How to download the NLTK library?

This recipe helps you download the NLTK library.

Recipe Objective: How to download the NLTK library?

This step-by-step recipe will show you how to download NLTK in Jupyter Notebook and how to download Specific packages from the NLTK library.

How To Download NLTK in Jupyter Notebook?

The below steps will help you install and download the NLTK library in Jupter Notebook.

Step 1 - Install the NLTK in Jupyter Notebook Using pip command

pip install nltk

If it is already installed or present in your notebook, it will prompt Requirement already Satisfied; otherwise, it will start downloading and installing the NLTK library in your notebook

Step 2 - How to Import NLTK in Python

This step will show you how to import NLTK in Jupyter Notebook.

import nltk

By using the above command, you can import the nltk library for your further operations.

Step 3 - Installing All from NLTK library

nltk.download('all')

If we want to download all packages from the NLTk library, then by using the above command, we can download the packages that will unzip all the packages from NLTK Corpus, for example, Stemmer, lemmatizer, and many more.

Step 4 - Downloading lemmatizers from NLTK

nltk.download('wordnet') from nltk.stem import WordNetLemmatizerd

You can use the above command to download WordNet Lemmatizer from the NLTK library and import it for further operations.

Step 5 - How To Download NLTK Stopwords

nltk.download('stopwords')

By using the above command, we will be able to download stopwords from the NLTK library.

How to Use NLTK in Jupyter Notebook?

Here is an example to show you how to NLTK in Jupyter Notebook to remove stopwords from text-

import nltk

def remove_stopwords(text):

  stop_words = nltk.corpus.stopwords.words('english')

  filtered_text = [word for word in text.split() if word not in stop_words]

  return filtered_text

text = "This is a sentence with some stopwords."

filtered_text = remove_stopwords(text)

print(filtered_text)

How to Install NLTK in Visual Studio Code?

You can install NLTK in VS Code using the following steps-

  1. Open Visual Studio Code.

  2. Click on the Extensions icon in the left sidebar.

  3. Search for "Python" and install the "Python" extension.

  4. Open a new file and create a Python script.

  5. Import the NLTK library:

import nltk

  1. Use the nltk.download() function to download the NLTK data:

nltk.download('all')

This will download all the NLTK data, which is about 1.5 GB.

FAQs

  1. How do I install NLTK using pip?

You can install NLTK using the command 'pip install nltk' in Jupyter Notebook.

 

What Users are saying..

profile image

Savvy Sahai

Data Science Intern, Capgemini
linkedin profile url

As a student looking to break into the field of data engineering and data science, one can get really confused as to which path to take. Very few ways to do it are Google, YouTube, etc. I was one of... Read More

Relevant Projects

MLOps AWS Project on Topic Modeling using Gunicorn Flask
In this project we will see the end-to-end machine learning development process to design, build and manage reproducible, testable, and evolvable machine learning models by using AWS

Build a Graph Based Recommendation System in Python-Part 2
In this Graph Based Recommender System Project, you will build a recommender system project for eCommerce platforms and learn to use FAISS for efficient similarity search.

BERT Text Classification using DistilBERT and ALBERT Models
This Project Explains how to perform Text Classification using ALBERT and DistilBERT

Recommender System Machine Learning Project for Beginners-3
Content Based Recommender System Project - Building a Content-Based Product Recommender App with Streamlit

Recommender System Machine Learning Project for Beginners-4
Collaborative Filtering Recommender System Project - Comparison of different model based and memory based methods to build recommendation system using collaborative filtering.

Demand prediction of driver availability using multistep time series analysis
In this supervised learning machine learning project, you will predict the availability of a driver in a specific area by using multi step time series analysis.

Time Series Forecasting Project-Building ARIMA Model in Python
Build a time series ARIMA model in Python to forecast the use of arrival rate density to support staffing decisions at call centres.

Azure Text Analytics for Medical Search Engine Deployment
Microsoft Azure Project - Use Azure text analytics cognitive service to deploy a machine learning model into Azure Databricks

PyCaret Project to Build and Deploy an ML App using Streamlit
In this PyCaret Project, you will build a customer segmentation model with PyCaret and deploy the machine learning application using Streamlit.

House Price Prediction Project using Machine Learning in Python
Use the Zillow Zestimate Dataset to build a machine learning model for house price prediction.