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Text Munging using python
Shashank Shanu
2 years ago
We
all know that how much these days social media are becoming popular. Everyone is
showing their presence on it from a small kid to an elder one. Due to these, we
are generating zettabytes and petabytes of text data on a daily. Big companies use
these text data to find the hidden insights into it and stand ahead from most
of their competitors in the market. Facebook, YouTube, Netflix are some of the companies
which use these data to provide the best customer service to their customers.
So
before moving ahead. Let’s try to first understand:
What is Text munging?
Munging
is a technique which is used to clean the messy data by using some kind of transformation
on it.
This
is one of the important techniques as nowadays most of the data which is being
generated are present in the form of unstructured data. These data need some
kind of treatment or cleaning applied on it so that we can find the correct
hidden insights from them.
To
understand it better. Let’s take an example:
In our example, we will try to see how we can apply
some kind of transformation on our text to get some useful results which give some
desirable changes to data.
In a simple language, it is only about transforming
the text we are dealing with.
Example
Here, in our example, we are first shuffling the text
and then rearranging all the letters of the given sentence. Except the first and
the last sentences to get alternate words which may get generated as a misspelt
word during writing by a human.
Let’s see the code:
# import library
import random
import re
# creating a function to perform the task
def replace(a):
word = list(a.group(2))
random.shuffle(word)
return a.group(1) + "".join(word) + a.group(3)
text = "Hello, You should reach the finish line."
print(re.sub(r"(\w)(\w+)(\w)", replace, text))
print(re.sub(r"(\w)(\w+)(\w)", replace, text))
Output:
When we execute the above program, we get the output as given below −
Hlleo, You slouhd raech the fsiinh lnie.
Hlleo, You suolhd raceh the fniish line.From the above results, we can observe how the
words are jumbled except for the first and the last letters. By taking a statistical approach helps us to find the wrong spelling of the words and then
we can decide what are the commonly misspelt words and supply the correct
spelling for them to get the desired results.
I hope after you enjoyed reading this
article and finally, you came to know about Text Munging using python.
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