Sentiment Analysis for the tweets of @realDonaldTrump done using TextBlob. TextBlob is a Python (2 and 3) library for processing textual data. It provides a consistent API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, and more. TextBlob objects can be treated as if they were Python strings that learned how to do Natural Language Processing. TextBlob heavily depends on Python NLTK. Corpora used by NLTK is the default corpora for TextBlob as well.
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NumPy: This is the fundamental package for scientific computing with Python. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data.
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Pandas: This is an open source library providing high-performance, easy-to-use data structures and data analysis tools.
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Matplotlib: This is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.
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Textblob: This is a Python library for processing textual data. It provides a simple API for diving into common natural language processing (NLP) tasks.
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NLTK: This is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language.
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WordCloud: This is a data visualization technique used for representing text data in which the size of each word indicates its frequency or importance. Significant textual data points can be highlighted using a word cloud.