RAJESHVHANKADE / Blackcoffer_Assignment

Web scraping and NLP assignment: Extracts text from URLs, analyzes content, computes variables. Perfect for honing web scraping and NLP skills.

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Blackcoffer_Assignment

Blackcoffer

Consulting Website: https://blackcoffer.com | https://lsalead.com/

Web App Products: https://netclan.com/ | https://insights.blackcoffer.com/ | https://hirekingdom.com/ | https://workcroft.com/

Mobile App Products: Netclan | Bwstory

Data Extraction and NLP

Test Assignment

1. Objective

The objective of this assignment is to extract textual data articles from the given URL and perform text analysis to compute variables that are explained below.

2. Data Extraction

Input.xlsx For each of the articles, given in the input.xlsx file, extract the article text and save the extracted article in a text file with URL_ID as its file name. While extracting text, please make sure your program extracts only the article title and the article text. It should not extract the website header, footer, or anything other than the article text.

NOTE: YOU MUST USE PYTHON PROGRAMMING TO EXTRACT DATA FROM THE URLs. YOU CAN USE BEATIFULSOUP, SELENIUM OR SCRAPY, OR ANY OTHER PYTHON LIBRARIES THAT YOU PREFER FOR DATA CRAWLING.

3. Data Analysis

For each of the extracted texts from the article, perform textual analysis and compute variables, given in the output structure excel file. You need to save the output in the exact order as given in the output structure file, “Output Data Structure.xlsx” NOTE: YOU MUST USE PYTHON PROGRAMMING FOR THE DATA ANALYSIS

4. Variables

The definition of each of the variables given in the “Text Analysis.docx” file. Look for these variables in the analysis document (Text Analysis.docx):

  1. POSITIVE SCORE
  2. NEGATIVE SCORE
  3. POLARITY SCORE
  4. SUBJECTIVITY SCORE
  5. AVG SENTENCE LENGTH
  6. PERCENTAGE OF COMPLEX WORDS
  7. FOG INDEX
  8. AVG NUMBER OF WORDS PER SENTENCE
  9. COMPLEX WORD COUNT
  10. WORD COUNT
  11. SYLLABLE PER WORD
  12. PERSONAL PRONOUNS
  13. AVG WORD LENGTH

5. Output Data Structure

Output Variables:

  1. All input variables in “Input.xlsx”
  2. POSITIVE SCORE
  3. NEGATIVE SCORE
  4. POLARITY SCORE
  5. SUBJECTIVITY SCORE
  6. AVG SENTENCE LENGTH
  7. PERCENTAGE OF COMPLEX WORDS
  8. FOG INDEX
  9. AVG NUMBER OF WORDS PER SENTENCE
  10. COMPLEX WORD COUNT
  11. WORD COUNT
  12. SYLLABLE PER WORD
  13. PERSONAL PRONOUNS
  14. AVG WORD LENGTH Check out the output data structure spreadsheet for the format of your output, i.e. “Output Data Structure.xlsx”.

6. Timeline

6 days, sooner is better.

7. Where to submit

To submit your solution, please fill out this Google form, upload your solution submission to Google Drive, and share the drive url in the Google form: https://forms.gle/nvWAgrCBdq1JkKou8

Make sure your submission contains: a) .py file b) output in csv or Excel file as given in the output structure c) instructions

  1. explaining how you approached the solution
  2. How to run the .py file to generate output
  3. Include all dependencies required

Do not include any other file in the deliverable.

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Web scraping and NLP assignment: Extracts text from URLs, analyzes content, computes variables. Perfect for honing web scraping and NLP skills.

License:MIT License


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