![]() We can glue these parts together with a placeholder which we will substitute the desired value in: fmt = "".join(sentence for s, e in zip(**2)). This pattern represents a generic sequence of characters. In the case of regular expressions, a regex pattern has to be passed. toreplace: Denotes the value that has to be replaced in the dataframe or series. If you maintained a list of the starting points (which is the start of the string and the end of every group), and a list of the ending points (which is the start of every group, and the end of the string), you could use these to retrieve the parts of the original string you want to keep: start = Įnd = Replace function for regex For using pandas replace function with regex, you need to define 3 parameters: toreplace, regex and value. If you need to analyze the match to extract information about specific group captures, for instance, you can pass a function to the string argument. Your difficulty come in manually building up the original string parts from the spans of the original string. In order to replace text using regular expression use the re.sub function: sub(pattern, repl, string, count, flags) It will replace non-everlaping instances of pattern by the text passed as string. Here is a solution using the original format string, instead of the inverted format string suggested by Reindeerien. I guess someone with more NLTK experience could find a more robust way to replace the words. This version is brittle though, because some verbs appear to be nouns or vice-versa. RegEx Module Python has a built-in package called re, which can be used to work with Regular Expressions. Repl("The sea is blue", "yellow", "elephant") Repl("The sea is blue", "moon", "white", "hate") New_sentence.append(possible_replacements.pop(0)) Possible_replacements = new_words_by_tag.get(tag) Return įor new_word, tag in simple_tags(new_words):įor word, tag in simple_tags(nltk.word_tokenize(sentence)): ) and replace words in the original sentence according to their tags: import nltk You could import it, tags the words (NOUN, ADJ. ![]() You might want to experiment with NLTK, a leading platform for building Python programs to work with human language data: New_string = s verb sĭo you think there is a more straightforward way to implement this? replace() because there is edge cases if the string contains the subject twice for example): def repl(sentence, subject, color, verb): Here is the solution I come with (I can't use. The expected output of such function would look like this: repl("The sea is blue", "moon", "white", "hate") I would like to constuct a function which replaces subject, color and optional verb from this string with others values.Īll strings match a certain regex pattern as follow: regex = r"(?:The|A) (?P\w ) is (?P\w )(?: and I (?P\w ) it)?" Susan Maina 686 Followers Data scientist, Machine Learning Enthusiast. Refresh the page, check Medium ’s site status, or find something interesting to read. Given a string taken from the following set: strings = [ Regular Expressions (Regex) with Examples in Python and Pandas by Susan Maina Towards Data Science Write Sign up Sign In 500 Apologies, but something went wrong on our end.
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