Install NRC Lexicon from within Jupyter Notebook

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1.Upgrade Python version (if needed)

import sys !{sys.executable} -m pip install --upgrade pip

Expected output:

Requirement already satisfied: pip in c:\portable\jupyterlab-portable-3.1.0-3.9\apps\lib\site-packages (21.2.1) Collecting pip Downloading pip-21.2.4-py3-none-any.whl (1.6 MB) Installing collected packages: pip Attempting uninstall: pip Found existing installation: pip 21.2.1 Uninstalling pip-21.2.1: Successfully uninstalled pip-21.2.1 Successfully installed pip-21.2.4

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2.Install NRC Lexicon

!{sys.executable} -m pip install NRCLex

Expected Output

Collecting NRCLex Downloading NRCLex-3.0.0.tar.gz (396 kB) Collecting textblob Downloading textblob-0.15.3-py2.py3-none-any.whl (636 kB) Collecting nltk>=3.1 Downloading nltk-3.6.3-py3-none-any.whl (1.5 MB) Collecting joblib Downloading joblib-1.0.1-py3-none-any.whl (303 kB) Collecting regex Downloading regex-2021.8.28-cp39-cp39-win_amd64.whl (271 kB) Collecting click Downloading click-8.0.1-py3-none-any.whl (97 kB) Collecting tqdm Downloading tqdm-4.62.3-py2.py3-none-any.whl (76 kB) Requirement already satisfied: colorama in c:\portable\jupyterlab-portable-3.1.0-3.9\apps\lib\site-packages (from click->nltk>=3.1->textblob->NRCLex) (0.4.4) Using legacy 'setup.py install' for NRCLex, since package 'wheel' is not installed. Installing collected packages: tqdm, regex, joblib, click, nltk, textblob, NRCLex Running setup.py install for NRCLex: started Running setup.py install for NRCLex: finished with status 'done' Successfully installed NRCLex-3.0.0 click-8.0.1 joblib-1.0.1 nltk-3.6.3 regex-2021.8.28 textblob-0.15.3 tqdm-4.62.3

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Note: Even after the installation of NRC Lexicon, MissingCorpusError may occur while running programs. So it is recommended to also install textblob.download_corpora.

3.Install textblob.download_corpora (Recommended)

import sys !{sys.executable} -m textblob.download_corpora

Expected Output

[nltk_data] Downloading package brown to C:\Portable\JupyterLab- [nltk_data] Portable-3.1.0-3.9\apps\nltk_data... [nltk_data] Unzipping corpora\brown.zip. [nltk_data] Downloading package punkt to C:\Portable\JupyterLab- [nltk_data] Portable-3.1.0-3.9\apps\nltk_data... [nltk_data] Unzipping tokenizers\punkt.zip. [nltk_data] Downloading package wordnet to C:\Portable\JupyterLab- [nltk_data] Portable-3.1.0-3.9\apps\nltk_data... [nltk_data] Unzipping corpora\wordnet.zip. [nltk_data] Downloading package averaged_perceptron_tagger to [nltk_data] C:\Portable\JupyterLab- [nltk_data] Portable-3.1.0-3.9\apps\nltk_data... [nltk_data] Unzipping taggers\averaged_perceptron_tagger.zip. [nltk_data] Downloading package conll2000 to C:\Portable\JupyterLab- [nltk_data] Portable-3.1.0-3.9\apps\nltk_data... [nltk_data] Unzipping corpora\conll2000.zip. [nltk_data] Downloading package movie_reviews to [nltk_data] C:\Portable\JupyterLab- [nltk_data] Portable-3.1.0-3.9\apps\nltk_data... [nltk_data] Unzipping corpora\movie_reviews.zip.

REFERENCE:

• https://www.geeksforgeeks.org/emotion-classification-using-nrc-lexicon-in-python/
• https://medium.com/@shivangisareen/for-anyone-using-jupyter-notebook-installing-packages-18a9468d0c1c

ADDITIONAL:

Install scikit-learn :

Note: Scikit-learn (Sklearn) is the most useful and robust library for machine learning in Python. It provides a selection of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction via a consistence interface in Python.
import sys !{sys.executable} -m pip install -U scikit-learn