Extracting dates that are in different formats using regex and sorting them - pandas

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被撕碎了的回忆 2020-12-01 17:40

I am new to text mining and I need to extract the dates from a *.txt file and sort them. The dates are in between the sentences ( each line) and their format can potentially

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  • 2020-12-01 18:26

    I think this is one of the coursera text mining assignment. Well you can use regex and extract to get the solution. dates.txt i.e

    doc = []
    with open('dates.txt') as file:
        for line in file:
            doc.append(line)
    
    df = pd.Series(doc)
    
    def date_sorter():
        # Get the dates in the form of words
        one = df.str.extract(r'((?:\d{,2}\s)?(?:Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)[a-z]*(?:-|\.|\s|,)\s?\d{,2}[a-z]*(?:-|,|\s)?\s?\d{2,4})')
        # Get the dates in the form of numbers
        two = df.str.extract(r'((?:\d{1,2})(?:(?:\/|-)\d{1,2})(?:(?:\/|-)\d{2,4}))')
        # Get the dates where there is no days i.e only month and year  
        three = df.str.extract(r'((?:\d{1,2}(?:-|\/))?\d{4})')
        #Convert the dates to datatime and by filling the nans in two and three. Replace month name because of spelling mistake in the text file.
        dates = pd.to_datetime(one.fillna(two).fillna(three).replace('Decemeber','December',regex=True).replace('Janaury','January',regex=True))
    return pd.Series(dates.sort_values())
    
    date_sorter()
    

    Output:

    9     1971-04-10
    84    1971-05-18
    2     1971-07-08
    53    1971-07-11
    28    1971-09-12
    474   1972-01-01
    153   1972-01-13
    13    1972-01-26
    129   1972-05-06
    98    1972-05-13
    111   1972-06-10
    225   1972-06-15
    31    1972-07-20
    171   1972-10-04
    191   1972-11-30
    486   1973-01-01
    335   1973-02-01
    415   1973-02-01
    36    1973-02-14
    405   1973-03-01
    323   1973-03-01
    422   1973-04-01
    375   1973-06-01
    380   1973-07-01
    345   1973-10-01
    57    1973-12-01
    481   1974-01-01
    436   1974-02-01
    104   1974-02-24
    299   1974-03-01
    

    If you want to return only the index then return pd.Series(dates.sort_values().index)

    Parsing of first regex

     #?: Non-capturing group 
    
    ((?:\d{,2}\s)? # The two digits group. `?` refers to preceding token or group. Here the digits of 2 or 1 and space occurring once or less.  
    
     (?:Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)[a-z]* # The words in group ending with any letters `[]` occuring any number of times (`*`). 
    
     (?:-|\.|\s|,) # Pattern matching -,.,space 
    
     \s? #(`?` here it implies only to space i.e the preceding token)
    
     \d{,2}[a-z]* # less than or equal to two digits having any number of letters at the end (`*`). (Eg: may be 1st, 13th , 22nd , Jan , December etc ) . 
    
     (?:-|,|\s)?# The characters -/,/space may occur once and may not occur because of `?` at the end
    
     \s? # space may occur or may not occur at all (maximum is 1) (`?` here it refers only to space)
    
     \d{2,4}) # Match digit which is 2 or 4   
    

    Hope it helps.

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