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Analysis using Natural Language Toolkit(NLTK), Numpy, Pandas and Matplotlib

Using various corpus available through NLTK did analysis like calculating frequency of texts for unique situations, finding person with lead roles, unusual words used in web chats etc.
Created different folder structures based on data contained in JSON files according to locations, dates, section names etc.
Analyzed data and pushed useful information from raw datasets into CSV files.
Using data from the CSV files, plotted graphs for the same using Matplotlib.

Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
.ipynb_checkpoints		.ipynb_checkpoints
NYT		NYT
NYTArticle		NYTArticle
Age Group.ipynb		Age Group.ipynb
Frequency Characters.ipynb		Frequency Characters.ipynb
Frequent Words.ipynb		Frequent Words.ipynb
Lead Actor.ipynb		Lead Actor.ipynb
Male Female Names.ipynb		Male Female Names.ipynb
NYT Analysis.ipynb		NYT Analysis.ipynb
President Words.ipynb		President Words.ipynb
README.md		README.md
Restaurant _Open_Hour.ipynb		Restaurant _Open_Hour.ipynb
Restaurants_Open_Hour.csv		Restaurants_Open_Hour.csv
Shakespear Words.ipynb		Shakespear Words.ipynb
Trump Headline.ipynb		Trump Headline.ipynb
Unusual Words.ipynb		Unusual Words.ipynb
Zipf's Law.ipynb		Zipf's Law.ipynb
Zipfs_law_list.csv		Zipfs_law_list.csv
recieve.csv		recieve.csv
section.csv		section.csv