Cleaning up the data (corpus) based on the provided instruction below. 1) Remove all the numbers (EXCEPT for 19 ) 2) Remove the dates/month names (January, February, etc...) 3) Remove fund names...

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Cleaning up the data (corpus) based on the provided instruction below.

1) Remove all the numbers (EXCEPT for 19) 2) Remove the dates/month names (January, February, etc...)

3) Remove fund names (i.e., invesco, pimco, blackrock, TIAA, vanguard, etc.

4) There are a lot of joined words example, "localregional" when there should be a space "local regional". Correct the errors of joined words using one or more of the following approaches (or using any approach):

Generate a dictionary from the corpus and pass it (or the whole corpus?) through a script that either identified misspellings, errors, etc. or can compare it with an english language dictionary. A quick search for cleaning corpus scripts suggested this as a one such possible script: https://predictivehacks.com/languagetool-grammar-and-spell-checker-in-python/#:~:text=LanguageTool%20is%20an%20open%2Dsource,through%20a%20command%2Dline%20interface.

corpusphsentence-1-s2wu4z2s.xlsx

Answered Same Day Apr 20, 2021

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Sandeep Kumar answered on Apr 21 2021

133 Votes

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Cleaning up the data (corpus) based on the provided instruction below. 1) Remove all the numbers (EXCEPT for 19 ) 2) Remove the dates/month names (January, February, etc...) 3) Remove fund names...

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