) based similarity and distance.. Levenshtein.. Normalized Levenshtein.. Weighted Levenshtein.. Damerau-Levenshtein.. How do you find similar words in Python?How to Find Synonyms of a Word with NLTK WordNet and Python?. Import NLTK.corpus.. Import WordNet from NLTK.Corpus.. Create a list for assigning the synonym values of the word.. Use the “synsets” method.. use the “syn. ... . Call the synonyms of the word with NLTK WordNet within a set.. How do you find similar strings?Hamming Distance, named after the American mathematician, is the simplest algorithm for calculating string similarity. It checks the similarity by comparing the changes in the number of positions between the two strings.
How do you check if a string is present in a list of strings in Python?We can also use count() function to get the number of occurrences of a string in the list. If its output is 0, then it means that string is not present in the list. l1 = ['A', 'B', 'C', 'D', 'A', 'A', 'C'] s = 'A' count = l1. count(s) if count > 0: print(f'{s} is present in the list for {count} times.
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